Claire Kabdebon

Camille Straboni

Hualin Xiao

Alexandre Cremers

Brent Strickland

Sharon Peperkamp

Does grammatical gender influence how we conceive of objects?

Four years ago, I arrived in Paris alone, carrying the largest suitcase I ever had. Before that, I knew very little about the feeling of carrying a Chinese suitcase in a foreign land, but I did know what I came here for. Now it's about time to pack again. I still have the suitcase I brought from my homeland, only that the items to fill in have changed.

I'm able to complete the four-year PhD thanks to my advisors Brent Strickland and Sharon Peperkamp. They not only initiated me into Psychology, but more importantly helped me develop another way of thinking that is rational and scientific. This may sound surprising, but it is a big challenge to someone with only a background in English language and literature to acquire this kind of reasoning as it is contrary to intuition or imagination-oriented thinking. Their knowledge, skills, attitudes towards science, and ways of doing things have broadened my horizon. As a supervisor, Sharon may give the impression that she goes too much into details (or just perfectionist), but after working four years with her I finally understand that it is a quality I should have to compensate for my impatient and clumsy personality. Now I feel jealous that she was born perfectionist. Brent, on the other hand, always has his eyes on the bigger picture.

He is the one who told me on our first meeting to think about my future career and research agenda. I'm impressed by how efficiently these two minds cooperate to foster a PhD. They have also helped

Chapter 1. Introduction

Gender has multiple facets. When used to refer to biological sex, it is a term for distinguishing a male from a female person with regard to their anatomical and hormonal differences. Put in the context of society, gender is a product of social norms and interactions embodied by the different roles, qualities, and behaviors associated with men and women [START_REF] Eagly | Social Role Theory of Sex Differences[END_REF]. Gender is also an important concept for human languages. Many of the world's languages have a grammatical gender system in which nouns are categorized into different gender classes based on features like sex, animacy, shape and size etc., and following this categorization, words appearing with the nouns, such as adjectives, articles, verbs and pronouns change their forms accordingly [START_REF] Aikhenvald | How gender shapes the world[END_REF][START_REF] Corbett | Gender[END_REF][START_REF] Gygax | A Language Index of Grammatical Gender Dimensions to Study the Impact of Grammatical Gender on the Way We Perceive Women and Men[END_REF]. The meanings and implications of gender vary depending on which facet of the notion one refers to. In this dissertation, I focus on the three aspects of gender and present three empirical studies on how each aspect as well as interactions between them shape various cultural landscapes.

The first study (Chapter 2) investigates the relationship between language and thought, in particular the influence of grammatical gender on the conceptualization of objects. The Neo-Whorfian hypothesis postulating that the structure of one's native language impacts the way one thinks about the world [START_REF] Whorf | Language, thought and reality[END_REF] has earned empirical support among cognitive scientists from various perspectives such as the influence of color terms on color perception (e.g. [START_REF] Davies | A cross-cultural study of colour grouping: Evidence for weak linguistic relativity[END_REF][START_REF] Gilbert | Whorf hypothesis is supported in the right visual field but not the left[END_REF][START_REF] Thierry | Unconscious effects of language-specific terminology on preattentive color perception[END_REF], and the impact of space and time framing in language on speakers' spatial reasoning and conceptualization of time (e.g. [START_REF] Boroditsky | Does Language Shape Thought?: Mandarin and English Speakers' Conceptions of Time[END_REF][START_REF] Haun | Cognitive cladistics and cultural override in Hominid spatial cognition[END_REF][START_REF] Levinson | Space in language and cognition: Explorations in cognitive diversity[END_REF]. However, research remains controversial on whether the grammatical gender of nouns denoting genderless objects prompts language users to associate different gender properties with the objects. The study described in Chapter 2 is an attempt to answer this question. To ensure that any positive/null results obtained are not due to unreliable research methods, I adopt an innovative approach by crowdsourcing the materials for Experiment 1, and I followed the open science initiative by submitting the study as a registered report 1 for peer review before we actually run the experiments. As this report is currently under review, I present in Chapter 2 in detail the design of two psycholinguistic experiments (without results), in addition to two pilot experiments (with results).

The second study (Chapter 3) examines the relationship between grammatical gender and mental representations of human referents. It focuses on the controversial use of masculine generics in French and its consequences for the underrepresentation of women in the mind of language users. Through two experiments, I compare the masculine form (e.g. les musiciens 'the musiciansmasc') to two gender-fair forms (double-gender: les musiciens et musiciennes 'the musiciansmasc and musiciansfem'; and middot: musicien•ne•s) across professions that have balanced and biased gender distributions. I ask three specific questions: 1) whether the two gender-fair forms differ from each other with regard to their effects on mental representations of gender distributions; 2) whether the effect of language form is moderated by the gender stereotype of a professional group; 3) and finally whether or not the representations induced by these language forms are consistent perceptions of real-world gender ratios.

The last study (Chapter 4) is about people's moral attitudes on gender equality between men and women and how it relates to their trust in scientific evidence of gender discrimination in academia. Moral attitudes toward a controversial issue have been shown to affect individuals' processing of new information, such that they tend to selectively assimilate or reject evidence 1 Registered reports are defined by the Royal Society as follows: "Registered reports are a format of empirical article where a study proposal is reviewed before the research is undertaken. Pre-registered proposals that meet high scientific standards are then provisionally accepted before the outcomes are known, independently of the results." (see https://royalsociety.org/blog/2016/11/registered-reports-whatare-they-and-why-are-they-important/). depending on whether it is consistent with their pre-existing attitudes or not [START_REF] Lord | Biased Assimilation and Attitude Polarization: The Effects of Prior Theories on Subsequently Considered Evidence[END_REF].

In Chapter 4, I present six experiments exploring the effects of individuals' moral commitment to gender equality on their evaluations of research summaries on sex-based hiring bias in STEM fields.

In this introductory chapter, I first provide an overview of research on language and thought with respect to object conceptualization, as the empirical evidence pertaining to this topic is less conclusive. Then I introduce the investigations on the role of language in the mental representations of persons, and finally I cover the study of the relationship between moral attitudes and trust in science.

Gender in Language and Its Influences on Mental Representations of Gender

More than a core characteristic of human beings, gender is also a productive feature of human languages. Depending on how gender is encoded in the language structure, the world's languages can be roughly divided into a few categories: grammatical gender languages (e.g. French, German), natural gender languages (e.g. English, Swedish), and genderless languages (e.g. Chinese, Finnish) [START_REF] Gygax | A Language Index of Grammatical Gender Dimensions to Study the Impact of Grammatical Gender on the Way We Perceive Women and Men[END_REF][START_REF] Stahlberg | Representation of the sexes in language[END_REF]. In grammatical gender languages, every noun, no matter if it refers to persons, objects or abstract concepts, is assigned to a gender class. The number of gender class varies across languages. For example, among the 256 languages documented by the World Atlas of Language Structures online (https://wals.info/) based on the work of [START_REF] Corbett | Gender[END_REF], 144 do not have grammatical gender, 50 have a two-gender system (e.g. French: masculine and feminine), 26 a three-gender system (e.g. German: masculine, feminine and neuter), 12 a four-gender system (e.g. Dyirbal: gender I , II, III, and IV) and 24 languages have five and more genders (e.g. Swahili: gender I -VII). The grammatical gender of nouns determines the form of other lexical categories appearing in the same sentence including verbs, adjectives, articles, and pronouns. For instance, in French, the word student has two forms étudiant and étudiante respectively for a male and a female student. In many cases, a French speaker cannot avoid indicating the sex of human referents in their phrases (except when they mean to do so) as the gender information of the referent is marked on the words they use. If the author writes Elle est une bonne étudiante 'She is a good student', the reader would not doubt that it is a female student the author is describing. Similarly, nouns denoting inanimate entities have gender markings and determine the form of other words appearing with them, as in une petite table 'afem smallfem table' and un petit bureau 'amasc smallmasc desk'. Here, a and small were shown in their feminine and masculine forms, respectively, modifying the feminine noun table and the masculine noun desk. The gender assignment of person nouns in grammatical gender languages mostly corresponds to the sex of the referent, while that of object nouns seems to be arbitrary, if not based on shape, size or other semantic features [START_REF] Corbett | Gender[END_REF].

Natural gender languages do not group nouns into gender classes, except that personal pronouns (e.g. he and she in English) and some person nouns (e.g. waiter/waitress, actor/actress) distinguish between the male and female forms. In genderless languages, finally, the sex information of referents is conveyed through lexical means, hence the absence of grammatical gender marking for nouns and pronouns [START_REF] Gygax | A Language Index of Grammatical Gender Dimensions to Study the Impact of Grammatical Gender on the Way We Perceive Women and Men[END_REF][START_REF] Stahlberg | Representation of the sexes in language[END_REF].

Following the Neo-Whorfian hypothesis that the structure of a language influences the way representations of the world are constructed in the minds of the speakers, one would argue that the grouping of nouns into masculine or feminine gender class should lead language users to associate male or female gender properties with the referents of the nouns. Research on this topic can be divided into two lines. One line investigates person nouns whose grammatical gender has a sex-based semantic underpinning as it overlaps the natural gender of the referents. The other line of research focuses on inanimate nouns (e.g. objects, concepts) whose grammatical gender does not overlap natural gender and has no semantic underpinnings related to sex. Overall, research on person nouns has provided converging evidence of grammatical gender influencing the mental representations of person referents, while results from the second line of research seem to be contradictory.

Does Grammatical Gender Affect Our Conceptualization of Objects?

Previous research on the effects of linguistic relativity has provided some evidence supporting the weak version of the Whorfian hypothesis postulating that language influences thought (the Neo-Whorfianism), but not the strong version that language determines thought (see [START_REF] Wolff | Linguistic relativity[END_REF][START_REF] Zlatev | Language may indeed influence thought[END_REF]. The hypothesized language effect has been found from many perspectives such as color terms and color perception [START_REF] Davies | A cross-cultural study of colour grouping: Evidence for weak linguistic relativity[END_REF][START_REF] Gilbert | Whorf hypothesis is supported in the right visual field but not the left[END_REF][START_REF] Thierry | Unconscious effects of language-specific terminology on preattentive color perception[END_REF][START_REF] Winawer | Russian blues reveal effects of language on color discrimination[END_REF], linguistic labels and conceptual category learning [START_REF] Boutonnet | Words Jump-Start Vision: A Label Advantage in Object Recognition[END_REF][START_REF] Lupyan | Language is not just for talking: Redundant labels facilitate learning of novel categories[END_REF], and the impact of space and time framing on speakers' spatial orientation and conceptualization of time [START_REF] Boroditsky | Does Language Shape Thought?: Mandarin and English Speakers' Conceptions of Time[END_REF][START_REF] Haun | Cognitive cladistics and cultural override in Hominid spatial cognition[END_REF][START_REF] Levinson | Space in language and cognition: Explorations in cognitive diversity[END_REF][START_REF] Levinson | Returning the tables: Language affects spatial reasoning[END_REF][START_REF] Li | Spatial reasoning in tenejapan mayans[END_REF][START_REF] Loewenstein | Relational language and the development of relational mapping[END_REF][START_REF] Majid | Can language restructure cognition? The case for space[END_REF][START_REF] Munnich | Spatial language and spatial representation: A crosslinguistic comparison[END_REF]. However, regarding grammatical gender and its influences on the perceived properties of objects, the existing empirical evidence remains rather controversial as suggested by the inconsistent findings in the literature (see [START_REF] Bassetti | Bilingualism and thought: Grammatical gender and concepts of objects in Italian-German bilingual children[END_REF][START_REF] Beller | Culture or language: What drives effects of grammatical gender?[END_REF][START_REF] Bender | Grammatical gender in German: A case for linguistic relativity[END_REF]Bender et al., , 2016a;;[START_REF] Boroditsky | Language in Mind: Advances in the Study of Language and Thought[END_REF][START_REF] Boutonnet | Unconscious effects of grammatical gender during object categorisation[END_REF][START_REF] Cubelli | The Effect of Grammatical Gender on Object Categorization[END_REF][START_REF] Haertlé | Does grammatical gender influence perception? A study of Polish and French speakers[END_REF][START_REF] Imai | All giraffes have female-specific properties: Influence of grammatical gender on deductive reasoning about sex-specific properties in german speakers[END_REF][START_REF] Kousta | Investigating linguistic relativity through bilingualism: The case of grammatical gender[END_REF][START_REF] Mickan | Key is a llave is a Schlüssel: A failure to replicate an experiment from Boroditsky et al[END_REF][START_REF] Saalbach | Grammatical Gender and Inferences About Biological Properties in German-Speaking Children[END_REF][START_REF] Saalbach | Grammatical Gender and Inferences About Biological Properties in German-Speaking Children[END_REF][START_REF] Sato | Grammatical gender affects gender perception: Evidence for the structural-feedback hypothesis[END_REF][START_REF] Sera | When language affects cognition and when it does not: An analysis of grammatical gender and classification[END_REF].

As mentioned before, grammatical gender refers to the classification of nouns into different classes followed by a grammatical rule of agreement according to which the forms of other lexical categories change, including that of adjectives, articles and pronouns. Even though the grammatical gender of nouns denoting objects does not have a sex-based semantic underpinning, one can ask whether the classification of masculine and feminine nouns, as in French, would prompt speakers to make different gender associations with the objects. To my knowledge, this question was first experimentally investigated by the cognitive scientists [START_REF] Guiora | A Cross-Cultural Study of Symbolic Meaning-Developmental Aspects[END_REF]. Using a semantic differential test, [START_REF] Guiora | A Cross-Cultural Study of Symbolic Meaning-Developmental Aspects[END_REF] showed Hebrew speaking Israeli kindergarteners and adults a list of object nouns and asked them to judge to what extent the words could be related to masculine or feminine characteristics. In addition to grammatical gender, they varied the cultural gender connotations of the stimulus words: malerelated (e.g. aircraft, tank), female-related (e.g. doll, skirt), and gender-neutral (e.g. clock, book).

Counter the predictions of the hypothesis, they found that both child and adult participants categorized the words according to their gender connotations rather than grammatical gender.

This study actually replicated results of their previous cross-cultural study comparing American and Israeli adults (cited in [START_REF] Guiora | A Cross-Cultural Study of Symbolic Meaning-Developmental Aspects[END_REF] where they found English and Hebrew speakers showed a similar pattern of responsesthe associations were made based on gender connotations. The authors thus concluded that grammatical gender in Hebrew did not influence native speakers' perceptions of objects. Being the first researchers to look at the relationship between grammatical gender and object perception, they provided the initial counter evidence of the hypothesized gender effect.

Later, [START_REF] Clarke | Gender perception in Arabic and English[END_REF] replicated the study with Arabic (a grammatical gender language) and English (for comparison). This time, contrary to the findings of [START_REF] Guiora | A Cross-Cultural Study of Symbolic Meaning-Developmental Aspects[END_REF], a gender effect was detected. The Arabic participants assigned gender qualities to words according to their grammatical gender, while the English participants relied on the words' gender connotations. After that, continuous attempts were made to replicate the studies with other languages like German, Spanish, French, Italian and Polish, on age groups from 5-year-olds to adults, employing various paradigms ranging from voice assignment, word and picture grouping, inference tasks, to word error induction tasks [START_REF] Bassetti | Bilingualism and thought: Grammatical gender and concepts of objects in Italian-German bilingual children[END_REF][START_REF] Bender | Grammatical gender in German: A case for linguistic relativity[END_REF][START_REF] Bender | Lady Liberty and Godfather Death as candidates for linguistic relativity? Scrutinizing the gender congruency effect on personified allegories with explicit and implicit measures[END_REF][START_REF] Boutonnet | Unconscious effects of grammatical gender during object categorisation[END_REF][START_REF] Cubelli | The Effect of Grammatical Gender on Object Categorization[END_REF][START_REF] Flaherty | How a language gender system creeps into perception[END_REF][START_REF] Imai | All giraffes have female-specific properties: Influence of grammatical gender on deductive reasoning about sex-specific properties in german speakers[END_REF][START_REF] Konishi | The semantics of grammatical gender: A cross-cultural study[END_REF][START_REF] Kousta | Investigating linguistic relativity through bilingualism: The case of grammatical gender[END_REF][START_REF] Kurinski | Does learning Spanish grammatical gender change English-speaking adults' categorization of inanimate objects?[END_REF][START_REF] Maciuszek | Grammatical Gender Influences Semantic Categorization and Implicit Cognition in Polish[END_REF][START_REF] Mills | The acquisition of gender: A study of English and German[END_REF][START_REF] Ramos | What constrains grammatical gender effects on semantic judgements? Evidence from Portuguese[END_REF][START_REF] Sato | Grammatical gender affects gender perception: Evidence for the structural-feedback hypothesis[END_REF][START_REF] Sera | Grammatical and conceptual forces in the attribution of gender by English and Spanish speakers[END_REF][START_REF] Sera | When language affects cognition and when it does not: An analysis of grammatical gender and classification[END_REF][START_REF] Vigliocco | Grammatical gender effects on cognition: Implications for language learning and language use[END_REF].

Although most of the studies reported positive results, the picture is more of a complex one. For example, the gender effect was more robust in languages with a sex-based two-gender system (e.g. French, Italian) than in those having three grammatical gender classes (e.g. German) (Sera et al., 2002b;[START_REF] Vigliocco | Grammatical gender effects on cognition: Implications for language learning and language use[END_REF]; but see [START_REF] Bender | Gender congruency from a neutral point of view: The roles of gender classes and conceptual connotations[END_REF]; the influence of grammatical gender was not detected if participants' lexical access was blocked by articulatory suppression when performing the target task [START_REF] Cubelli | The Effect of Grammatical Gender on Object Categorization[END_REF]; the effect was found with monolinguals but not with bilinguals who spoke two grammatical gender languages [START_REF] Bassetti | Bilingualism and thought: Grammatical gender and concepts of objects in Italian-German bilingual children[END_REF], or that the language effect in bilinguals was dependent on the test language [START_REF] Kousta | Investigating linguistic relativity through bilingualism: The case of grammatical gender[END_REF]; the language effect was limited among adult language learners [START_REF] Kurinski | Does learning Spanish grammatical gender change English-speaking adults' categorization of inanimate objects?[END_REF]; the effect was stronger with explicit measures (e.g. biological sex assignment) and linguistic stimuli than with implicit measures (e.g. Extrinsic Affective Simon Task) and visual stimuli [START_REF] Bender | Lady Liberty and Godfather Death as candidates for linguistic relativity? Scrutinizing the gender congruency effect on personified allegories with explicit and implicit measures[END_REF][START_REF] Ramos | What constrains grammatical gender effects on semantic judgements? Evidence from Portuguese[END_REF], and so on and so forth. Another complexity is that some positive effects could be attributed to task demands, or participants' employment of response strategies in completing the task that may have biased the results in favor of the hypothesis. For example, when asked to assign a male or female voice to objects as in [START_REF] Sera | When language affects cognition and when it does not: An analysis of grammatical gender and classification[END_REF], participants could simply rely on the cue of grammatical gender to complete the somewhat strange task.

That said, some research did adopt measures that were less subject to task demands (e.g. word or image priming), but again mixed results were reported. Using a semantic categorization task, [START_REF] Boutonnet | Unconscious effects of grammatical gender during object categorisation[END_REF] presented Spanish-English bilinguals with three pictures of objects one by one and asked them to decide whether the third picture in a series belonged to the same semantic category as the first two while measuring the event-related brain potentials (ERP). The researchers manipulated the semantic relatedness and grammatical gender of the objects. The participants' explicit judgments revealed no gender effect, but their ERPs did, suggesting that participants retrieved grammatical gender information even when it was irrelevant to the task [START_REF] Boutonnet | Unconscious effects of grammatical gender during object categorisation[END_REF]. Later, [START_REF] Sato | Grammatical gender affects gender perception: Evidence for the structural-feedback hypothesis[END_REF] tested native English and French-English bilinguals with a facial image categorization task and found that English speakers were influenced by the gender connotations of object primes when asked to categorize male and female facial images, while French-English bilinguals relied on the grammatical gender of objects in performing the task. Other studies that employed different implicit methods also reported positive effects of grammatical gender [START_REF] Bender | Grammatical gender in German: A case for linguistic relativity[END_REF][START_REF] Bender | Gender congruency from a neutral point of view: The roles of gender classes and conceptual connotations[END_REF]. It is worth noting that [START_REF] Bender | Gender congruency from a neutral point of view: The roles of gender classes and conceptual connotations[END_REF] reported equally strong effects for neuter and gender-marked nouns in German. This result, however, should be interpreted with a caveat: it may have been confounded with gender connotations since neuter nouns should not exhibit such an effect except if they were stereotypically associated with males or females.

Among the previous studies, the one reported by [START_REF] Boroditsky | Language in Mind: Advances in the Study of Language and Thought[END_REF] is particularly worth mentioning here. Employing a word association method, [START_REF] Boroditsky | Language in Mind: Advances in the Study of Language and Thought[END_REF] asked German and Spanish participants to produce adjectives for a list of 24 object nouns that had opposite grammatical gender in the two languages (i.e. masculine in German and feminine in Spanish, feminine in German and masculine in Spanish). To minimize the influence of participants' native language, the task was administered in English. Then to test if the adjectives generated for masculine and feminine nouns differed in their gender associations, the researchers asked a group of English speakers to rate the adjectives on the extent to which they were associated with masculine or feminine properties. According to the summary of results provided by the authors [START_REF] Boroditsky | Language in Mind: Advances in the Study of Language and Thought[END_REF], German and Spanish participants generated adjectives that were rated as "masculine" or "feminine" for grammatically masculine or feminine nouns in their native language. For example, the word "bridge", which is grammatically feminine in German ("Brücke"), elicited female-typed adjectives from German speakers (e.g. beautiful, elegant, fragile, peaceful, pretty, and slender), while it is grammatically masculine in Spanish ("puente") and thus induced male-typed adjectives from Spanish speakers (e.g. big, dangerous, long, strong, sturdy, and towering). The study has garnered much attention from experts and laypeople alike as evinced by the more than 800 citations on Google scholar and the over seven million views of Boroditsky's YouTube video in which these findings were described (https://www.youtube.com/watch?v=RKK7wGAYP6k). Despite the wide attention it has drawn, the important aspects of the study remain unknown, including the experimental materials, procedure and results, except being briefly described in the book chapter [START_REF] Boroditsky | Language in Mind: Advances in the Study of Language and Thought[END_REF].

Recently, [START_REF] Mickan | Key is a llave is a Schlüssel: A failure to replicate an experiment from Boroditsky et al[END_REF] made an attempt to replicate [START_REF] Boroditsky | Language in Mind: Advances in the Study of Language and Thought[END_REF]'s study, but this time the German and Spanish speakers were tested in their native language instead of a third language. Contrary to the findings that were originally reported, results of the replication study showed no grammatical gender effect [START_REF] Mickan | Key is a llave is a Schlüssel: A failure to replicate an experiment from Boroditsky et al[END_REF]. The study of [START_REF] Mickan | Key is a llave is a Schlüssel: A failure to replicate an experiment from Boroditsky et al[END_REF], however, had its own limitations with regard to the selection of items and its sample size. The authors tested a small number of items (N = 10) with two of them denoting animals ("whale" and "mouse") and eight, objects (e.g. "pumpkin", "clock"). The mixture of animate and inanimate nouns could bias the results in opposite directions, as previous studies suggested differential effects of grammatical gender for the two types of items (see [START_REF] Bender | Grammatical gender in German: A case for linguistic relativity[END_REF]Bender et al., , 2016a;;[START_REF] Maciuszek | Grammatical Gender Influences Semantic Categorization and Implicit Cognition in Polish[END_REF]. In addition, the nouns were not controlled for gender connotations and natural/artificial classification, two factors that could confound the grammatical gender effect (see Bender et al., 2016a[START_REF] Bender | Gender congruency from a neutral point of view: The roles of gender classes and conceptual connotations[END_REF][START_REF] Mullen | Children's classifications of nature and artifact pictures into female and male categories[END_REF][START_REF] Sera | Grammatical and conceptual forces in the attribution of gender by English and Spanish speakers[END_REF]. With respect to the sample size, within each language group, there were only 15 participants for the adjective generation task and 10 for the adjective rating task. One would argue that results from such a small sample size are hardly generalizable to a greater population.

Overall, more reliable research methods are needed to better answer the question of whether grammatical gender affects people's conceptualization of objects. Thus, building on the work of [START_REF] Boroditsky | Language in Mind: Advances in the Study of Language and Thought[END_REF] and [START_REF] Mickan | Key is a llave is a Schlüssel: A failure to replicate an experiment from Boroditsky et al[END_REF], Chapter 2 of the dissertation presents two psycholinguistic experiments, using a similar word association method, to investigate French and German speakers mental representations of objects. Here, we adopt a "stack the deck" approach in which we diverge from previous studies by stacking the deck in favor of the original hypothesis, in such a way that any null result(s) obtained (suggested by extensive piloting) would provide strong weight against it. Specifically, unlike [START_REF] Boroditsky | Language in Mind: Advances in the Study of Language and Thought[END_REF] who tested participants in English as a way to reduce the influence of their native language, we will test participants directly in their native language by asking one group of participants to produce adjectives to gender marked masculine and feminine nouns, and another group of native participants to rate these adjectives as representing typically male or female qualities. All things being equal, we would expect that testing in a speaker's gendered native language (as opposed to testing them in English) while using gender marked test items would only serve to enhance any existing Neo-Whorfian effects. In addition, to address concerns over the experimenter bias (see [START_REF] Strickland | Experimenter Philosophy: The Problem of Experimenter Bias in Experimental Philosophy[END_REF] for a discussion), we crowdsourced the materials for Experiment 1 by asking participants to create semantically related noun pairs in French, and we standardized our item selection process to better control for the potential confounding factors such as the number of syllables and gender connotations.

As the underlying hypothesis/results which we are addressing is one which has captured the imagination of millions of people, including both scientists and the public, but there are very real doubts about the veracity or robustness of the findings, we decided to adopt an open sciencebased approach in assessing whether it is actually true that grammatical gender deeply influences how we think about inanimate objects. Specifically, considering that a potential publication bias a greater likelihood of positive results that support a hypothesis being published on academic journals -may exist in science practices, any null effects that we observe may have a lesser chance of being accepted for publication. To combat such a publication bias, and at the same time, to ensure the reliability of our research design, we decided to follow the open science initiative by submitting the described work (Chapter 2) as a registered report. In doing so, we can have our experimental design peer reviewed before we commence data collection. The registered report is currently under review. In Chapter 2, I present the manuscript of the registered report as submitted, including detailed descriptions of two experiments (for which data collection will start after we receive an in-principle acceptance of the report by a journal) followed by the descriptions and results of two pilot studies.

Linguistic Gender Inequality and Language Reform

In languages with a sex-based grammatical gender system, i.e. nouns referring to male persons have masculine gender and those for female persons have feminine gender, the roles of masculine and feminine genders are often asymmetrical. The masculine gender is typically assigned the role of a generic and can be used to refer to a group of women and men, or to persons whose sex is unknown or irrelevant [START_REF] Corbett | Gender[END_REF][START_REF] Gygax | A Language Index of Grammatical Gender Dimensions to Study the Impact of Grammatical Gender on the Way We Perceive Women and Men[END_REF]. On the contrary, the feminine gender has a specific female meaning and can only be used to denote female persons. The two French sentences (1a) and (1b) illustrate such a difference.

(1) a. Les sportifs français ont gagné 10 médailles d'or.

'The Frenchmasc athletesmasc have gained 10 gold medals' b. Les sportives françaises ont gagné 10 médailles d'or.

'The Frenchfem athletesfem have gained 10 gold medals' Written in the masculine form, sentence (1a) can be interpreted in three ways: only the male French athletes have gained 10 gold medals, the male and female French athletes together gained 10 gold medals, and the French athletes whose sex is unknown or irrelevant here earned 10 medals. However, the feminine form in (1b) exclusively refers to female athletes.

Another comparable example is English: the masculine third person pronoun he is designated as the generic pronoun while the feminine counterpart she has a female specific meaning. Similar use of masculine generic can be found in other grammatical gender languages such as German (e.g. Lehrer 'teachersmasc'), and natural gender languages like Swedish (i.e. han 'he').

Since 1970s, the world has seen heated debates on gender equality regarding the unequal treatment of masculine and feminine gender in languages, in particular, the use of masculine gender as generics. Language is both a reflection and a source of stereotyped gender beliefs. The unequal roles of masculine and feminine gender in a language has been argued to largely mirror the asymmetrical power and status relations between men and women in a speech community [START_REF] Bodine | Androcentrism in prescriptive grammar: Singular 'they', sex-indefinite 'he', and 'he or she'1[END_REF][START_REF] Menegatti | Gender bias and sexism in language[END_REF]. Consistent with the converging evidence of the linguistic mapping of gender stereotype across languages (T. E. S. [START_REF] Charlesworth | Gender Stereotypes in Natural Language: Word Embeddings Show Robust Consistency Across Child and Adult Language Corpora of More Than 65 Million Words[END_REF][START_REF] Garg | Word embeddings quantify 100 years of gender and ethnic stereotypes[END_REF][START_REF] Lewis | Gender stereotypes are reflected in the distributional structure of 25 languages[END_REF][START_REF] Tavits | Language influences mass opinion toward gender and LGBT equality[END_REF], a previous cross-national research has shown that the more explicit gender information is encoded linguistically, as in grammatical gender languages, the more likely that gender stereotypes are made salient and thus the higher are the chances of reproducing sexist beliefs in speakers [START_REF] Prewitt-Freilino | The gendering of language: A comparison of gender equality in countries with gendered, natural gender, and genderless languages[END_REF].

The use of masculine generics was considered to be problematic as it may represent a linguistic means of legitimizing the dominant status of the masculine gender, and in consequence turning sexist beliefs into a routine practice with most language users being unaware of it [START_REF] Ng | Language-based discrimination: Blatant and subtle forms[END_REF].

Over the last five decades, people who were aware of linguistic inequalities in their languages have expressed concern over the role of masculine generics in contributing to the underrepresentation of women in many fields. As a remedy to the male-oriented language structure, alternative forms that are considered more gender-fair have been proposed to replace masculine generics. For instance, the French community has introduced several gender-fair forms: double-gender (e.g. étudiants et étudiantes 'studentsmasc and studentsfem'), and contracted forms using a slash (e.g. étudiant/es), a dash (e.g. étudiant-e-s), brackets (e.g. étudiant(e)s), and a middot (e.g. étudiant•e•s) [START_REF] Abbou | Double gender marking in French: A linguistic practice of antisexism[END_REF]. In a similar vein, German has seen the existence of contracted forms with an asterisk (e.g. Reporter*in 'reportermasc*fem') [START_REF] Kruppa | Does the Asterisk in Gender-fair Word Forms in German Impede Readability? Evidence from a Lexical Decision Task[END_REF], word pair forms (e.g. Politikerinnen und Politiker 'politiciansfem and politiciansmasc'), capital I (e.g. PolitikerInnen), and nominalized form (e.g. die Studierenden 'the students' derived from the verb studieren 'to study') [START_REF] Sato | Altering male-dominant representations: A study on nominalized adjectives and participles in first and second language German[END_REF]. Likewise, in English, alternatives such as pair pronouns he or she (also he/she), singular they, and contracted forms s/he and (s)he have been proposed as replacements of the male generic he [START_REF] Bodine | Androcentrism in prescriptive grammar: Singular 'they', sex-indefinite 'he', and 'he or she'1[END_REF][START_REF] Gastil | Generic pronouns and sexist language: The oxymoronic character of masculine generics[END_REF][START_REF] Hyde | Children's understanding of sexist language[END_REF] see [START_REF] Stahlberg | Representation of the sexes in language[END_REF], for a review), and in Swedish, a gender-neutral third person pronoun hen was invented as a substitute for han [START_REF] Gustafsson Sendén | Introducing a gender-neutral pronoun in a natural gender language: The influence of time on attitudes and behavior[END_REF].

The course of gender-fair language never runs smoothly. Initiatives for language reform were received with mixed responses by the public [START_REF] Blaubergs | An analysis of classic arguments against changing sexist language[END_REF][START_REF] Parks | Contemporary arguments against nonsexist language: Blaubergs (1980) revisited[END_REF] see [START_REF] Stahlberg | Representation of the sexes in language[END_REF] for a review). On the one hand, proponents of gender-fair language believe that the use of masculine generics in reference to a mixed-sex group leads to biased mental representations favoring males, and in result, leaves women invisible or ignored; masculine formulations put women at a disadvantage as they are less likely to be considered for roles presented in masculine forms, and women themselves also find it hard to identify with such roles and positions [START_REF] Stahlberg | Representation of the sexes in language[END_REF]. On the other hand, opponents of language reform responded with a list of reasons for not using gender-fair language forms: there is no causal relation between language structure and gender inequality, changing sexist language is rather frivolous as a matter compared to other forms of injustice in society, people cannot be coerced to use a nonsexist language, language is not sexist by itself but instead it is the hearer/reader who interprets it in a sexist way, masculine generics are not male-biased, changing the language will estrange the current and future generations from historical heritage, and in extreme cases, people even admit and support sexism and linguistic patriarchy [START_REF] Blaubergs | An analysis of classic arguments against changing sexist language[END_REF][START_REF] Parks | Contemporary arguments against nonsexist language: Blaubergs (1980) revisited[END_REF][START_REF] Stahlberg | Representation of the sexes in language[END_REF]. In French, additional skepticism was pointed to the possible reading and learning difficulties2 created by the innovative, contracted gender-fair language forms (see [START_REF] Gygax | Féminisation et lourdeur de texte[END_REF].

When the proponents and critics of gender-fair language were tossing arguments around at each other, a growing body of literature from the last five decades has documented converging evidence of male-biased interpretations of masculine generics compared to the gender inclusive alternatives (see Stahlberg et al., 2007 for a review). Beginning in the 1970s, researchers investigated the difference between generic he and gender-fair alternatives in English. Results

showed that relative to they and he or she, the male generic he was disproportionately associated with men [START_REF] Gastil | Generic pronouns and sexist language: The oxymoronic character of masculine generics[END_REF][START_REF] Hamilton | Using masculine generics: Does generic he increase male bias in the user's imagery?[END_REF][START_REF] Hyde | Children's understanding of sexist language[END_REF][START_REF] Mackay | Psychology, prescriptive grammar, and the pronoun problem[END_REF][START_REF] Martyna | What does 'he'mean? Use of the generic masculine[END_REF][START_REF] Martyna | Beyond the" he/man" approach: The case for nonsexist language[END_REF][START_REF] Moulton | Sex bias in language use:"Neutral" pronouns that aren't[END_REF]. In a similar vein, empirical studies revealed male-oriented representations when masculine generics was used in German and French, while gender-fair alternative forms improved women's visibility in mental representations [START_REF] Braun | Cognitive effects of masculine generics in German: An overview of empirical findings[END_REF][START_REF] Gabriel | Au pairs are rarely male: Norms on the gender perception of role names across English, French, and German[END_REF]Gygax et al., 2008[START_REF] Gygax | The masculine form and its competing interpretations in French: When linking grammatically masculine role names to female referents is difficult[END_REF]Gygax & Gabriel, 2008;[START_REF] Hansen | The Social Perception of Heroes and Murderers: Effects of Gender-Inclusive Language in Media Reports[END_REF][START_REF] Sato | Altering male-dominant representations: A study on nominalized adjectives and participles in first and second language German[END_REF]Stahlberg et al., 2001;Stahlberg & Sczesny, 2001). These studies thus justified the concerns over sexist language forms across cultures by showing that masculine generics indeed evoke representations favoring males, leaving the roles of women largely forgotten.

Although proposals for language change encountered strong resistance at the beginning, over time, gender-inclusive language forms seemed to be accepted and applied more commonly in public communication. For instance, in Germany, German-speaking Switzerland, and Austria, using gender-fair generic form in official language has become a well-established norm [START_REF] Bußmann | Engendering female visibility in German[END_REF][START_REF] Formanowicz | Capturing socially motivated linguistic change: How the use of gender-fair language affects support for social initiatives in Austria and Poland[END_REF][START_REF] Mucchi-Faina | Visible or influential? Language reforms and gender (in) equality[END_REF][START_REF] Sarrasin | Sexism and attitudes toward gender-neutral language[END_REF]; the use of generic he in English declined over time and the appearance of gender-inclusive forms grew significantly in public discourse [START_REF] Rubin | Adopting gender-inclusive language reforms: Diachronic and synchronic variation[END_REF], and now one would say it is common to encounter gender-inclusive formulations in both oral and written English [START_REF] Sarrasin | Sexism and attitudes toward gender-neutral language[END_REF]; in Sweden, people's attitudes towards the gender-neutral pronoun hen became positive over time, and accordingly they were more willing to use it in everyday communication [START_REF] Gustafsson Sendén | Introducing a gender-neutral pronoun in a natural gender language: The influence of time on attitudes and behavior[END_REF]; additionally, even though gender-fair language, especially the middot form, remains a controversial topic in France, one can find gender-fair language forms more and more often in official language (e.g. middot form is adopted by the City Hall of Paris https://www.paris.fr/municipalite and Lyon https://www.lyon.fr/solidarite).

Controversial Impact of Gender-Fair Language

Previous studies have provided consistent evidence of gender-inclusive language reducing male bias in people's mental representations (thus increasing women's presence in the minds of language users). Now, one question to ask is what social impacts does gender-fair language bring about. This may involve the perceived competence and social status of women, the inclusion of females in the workplace, and how a gender-fair language user is perceived, to name a few. Answers to these questions are by far mixed. Some research results revealed positive effects of gender-fair language as demonstrated by the findings that both women and men were more willing to apply for an opposite-sex job when the job advertisement was written in gender-inclusive language (e.g. man or woman) than when the language was gender-specific [START_REF] Bem | Does Sex-biased Job Advertising "Aid and Abet" Sex Discrimination? 1[END_REF]. Similarly, the French double-gender form (e.g. infirmier/infirmière, 'nursemasc/nursefem') and contracted form (e.g. infirmier (ère), 'nursemasc(fem)') augmented young adolescents' perceptions of professional self-efficacy, compared to the masculine form [START_REF] Chatard | Impact de la féminisation lexicale des professions sur l'auto-efficacité des élèves: Une remise en cause de l'universalisme masculin?[END_REF]. Furthermore, speakers of gender-inclusive language were perceived as less sexist and were evaluated more positively than those who used gender-exclusive language [START_REF] Greene | Effects of gender inclusive/exclusive language in religious discourse[END_REF], and applicants for the job of a spokesperson for UNICEF were rated as less sexist, warmer, more competent, and were more likely to be hired when they used gender-fair language than when they chose masculine generics [START_REF] Vervecken | Ambassadors of gender equality? How use of pair forms versus masculines as generics impacts perception of the speaker[END_REF]. Nevertheless, Horvath et al., (2016) showed that gender-fair forms in German and Italian increased women's visibility across male-and female-stereotyped professions, but the perceived social status and competence of people working in those professions were not affected by linguistic forms. A similar null effect of language form on the evaluations of professions was reported for the French language [START_REF] Gygax | Féminisation et lourdeur de texte[END_REF].

Inclusive language can help create an inclusive work environment. Using a mock interview method, [START_REF] Stout | When he doesn't mean you: Gender-exclusive language as ostracism[END_REF] found that participants' perceived sexism in the workplace, their feel of belonging, motivation to pursue a job, and identification with the job were influenced by the language form (i.e. masculine generic he vs. gender-fair he or she vs. gender-neutral one) used in the job description as well as by the interviewer. Their results demonstrated that job seekers, in particular women, perceived lower degree of sexism exhibited by the interviewer, felt less ostracized, more motivated to pursue the job and more identified with the job when gender-fair and gender-neutral language forms were used than when genderexclusive he was adopted [START_REF] Stout | When he doesn't mean you: Gender-exclusive language as ostracism[END_REF]. Consistent with this finding, Horvath & Sczesny (2016) reported that word pair forms improved the perceived fitting of women applicants for a high-status position compared to masculine form.

On the negative side, however, some evidence showed that gender-fair language could fail its good intentions by activating gender stereotypes that are disadvantageous to women. A good example is that in Italian, a female professor was seen as less persuasive and reliable when presented with a feminine professional title (e.g. professoressa) than with a masculine title (e.g. professore) [START_REF] Mucchi-Faina | Visible or influential? Language reforms and gender (in) equality[END_REF]. The negative evaluations invoked by the feminine title may be attributed to the derogatory associations with the suffix -essa in Italian [START_REF] Merkel | Shielding women against status loss: The masculine form and its alternatives in the Italian language[END_REF] and the controversial state of gender-fair language reform in Italy the time when the study was conducted. By comparing the traditional masculine form with two feminine forms (i.e. suffixessa, and neologisms -a and -e) in Italian, [START_REF] Merkel | Shielding women against status loss: The masculine form and its alternatives in the Italian language[END_REF] did prove that feminized occupational titles with -essa led to a status loss for women relative to the masculine form and neologisms -a and -e. Similarly in Polish, feminine forms (e.g. suffix -ka) often derived from masculine terms and had derogatory connotations (e.g. referring to the "wife of" or "possessions of") [START_REF] Koniuszaniec | Language and gender in Polish[END_REF]. Accordingly, in a CV evaluation study, women applicants of a position were rated less favorably when introduced with a feminized title (e.g. nanotechnolożka 'nanotechnologistfem') than with a masculine one (e.g. nanotechnolog 'nanotechnologistmasc') (M. [START_REF] Formanowicz | Side effects of gender-fair language: How feminine job titles influence the evaluation of female applicants[END_REF]; in a similar vein, female applicants for a fictional job were perceived as less competent by both women and men, but only less warm by men when a feminine title (e.g. aborolożka) was used [START_REF] Budziszewska | Backlash over gender-fair language: The impact of feminine job titles on men's and women's perception of women[END_REF]. Even though these deleterious effects of gender-fair language documented could be attributed to the negative associations specific to some forms but not the practice of gender-fair language in general, one would anticipate some backlash effects of language reform in the short run.

Gender-fair language does not influence everyone to the same degree just as everyone in a society is not unanimously pro or against language reform. The effects of gender-fair language could be moderated by factors such as the status of language reform in a community and language users' attitudes on the issue. One would expect more positive influences of genderinclusive language in a community where the usage of gender-fair language is well established than a society for which language reform is novel and controversial. For instance, [START_REF] Formanowicz | Capturing socially motivated linguistic change: How the use of gender-fair language affects support for social initiatives in Austria and Poland[END_REF] observed backlash effects of gender-fair language with Polish speakers who were not used to the presence of such forms, while positive effects were found with Austrian participants to whom using gender-fair language was already a well-established norm.

Specifically, the authors presented a fictitious initiative to participants and asked for their evaluations. With Polish participants, the authors found when the initiative was related to gender equality, the gender-fair language framing evoked more negative evaluations and less support, especially among male participants; when the initiative was unrelated to gender, language form did not show any effect on the evaluations. Conversely, the Austrian results showed that the gender-equality initiative was evaluated more favorably when presented in gender-fair form than in masculine form. In Swedish, another language that adopted a gender-fair form, [START_REF] Tavits | Language influences mass opinion toward gender and LGBT equality[END_REF] observed similar positive effectswomen politicians were more likely to be acknowledged when the gender-inclusive pronoun hen was used.

With regard to the moderating role of people's attitudes and ideology, [START_REF] Sarrasin | Sexism and attitudes toward gender-neutral language[END_REF] found that individuals holding sexist beliefs were more inclined to express negative attitudes toward gender-related language reform. Furthermore, [START_REF] Formanowicz | Side effects of gender-fair language: How feminine job titles influence the evaluation of female applicants[END_REF] revealed that conservatives were more likely to devalue a female applicant presented with a feminine title than liberals since the former tended to maintain traditional gender role beliefs, and were more resistant to social changes and feminist reforms. That said, the current adherence to gender-fair language in the U.K., Austria, Sweden and other countries seems to suggest that a converging attitude toward language reform and in result, positive impacts of gender-fair language on the societal level is not unattainable.

Gender-Fair Forms: Which One to Choose?

Difficulties in finding a proper gender-fair alternative to masculine generics vary from one language to another. It may be relatively more complicated for grammatical gender languages than for natural gender and genderless languages, given that changes of nominal forms in the former have consequences for the grammatical agreement in adjectives, articles and other lexical categories. Constrained by the language structure, the advancement of language reform in grammatical gender languages often gets pushed back due to the unconventional looking of newly invented forms that speakers find hard to accept. For example, in France, debates on sexist language dated back to the late 1990s [START_REF] Mucchi-Faina | Visible or influential? Language reforms and gender (in) equality[END_REF], while gender-inclusive language, especially the middot form, remains a highly controversial subject in the year of 2021. Although various gender-fair forms (e.g. étudiants et étudiantes, étudiant/es, and étudiant•e•s) are frequently seen in the public space such as in subway stations, and online in official language, there is never a normative criterion as to which gender-fair form should be adopted. Oftentimes one finds multiple forms appearing in a single piece of writing3 . The chaotic state of gender-fair language use can be attributed to the arguable drawbacks with regard to each individual form4 that put speakers off the idea: the double-gender form (e.g. étudiants et étudiantes) is long and repetitive; the splitting form with a slash (e.g. étudiant/es) places feminine gender in a secondary position, the middot form (e.g. étudiant•e•s) creates reading and learning problems.

Much of the criticism concerns the unease that speakers might experience when using gender-fair language. However, despite being intuitive, these claims are not empirically validated. [START_REF] Gygax | Féminisation et lourdeur de texte[END_REF] provided suggestive evidence that gender-fair forms did not make reading more difficult than it normally is. By asking participants to read texts containing different language forms (i.e. masculine: avocats 'lawyersmasc'; double-gender: avocats et avocates 'lawyersmasc and lawyersfem'; and contracted form with a dash: avocat-e-s 'lawyermascfem-s'), the authors showed that the contracted form slowed down reading when it was shown the first time, compared to masculine and double-gender forms, but the difference in reading speed disappeared when the contracted form was encountered the second and third time in the texts.

Furthermore, readers of the contracted form did not report any experience of reading difficulties.

The message from this study is that French readers and hearers may need to take a short break from their task and process a bit more the contracted forms when they are encountered for the first time, but the powerful human brain will not be defeated by this tiny little puzzle.

To answer the question of which gender-fair form should be used in France, one needs to consider the costs and benefits of language reform on the societal level. Currently, empirical data that can allow for such an analysis are still much needed. For instance, we need to assess the influences of language forms on the mental representations of gender groups, the effects of gender-fair forms on language learning and processing, the social impacts of language reform and other aspects important to the decision making. To provide data bearing on this analysis, Chapter 3 presents two empirical studies on the consistency of mental representations induced by gender-fair forms, especially, the most controversial middot form. The experiments compared two candidate alternative generic forms (i.e. double-gender and middot) with the masculine form across professions of differing gender stereotypicality. Participants were asked to read a short text about the taking place of a professional gathering and provide their estimates of proportions of women and men present at the gathering. Consistent with existing evidence in English and German (e.g. [START_REF] Braun | Cognitive effects of masculine generics in German: An overview of empirical findings[END_REF][START_REF] Gastil | Generic pronouns and sexist language: The oxymoronic character of masculine generics[END_REF][START_REF] Hyde | Children's understanding of sexist language[END_REF][START_REF] Moulton | Sex bias in language use:"Neutral" pronouns that aren't[END_REF]Stahlberg et al., 2001), results of the two experiments showed that both gender-fair forms increased the presence of women in the minds of language users. We also compared the participants' estimates with data of a previous norming study [START_REF] Misersky | Norms on the gender perception of role nouns in Czech, English, French, German, Italian, Norwegian, and Slovak[END_REF] to examine the consistency of those estimates and establish whether some language form led to biased representations of gender ratios. The results suggested that depending on whether a profession is gender-balanced, male-or female-dominated, the two forms seemed to work differently, leading to various effects regarding the reduction of male bias and the consistency of representations.

From Gender Stereotyping to Gender Inequality

Stereotyping is "the attribution of general psychological characteristics to large human groups" [START_REF] Tajfel | Cognitive aspects of prejudice[END_REF]. Holding stereotypes makes people neglect individual differences and believe that all members of a group are similar [START_REF] Hogg | Social identifications: A social psychology of intergroup relations and group processes[END_REF], and once stereotypes are formed, they are spontaneously applied to members of a group [START_REF] Devine | Stereotypes and prejudice: Their automatic and controlled components[END_REF].

Characteristics such as gender and ethnicity are common sources of stereotypes. Take gender for example, men are often associated with agentic qualities (e.g. independent, competitive, arrogant and boastful) while women are thought of as having communal properties (e.g. warm, emotional, gullible and whiny) [START_REF] Bem | The Measurement of Psychological Androgyny[END_REF][START_REF] Deaux | Putting gender into context: An interactive model of gender-related behavior[END_REF][START_REF] Eagly | Gender stereotypes and attitudes toward women and men[END_REF][START_REF] Garg | Word embeddings quantify 100 years of gender and ethnic stereotypes[END_REF]. In accordance with these stereotypes, men and women are assigned to different roles in society. Generally speaking, women are significantly underrepresented in senior, leadership positions [START_REF] Bertrand | The gender gap in top corporate jobs[END_REF][START_REF] Soarea | 2013 Catalyst census Fortune 500 women executive officers and top earners[END_REF].

For example, a recent word embedding study revealed a century long (from 1910 to 1990) gender segregation in occupations, i.e., males dominated high-status professions like architect, soldier, engineer, and judge while females took on roles of caregiver or entertainer such as nurse, housekeeper, midwife, and dancer [START_REF] Garg | Word embeddings quantify 100 years of gender and ethnic stereotypes[END_REF]. Similar patterns of gender distributions have been shown in norming studies and census data [START_REF] Gabriel | Au pairs are rarely male: Norms on the gender perception of role names across English, French, and German[END_REF][START_REF] Garnham | True gender ratios and stereotype rating norms[END_REF][START_REF] Kennison | Comprehending Pronouns: A Role for Word-Specific Gender Stereotype Information[END_REF][START_REF] Misersky | Norms on the gender perception of role nouns in Czech, English, French, German, Italian, Norwegian, and Slovak[END_REF].

The interaction between social role assignment and stereotypical beliefs about the two sexes perpetuates the gender disparities across professional domains. According to Social Role Theory [START_REF] Eagly | Social role theory of sex differences and similarities: A current appraisal[END_REF][START_REF] Eagly | Social Role Theory of Sex Differences[END_REF], we often associate people with the roles they play in the society where they live, and at the same time, we perceive the qualities people exhibit when they are in roles as their personal properties. Since women and men typically occupy different roles in a community, they are thought of possessing different properties specific to the gender. In return, the stereotyped gender qualities feed normative role beliefs that the two sexes should behave differently and take on different roles [START_REF] Eagly | Social Role Theory of Sex Differences[END_REF]. For example, the observation that women occupy the role of caregiver leads us to think that they possess caregiving properties -being warm, emotionally expressive, and mindful of other people's feelingsand that they should play the role of caregiver. However, women are considered as less suitable for a leadership role, and are less often seen as assertive, dominant and aggressive, qualities that characterize a leader and decision maker, due to the fact that females are a rarity in positions of authority.

There are two mechanisms by which gender stereotypes may affect the distributions of men and women: externally through societal expectations and internally by individuals' identification with the gender roles. On the one hand, stereotypes may blind us to differences between members of a group, and in consequence bias our perceptions and judgments about individual group members. External bias, manifested in the discriminatory practices against females in hiring and promotion processes, has been argued to contribute to the underrepresentation of women in traditional male-dominated professions such as the STEM (Science, Technology, Engineering and Mathematics) fields [START_REF] Charlesworth | Gender in science, technology, engineering, and mathematics: Issues, causes, solutions[END_REF][START_REF] Koch | A meta-analysis of gender stereotypes and bias in experimental simulations of employment decision making[END_REF]. For instance, when applying for a lab manager position at a research intensive university, a female candidate was evaluated less positively than a male candidate even though they had exactly the same resume (Moss-Racusin et al., 2012a). Similarly, the same performance review of a veterinarian was evaluated less favorably and in result lower salaries were proposed by employers when the purported gender on the document was female rather than male [START_REF] Begeny | In some professions, women have become well represented, yet gender bias persists-Perpetuated by those who think it is not happening[END_REF], and, compared to men, women were less likely to be employed to perform mathematical tasks [START_REF] Reuben | How stereotypes impair women's careers in science[END_REF]. Furthermore, even when women did succeed in maletyped fields, they were penalized for violating the stereotype that women are communal but not competitive, as shown in less favorable evaluations of female leaders than male ones [START_REF] Eagly | Role congruity theory of prejudice toward female leaders[END_REF][START_REF] Heilman | Description and prescription: How gender stereotypes prevent women's ascent up the organizational ladder[END_REF][START_REF] Heilman | Gender in the workplace. Sex stereotypes: Do they influence perceptions of managers[END_REF]. These studies suggest that gender stereotyped beliefs are able to induce biased perceptions and evaluations of women's qualities and competence, which may contribute to the sustaining underrepresentation of women in professions of high social status and economic reward.

On the other hand, internalized gender stereotypes and social norms may bind individuals' behaviors. Once identified with a social group, individuals think and behave in conformity with the social norms that define the group [START_REF] Hogg | Social identifications: A social psychology of intergroup relations and group processes[END_REF]. The normative belief that the two sexes possess different qualities and should align with different social roles can constrain the life and career choices individuals make (see [START_REF] Knight | One egalitarianism or several? Two decades of gender-role attitude change in Europe[END_REF]. For example, the dearth of women in STEM fields has also been arguably attributed to females' lower interest in these fields and higher personal preferences for less math-intensive occupations [START_REF] Breda | Girls' comparative advantage in reading can largely explain the gender gap in math-related fields[END_REF][START_REF] Ceci | Women's underrepresentation in science: Sociocultural and biological considerations[END_REF][START_REF] Ceci | Understanding current causes of women's underrepresentation in science[END_REF]. According to this view, women's higher interest in persons relative to objects leads them to opt out of math-intensive fields even though they are equally competent as men (see [START_REF] Ceci | Women's underrepresentation in science: Sociocultural and biological considerations[END_REF] for a review). However, women's career choices may not reflect their vocational aspirations but instead be constrained by the traditional gender stereotypes such as 'math is not for girls' and 'women are family-centered' [START_REF] Breda | Gender stereotypes can explain the genderequality paradox[END_REF][START_REF] Charles | Indulging our gendered selves? Sex segregation by field of study in 44 countries[END_REF][START_REF] Knight | One egalitarianism or several? Two decades of gender-role attitude change in Europe[END_REF]. Thus, individuals themselves are not free from the influence of gender norms when they decide what to do in their life.

Attitudes on Gender Equality Impacts Evaluations of Research on Gender Bias

The fact is indisputable that the STEM fields are male-dominated [START_REF] Shen | Inequality Quantified: Mind the Gender Gap[END_REF]. As illustrated before, the persistent underrepresentation of women has been attributed to multiple interacting factors, ranging from stereotype-based external biases (explicit and implicit), inherent individual differences in math abilities, to free or constrained life and career choices (see [START_REF] Ceci | Women's underrepresentation in science: Sociocultural and biological considerations[END_REF][START_REF] Charlesworth | Gender in science, technology, engineering, and mathematics: Issues, causes, solutions[END_REF]. Among these factors, previous research has provided evidence that discriminatory hiring and promotion practices disfavoring women partially accounts for the current gender disparities [START_REF] Begeny | In some professions, women have become well represented, yet gender bias persists-Perpetuated by those who think it is not happening[END_REF][START_REF] Moss-Racusin | Science faculty's subtle gender biases favor male students[END_REF]Régner et al., 2019a;[START_REF] Reuben | How stereotypes impair women's careers in science[END_REF]. For example, in the study of [START_REF] Moss-Racusin | Science faculty's subtle gender biases favor male students[END_REF], the experimenters asked professors at research-intensive universities to evaluate the CV of an undergraduate student for a lab manager position. All professors received the exact same CV except in one experimental group, the applicant was given a male name and in the other group, a female name. Results revealed a significant bias in favor of the male applicant, who was rated as more competent, hirable and was offered more mentoring and a higher starting salary than the female applicant with the same qualifications.

Despite research consistently showing that women are being discriminated against in STEM fields, people's reactions to this evidence are varied [START_REF] Danbold | Men's defense of their prototypicality undermines the success of women in STEM initiatives[END_REF][START_REF] Handley | Quality of evidence revealing subtle gender biases in science is in the eye of the beholder[END_REF][START_REF] Moss-Racusin | Can evidence impact attitudes? Public reactions to evidence of gender bias in STEM fields[END_REF]. For instance, by asking participants to rate the quality of the research by [START_REF] Moss-Racusin | Science faculty's subtle gender biases favor male students[END_REF], [START_REF] Handley | Quality of evidence revealing subtle gender biases in science is in the eye of the beholder[END_REF] showed that males rated the research less favorably than female participants, and that this sex difference in evaluations was more pronounced among STEM experts than the general public. A similar sex difference was documented by [START_REF] Moss-Racusin | Can evidence impact attitudes? Public reactions to evidence of gender bias in STEM fields[END_REF] who conducted a content analysis of the comments posted by readers of three press articles reporting on the research of [START_REF] Moss-Racusin | Science faculty's subtle gender biases favor male students[END_REF].

The authors found more positive reactions (e.g., calls for social change) among female readers, and more negative reactions (e.g. justifications of gender bias) among males. The reported sex difference in reactions was ascribed to ingroup bias, a mechanism by which men defend their dominant identity in STEM [START_REF] Danbold | Men's defense of their prototypicality undermines the success of women in STEM initiatives[END_REF][START_REF] Handley | Quality of evidence revealing subtle gender biases in science is in the eye of the beholder[END_REF]. However, previous research also revealed that both men and women can act as defenders of the male-dominated status quo [START_REF] Charles | Indulging our gendered selves? Sex segregation by field of study in 44 countries[END_REF][START_REF] Glick | Beyond Prejudice as Simple Antipathy: Hostile and Benevolent Sexism Across Cultures[END_REF][START_REF] Glick | An Ambivalent Alliance: Hostile and Benevolent Sexism as Complementary Justifications for Gender Inequality[END_REF][START_REF] Jost | Exposure to benevolent sexism and complementary gender stereotypes: Consequences for specific and diffuse forms of system justification[END_REF][START_REF] Napier | The joy of sexism? A multinational investigation of hostile and benevolent justifications for gender inequality and their relations to subjective wellbeing[END_REF].

Finding the explanation for the differing responses to research on gender bias is critical to the advance of gender equality. Individuals skeptical about the existence of COVID-19 and its ability to kill an infected person are more likely to violate social distancing rules, just as people who do not believe the existence and severity of gender inequality tend to make biased judgments and decisions against women. There is some evidence that individuals who think gender inequality is not any more a problem are more inclined to discriminatory views and practices. For example, Begeny et al, (2020) asked a group of managers in the profession of veterinary medicine (men and women have equal representations in this profession in the United States) to evaluate the performance review of a vet. The experimenters randomly assigned a male or female name to the vet while keeping every other content in the review identical. The authors found that managers endorsing the belief that gender inequality is a problem of the past (given the balanced representations of men and women) were more susceptible to under-evaluations of women's competence and worth, and as a result, assigning fewer career opportunities and lower salaries to female professionals relative to their male colleagues who possessed the exact same qualifications [START_REF] Begeny | In some professions, women have become well represented, yet gender bias persists-Perpetuated by those who think it is not happening[END_REF]. Consistent with this finding, scientific evaluation committees promoted fewer women to elite research positions, especially those who rejected the belief that external barriers (e.g. discrimination) rather than internal abilities constrained women's success in academia and caused their underrepresentation in STEM fields (Régner et al., 2019b). These findings suggest that people who are unaware of or having doubts about the extant gender disparities are more often than not the ones who act on stereotypes, have biased perceptions of women and make discriminatory decisions that contribute to the persistence of gender inequality.

Here, I propose that in addition to ingroup bias, a person's moral attitudes on gender equity may play a crucial role in their reception of new information related to gender bias. In particular, the moralization of gender equality -the tendency of seeing gender equality as a moral imperative that is central to one's personal identity [START_REF] Skitka | The Psychology of Moral Conviction[END_REF][START_REF] Skitka | Moral Conviction: Another Contributor to Attitude Strength or Something More[END_REF] can have significant implications for their factual beliefs and judgments about research touching on gender discrimination.

People tend to confirm what they believe to be true by selectively assimilating or rejecting new evidence, and more often than not, this tendency is moderated by their attitudes on the relevant issue. When faced with pro-attitudinal information, people are prompted to accept the information at face value as a way to validate their initial views, while for counter-attitudinal information, they would be skeptical about its relevance and reliability. This type of attitude-based (mis)trust in new information is a good demonstration of "motivated confirmation bias" [START_REF] Nickerson | Confirmation bias: A ubiquitous phenomenon in many guises[END_REF] or "motivated thinking" [START_REF] Kunda | Motivated Inference: Self-Serving Generation and Evaluation of Causal Theories[END_REF][START_REF] Kunda | The case for motivated reasoning[END_REF].

Motivated confirmation bias has been documented in many areas, such as biased processing of health messages [START_REF] Ditto | Motivated skepticism: Use of differential decision criteria for preferred and nonpreferred conclusions[END_REF][START_REF] Kunda | Motivated Inference: Self-Serving Generation and Evaluation of Causal Theories[END_REF][START_REF] Liberman | Defensive processing of personally relevant health messages[END_REF], and differential evaluations of arguments and evidence pertaining to controversial social issues like anthropogenic climate change, nuclear power and vaccine [START_REF] Campbell | Solution aversion: On the relation between ideology and motivated disbelief[END_REF][START_REF] Edwards | A disconfirmation bias in the evaluation of arguments[END_REF][START_REF] Lewandowsky | Worldview-motivated rejection of science and the norms of science[END_REF][START_REF] Lord | Biased Assimilation and Attitude Polarization: The Effects of Prior Theories on Subsequently Considered Evidence[END_REF][START_REF] Nisbet | The partisan brain: How dissonant science messages lead conservatives and liberals to (dis) trust science[END_REF][START_REF] Pennycook | Beliefs about COVID-19 in Canada, the UK, and the USA: A novel test of political polarization and motivated reasoning[END_REF][START_REF] Rutjens | Not all skepticism is equal: Exploring the ideological antecedents of science acceptance and rejection[END_REF][START_REF] Taber | Motivated skepticism in the evaluation of political beliefs[END_REF][START_REF] Washburn | Science denial across the political divide: Liberals and conservatives are similarly motivated to deny attitude-inconsistent science[END_REF].

For example, when confronted with new evidence pertaining to the crime deterrent effects of the death penalty, both the supporters and opponents of this practice were found to evaluate the information compatible with their prior beliefs as more convincing and reliable [START_REF] Edwards | A disconfirmation bias in the evaluation of arguments[END_REF][START_REF] Lord | Biased Assimilation and Attitude Polarization: The Effects of Prior Theories on Subsequently Considered Evidence[END_REF].

Following this line of research, it seems plausible that individuals respond to research showing discriminatory practices against women in academia based on their pre-existing moral attitudes, such that those who have moral convictions about gender equality find the evidence of gender bias against females more convincing than those who are less morally concerned. Having a strong moral commitment to gender equality, however, may also prompt individuals to make systematic errors in judgment, such as perceiving imprecise causal relations from correlations.

To investigate the origin of individuals' differing reactions to evidence of gender bias, and in particular, the effects of people's moral attitudes towards gender equality on their trust in science, Chapter 4 presents six experiments examining whether individuals' self-reported moral commitment to gender equality predicts their evaluations of research summary demonstrating gender bias against vs. favoring women, which may be consistent or inconsistent with their prior beliefs. Additionally, we also examined if individuals are more inclined to make inadequate inferences when faced with a palatable conclusion.

Introduction

The relationship between language and thought, and in particular the question of whether the structure of one's language has a deep influence on how we think about and perceive the world around us, has long intrigued philosophers, linguists, anthropologists, and psychologists [START_REF] Boroditsky | Does Language Shape Thought?: Mandarin and English Speakers' Conceptions of Time[END_REF][START_REF] Levinson | Returning the tables: Language affects spatial reasoning[END_REF]Pinker, 2007;[START_REF] Whorf | Language, thought and reality[END_REF]. Strong views of Whorfianism, i.e. the theory that our native language strictly determines the representational structures and processes underlying thought, have been largely discredited (see [START_REF] Wolff | Linguistic relativity[END_REF]Reines & Prinz, 2009, for a review). For example, if linguistic differences radically determine thought, then we would not be able to create new words or accurate translation from one language to another should not be so commonplace (Pinker, 2007).

There is, however, a body of more recent empirical work claiming to show that weaker versions of the Whorfian thesis may hold true: While language does not strictly determine thought, it may influence it in subtle and non-obvious ways (see [START_REF] Wolff | Linguistic relativity[END_REF]Reines & Prinz, 2009;Casanto, 2008, for a review). This topic has been examined from a number of angles, including looking at the relationship between color terms and color perception [START_REF] Davies | A cross-cultural study of colour grouping: Evidence for weak linguistic relativity[END_REF][START_REF] Gilbert | Whorf hypothesis is supported in the right visual field but not the left[END_REF][START_REF] Thierry | Unconscious effects of language-specific terminology on preattentive color perception[END_REF][START_REF] Winawer | Russian blues reveal effects of language on color discrimination[END_REF], the influence of linguistic labels on conceptual category learning [START_REF] Boutonnet | Words Jump-Start Vision: A Label Advantage in Object Recognition[END_REF][START_REF] Lupyan | Language is not just for talking: Redundant labels facilitate learning of novel categories[END_REF], and the influence of language on spatial and temporal reasoning [START_REF] Boroditsky | Does Language Shape Thought?: Mandarin and English Speakers' Conceptions of Time[END_REF][START_REF] Haun | Cognitive cladistics and cultural override in Hominid spatial cognition[END_REF][START_REF] Levinson | Space in language and cognition: Explorations in cognitive diversity[END_REF][START_REF] Levinson | Returning the tables: Language affects spatial reasoning[END_REF][START_REF] Li | Spatial reasoning in tenejapan mayans[END_REF][START_REF] Loewenstein | Relational language and the development of relational mapping[END_REF][START_REF] Majid | Can language restructure cognition? The case for space[END_REF][START_REF] Munnich | Spatial language and spatial representation: A crosslinguistic comparison[END_REF]. Critics of this view have argued that any observed effects are small enough so as to lack much ecological importance (Bloom & Keil, 2001;Pinker, 2007), can be explained through non-linguistic differences, such as differences in culture (Björk, 2008), or can be explained through relatively uninteresting task demands [START_REF] Mickan | Key is a llave is a Schlüssel: A failure to replicate an experiment from Boroditsky et al[END_REF][START_REF] Cubelli | The Effect of Grammatical Gender on Object Categorization[END_REF]).

Here we focus on one of the most popular examples of linguistic structure (putatively) influencing thought: The idea that the grammatical gender for nouns referring to objects causes speakers to conceive of those objects as having more masculine or feminine characteristics [START_REF] Bassetti | Bilingualism and thought: Grammatical gender and concepts of objects in Italian-German bilingual children[END_REF][START_REF] Beller | Culture or language: What drives effects of grammatical gender?[END_REF][START_REF] Bender | Grammatical gender in German: A case for linguistic relativity[END_REF]Bender et al., , 2016a[START_REF] Bender | Lady Liberty and Godfather Death as candidates for linguistic relativity? Scrutinizing the gender congruency effect on personified allegories with explicit and implicit measures[END_REF][START_REF] Boroditsky | Language in Mind: Advances in the Study of Language and Thought[END_REF][START_REF] Boutonnet | Unconscious effects of grammatical gender during object categorisation[END_REF][START_REF] Cubelli | The Effect of Grammatical Gender on Object Categorization[END_REF][START_REF] Haertlé | Does grammatical gender influence perception? A study of Polish and French speakers[END_REF][START_REF] Imai | All giraffes have female-specific properties: Influence of grammatical gender on deductive reasoning about sex-specific properties in german speakers[END_REF][START_REF] Kousta | Investigating linguistic relativity through bilingualism: The case of grammatical gender[END_REF][START_REF] Mickan | Key is a llave is a Schlüssel: A failure to replicate an experiment from Boroditsky et al[END_REF][START_REF] Saalbach | Grammatical Gender and Inferences About Biological Properties in German-Speaking Children[END_REF][START_REF] Sera | Grammatical and conceptual forces in the attribution of gender by English and Spanish speakers[END_REF][START_REF] Sera | When language affects cognition and when it does not: An analysis of grammatical gender and classification[END_REF]. In order to understand what is at stake, we suggest a few theoretical distinctions here.

One can distinguish natural (i.e. biological) sex, conceptual gender, and grammatical gender. Biological sex refers to the physical characteristics of an individual's reproduction system which determine whether a person or an animal is male, female, or intersex. By definition this is not applicable to objects. Conceptual gender relates to mental representations of and associations with biological sex, and can thus go beyond the limits of biological traits. It can pick out social roles typically related to members of each sex or can refer to a form of personal identification based on an internal awareness. Thus, certain objects can also evoke strong gender associations. For example, "lipstick" is often associated with females because women and not men typically use lipstick in modern western societies. Finally, grammatical gender refers to a linguistic way of categorizing nouns into classes which triggers agreement in other words, such as articles, adjectives, or verbs [START_REF] Aikhenvald | How gender shapes the world[END_REF][START_REF] Corbett | Gender[END_REF]. A large proportion of the world's languages have a grammatical gender system [START_REF] Aikhenvald | How gender shapes the world[END_REF][START_REF] Corbett | Gender[END_REF]. These systems can be roughly divided between those that are sex-based and those based on other semantic features such as animacy or size. In sex-based grammatical gender systems, terms which clearly refer to males vs. females predictably fall, respectively, into grammatical masculine and feminine categories. As to objects, they are assigned grammatical gender in a mostly arbitrary fashion in such languages [START_REF] Corbett | Gender[END_REF]. For example, "lipstick" in French (rouge à lèvres) is grammatically masculine despite its female gender association. Similarly, French nouns such as table ("table ") and bureau ("desk") differ in their grammatical gender despite obvious semantic similarity (with the former being feminine in French and the latter being masculine).

The central question that has sparked so much scientific and public interest is whether the grammatical gender of nouns that refer to objects fundamentally changes how speakers of the language conceive of these objects. When an object has feminine gender, do we think of it as possessing more feminine characteristics (and vice-versa for objects that have masculine gender)?

While this question has been investigated from a variety of angles [START_REF] Bassetti | Bilingualism and thought: Grammatical gender and concepts of objects in Italian-German bilingual children[END_REF][START_REF] Beller | Culture or language: What drives effects of grammatical gender?[END_REF][START_REF] Bender | Grammatical gender in German: A case for linguistic relativity[END_REF]Bender et al., , 2016a[START_REF] Bender | Lady Liberty and Godfather Death as candidates for linguistic relativity? Scrutinizing the gender congruency effect on personified allegories with explicit and implicit measures[END_REF][START_REF] Boroditsky | Language in Mind: Advances in the Study of Language and Thought[END_REF][START_REF] Boutonnet | Unconscious effects of grammatical gender during object categorisation[END_REF][START_REF] Cubelli | The Effect of Grammatical Gender on Object Categorization[END_REF][START_REF] Haertlé | Does grammatical gender influence perception? A study of Polish and French speakers[END_REF][START_REF] Imai | All giraffes have female-specific properties: Influence of grammatical gender on deductive reasoning about sex-specific properties in german speakers[END_REF][START_REF] Kousta | Investigating linguistic relativity through bilingualism: The case of grammatical gender[END_REF][START_REF] Mickan | Key is a llave is a Schlüssel: A failure to replicate an experiment from Boroditsky et al[END_REF][START_REF] Saalbach | Grammatical Gender and Inferences About Biological Properties in German-Speaking Children[END_REF][START_REF] Sera | Grammatical and conceptual forces in the attribution of gender by English and Spanish speakers[END_REF][START_REF] Sera | When language affects cognition and when it does not: An analysis of grammatical gender and classification[END_REF], it was brought to wider attention by a study summarized by [START_REF] Boroditsky | Language in Mind: Advances in the Study of Language and Thought[END_REF].

This study was conducted entirely in English on bilinguals whose native language was either German or Spanish. Participants were asked to associate adjectives with nouns, whose translations were either grammatically feminine in German and masculine in Spanish or viceversa. These adjectives were then rated as describing masculine or feminine properties by a group of English speakers. The key finding was that people produced qualitatively different adjectives depending on the grammatical gender of the relevant nouns in their native language.

For example, the word "bridge" when translated into German is grammatically feminine (brücke) and when translated into Spanish is masculine (puente). For "bridge", German speakers were reported to have produced adjectives that were rated as more feminine (e.g. beautiful, elegant, fragile, peaceful, pretty, and slender), while Spanish speakers produced adjectives that were rated as more masculine (e.g. big, dangerous, long, strong, sturdy, and towering).

These results have seemingly entered into the public's understanding of how language influences thought.

For example, Borodisksy's TED talk describing this work (https://www.youtube.com/watch?v=RKK7wGAYP6k) has been viewed more than 5 million times on Youtube alone. [START_REF] Boroditsky | Language in Mind: Advances in the Study of Language and Thought[END_REF] is also highly cited and continues to be cited in scientific work as evidence for an effect of grammatical gender on how we conceive of objects despite the crucial experiment summarized in it having never been published. Given the apparent widespread belief in the underlying theoretical claims, it is thus worth assessing just how robust the empirical evidence is.

The experimental paradigm described in [START_REF] Boroditsky | Language in Mind: Advances in the Study of Language and Thought[END_REF] is particularly wellsuited to address the issue of a conceptual effect of grammatical gender, as it does not explicitly ask participants to rate how masculine or feminine they perceive a given noun to be and therefore does not suffer from obvious task demands that could potentially serve as alternative explanations. This separates the paradigm from those which ask participants to explicitly rate how masculine or feminine they find specific nouns referring to objects to be (e.g. [START_REF] Clarke | Gender perception in Arabic and English[END_REF], to classify pictured objects as either masculine or feminine (e.g. [START_REF] Sera | Grammatical and conceptual forces in the attribution of gender by English and Spanish speakers[END_REF], or to assign a male or female voice to objects or animals (e.g. [START_REF] Haertlé | Does grammatical gender influence perception? A study of Polish and French speakers[END_REF][START_REF] Sera | When language affects cognition and when it does not: An analysis of grammatical gender and classification[END_REF]. In all of these cases, one can reasonably worry about any seeming gender effect merely reflecting how participants explicitly reason through or strategize about the task at hand. In contrast, empirically robust results from the paradigm used by [START_REF] Boroditsky | Language in Mind: Advances in the Study of Language and Thought[END_REF] would clearly strengthen the theoretical claim that grammatical gender does in fact influence object cognition. So far, one failed attempt at a conceptual replication [START_REF] Mickan | Key is a llave is a Schlüssel: A failure to replicate an experiment from Boroditsky et al[END_REF] has shed doubt on the replicability of the results. To the best of our knowledge, the use of different paradigms has similarly failed to generalize the results (e.g. Degani, 2007;[START_REF] Kousta | Investigating linguistic relativity through bilingualism: The case of grammatical gender[END_REF], thus enhancing the need for empirical clarity.

Our approach

Here we offer two innovative conceptual replications of [START_REF] Boroditsky | Language in Mind: Advances in the Study of Language and Thought[END_REF] using a methodology broadly based on their original approach. The novelty of the experiments here is that we "stack the deck" in favor of the original hypothesis. We choose to do this based on extensive piloting work (see supplementary materials) in addition to the published nonreplication [START_REF] Mickan | Key is a llave is a Schlüssel: A failure to replicate an experiment from Boroditsky et al[END_REF], suggesting that any influence of grammar on conceptual object representations is either weak or non-existent. Given the question marks we had about these effects, we decided on the "stack the deck" approach such that if there were a true underlying influence of grammatical gender on object cognition, our methodology would provide the best possible chance of detecting it.

In particular, in contrast to previous studies, participants will be tested in their native language as opposed to in a second language that has no grammatical gender, such as English.

The choice to originally test bilinguals in English was meant to counter any effects that might bias the results in favor of the hypothesis [START_REF] Boroditsky | Language in Mind: Advances in the Study of Language and Thought[END_REF]. All else being equal, one would thus expect that testing directly in a language that contains grammatical gender (such as French or German) would only serve to enhance gender effects on thought. Moreover, related experimental work using other paradigms has shown that experiments conducted in the participants' native language can produce significant effects of grammatical gender [START_REF] Bassetti | Bilingualism and thought: Grammatical gender and concepts of objects in Italian-German bilingual children[END_REF][START_REF] Kousta | Investigating linguistic relativity through bilingualism: The case of grammatical gender[END_REF] and that English-French and English-Spanish bilinguals show weaker sex-stereotype thinking when tested in English than when tested in gendered Romance languages (Wasserman & Weseley, 2009).

A second way in which we increase the likelihood of detecting an underlying effect (if there is one to be found) is by including gender marked determiners on the relevant noun items.

One would presume that, if anything, making grammatical gender information more salient in this way would again only serve to enhance any underlying effects if they are truly present.

The advantage of our approach is that if (as suggested by our piloting results) we find null effects of grammatical gender on the masculinity/femininity of adjectives people associate with masculine vs. feminine nouns, this will allow for strong inference against the original hypothesis.

This inferential strength from a potential null result comes at the cost of inferential strength in the case of a positive result. In other words, if positive effects of grammatical gender on adjective choice are found, this could be due to the underlying hypothesis being true, or it could be due to possible confounds which were intentionally introduced to increase the odds of finding any effect. For example, perhaps mere statistical associations between grammatically gendered determiners and certain adjectives, which are independent of conceptualization, could drive a positive effect. We therefore also plan for "conditional" experiments: if positive effects are found when gendered determiners are visible (nouns presented in singular forms), we will run followup experiments in which the nouns will be presented in plural forms, thus the relevant determiners are no longer used (German group) or do not visibly carry gender information (French group). To ensure that any null effect we find is not due to a lack of statistical power, we will use Bayesian analyses. These methods will allow us to quantify our confidence in null results.

Experiment 1

In this experiment we will test the gender effect hypothesis for pairs of French nouns that are related in meaning but have opposite grammatical gender. The choice of studying French instead of Spanish or Italian is theoretically neutral in that putative effects of grammatical gender on object conceptualization is not intended to be language specific. Thus, this choice should not in principle affect the underlying hypothesis derived from the broader theory.

Choosing semantically related nouns as stimuli will allow us to reduce a possible bias due to word meaning. We will test nouns referring to objects, and add a control condition with nouns referring to persons. That is, as male and female persons are typically associated with different gender traits (Costa et al., 2001), we expect to observe a gender effect for person nouns.

Methods

We will manipulate two factors, noun type (i.e. referring to objects vs. persons) and grammatical gender (masculine vs. feminine).

Materials

Person nouns. As control items we selected 12 pairs of person nouns, including kinship terms (e.g. father, mother) and role names (e.g. king, queen) (see Appendix B1). Within each pair, the two nouns are semantically related, as one refers to a male person and the other to the female counterpart (e.g. père 'father'mère 'mother'). Importantly, the grammatical gender of person nouns is consistent with the biological sex of their referents. For instance, père 'father' has masculine and mère 'mother' has feminine gender.

Object nouns. To avoid experimenter bias in selecting stimuli (see [START_REF] Strickland | Experimenter Philosophy: The Problem of Experimenter Bias in Experimental Philosophy[END_REF] for a discussion) we designed two tests to standardize our choices of object nouns. The first test asked a group of participants to generate semantically related noun pairs, and the second one invited another group of participants to rate these pairs on a scale for semantic relatedness. Note that as the items are meant to be presented with a gendered definite article, all nouns should be consonant-initial; indeed, before vowel-initial nouns, the masculine and the feminine article, i.e.

le and la, lose their vowel and hence become indistinct).

Noun pair generation: We recruited native French speakers (N = 155, 67 men, 86 women, and 2 other sex), aged between 18 and 61 years (M = 33, SD = 11.1), as participants on the platform Clickworker (https://www.clickworker.com/) for what was described as a "linguistic task". According to their report, none of them had learned a foreign language that had a grammatical gender system. They were paid 0.60 € for their participation.

The test was run online on Qualtrics (https://www.qualtrics.com). Participants were first shown instructions asking them to provide 12 pairs of semantically related nouns (e.g. sable "sand"plage "beach") that obey several constraints: Each pair should consist of one masculine and one feminine noun; all nouns should start with a consonant, and this consonant should not be 'h' (as before many h-initial nouns the masculine and feminine articles become indistinct, just like before vowel-initial words); all words should refer to objects or concrete places and no word should refer to animals or persons.

When they finished reading the instructions, participants were then shown seven pairs that violated a given constraint, along with explanations of why those pairs were not acceptable.

Next, they were shown seven different pairs with only one of them obeying all constraints, and they had to find the good one. Those who had found the right pair were told so, while those who had chosen an unacceptable pair were explained why their choice was wrong and they were shown the right pair. After receiving the feedback, all participants were able to move to the main task, which was to type in 12 word pairs. The above constraints remained visible during the test.

The test ended with questions about participants' sex, age and native language.

After removal of pairs containing compound words (e.g. brosse à dents 'toothbrush'), non-French words (e.g. ring), person nouns (e.g. princesse 'princess'), adjectives (e.g. pauvre 'poor') and abbreviations (e.g. CD), the list of responses comprised 883 noun pairs. We selected the 249 pairs that had been proposed by the largest number of participants (range: 2 -58 times)

to be used in the semantic relatedness rating test for final stimuli selection.

Semantic relatedness rating test: In order to assess the semantic relatedness of the pairs generated in the previously described phase, a norming test was run online using Labvanced (https://www.labvanced.com/).

In addition to the 249 target pairs, we included 83 filler pairs (i.e., 1/3 of the number of target pairs), created by pairing one masculine and one feminine noun taken from different pairs.

We then randomly divided the 332 word pairs (249 target and 83 filler pairs) into five lists, with each list containing between 65 and 67 pairs (i.e. 49 or 50 targets and 16 or 17 fillers).

Participants were randomly assigned to one of the five lists. The order in which the pairs of a relevant list were displayed was fixed across participants, with filler pairs being evenly distributed among target pairs.

We recruited native French speakers (N = 94, 59 men and 35 women), aged between 21 and 76 years (M = 43, SD = 11.9) on the crowdsourcing platform Foulefactory (https://www.foulefactory.com). We restricted recruitment to participants who had not learned a foreign language that also had a grammatical gender system as participants. They were paid 0.50€ for their participation.

Participants were presented with the word pairs one by one and asked to indicate on a 6point scale to what extent they thought the words were semantically related (1 -Not at all related, 6 -Perfectly related). We specifically made clear that they should not reflect too much on the task, but instead respond based on intuitions. After finishing all trials, participants answered questions about their sex, age, native language, and second language learned before age 10.

As a manipulation check, we ran a t-test on the average ratings between target and filler pairs. Results showed that target noun pairs (M = 4.56, SE = .008) were rated as more semantically related than filler pairs (M = 1.27, SE = .004; t(330) = 39.62, p < .0001). Eighty test pairs had received a mean score between 5 and 5.9 (M = 5.41, SD = .24). From these, we removed certain pairs such that the final set contained no duplicated nouns, i.e. nouns appearing in more than one pair. For example, consider the pairs toiletableau (5.76), peinturetableau

(5.62), and peinturepinceau (5.47). Both tableau and peinture appeared twice. As toiletableau had the highest rating among the three, we excluded peinturetableau because of the duplicate noun tableau (as well as all other pairs containing either toile or tableau), after which peinturepinceau no longer contained a duplicate noun and was hence kept. Then, from the unique pairs, we removed those containing words with ambiguous meanings (e.g., the word mine in French can refer to ore mining, a pencil core, a facial expression, or an explosive device). The final set consisted of 52 pairs that were matched in number of syllables (Mmasc = 1.81, Mfem = 1.60, t(50) = 1.75, p = 0.09). See Appendix B2 for the complete list.

Procedure

The experiment will be conducted online using Labvanced software. It will consist of two parts, adjective generation and adjective rating, performed by different groups of participants.

Adjective generation. The first part of the experiment assesses which characteristics participants tend to associate with inanimate entities. Participants will be told that the experiment is about the associations between nouns (pre-tested and selected above) and adjectives, with no mention of our interest in comparing masculine vs. feminine nouns. They will be shown four short sentences and asked to complete each sentence with three different adjectives. Nouns will be presented as subjects of sentences in singular forms, preceded by gender-marking articles le and la respectively for masculine and feminine words. The adverb très 'very' is used in the sentences to elicit gradable adjectives, which are more likely to represent people's subjective evaluations of non-arbitrary objects' characteristics (Wheeler, 1972). The presence of the adverb will also eliminate set phrases such as courrier recommandé ("registered mail").

Examples of an object and a person noun embedded in the carrier sentence are shown in

(2).

(2) a. Object noun: main 'hand'

La main est très _____

'The hand is very_____' b. Person noun: mère 'mother'

La mère est très _____ 'The mother is very_____'

Participants will first be randomly assigned to either the object or person noun condition, and within each condition, randomly to a subset of four pairs. The goal is to assign random pairs to each participant while ensuring that each pair is seen by the same number of participants. To avoid making the comparison of grammatical gender too salient, each participant will see only either the masculine or the feminine word of a semantic pair. From the four pairs assigned to each participant, we will randomly select two masculine and two feminine nouns. We will also ensure that the two nouns within each pair (masculine and feminine) are shown to the same number of participants. The test will end with demographic questions about participants' sex, age, native language, foreign language, and country of residence.

We will exclude all non-adjectival and non-French responses, and select adjectives that are used more than once for the following rating task. There is no minimum number of adjectives to be rated, but to limit the test to a manageable scale, we will test a maximum of 200 adjectives (in the adjective rating task described just below). If more than 200 adjectives are generated, we will order them by the number of times they were used and remove individual adjectives, starting from the least frequent one, until there are 200 left.

Adjective rating. The second part of the experiment tests if adjectives associated with feminine nouns are more likely to be related to female gender traits, and vice versa for masculine nouns. Participants will be randomly presented with adjectives and asked to indicate on a 7-point

Likert scale to what extent they think the words represent a masculine or a feminine quality (1 'Very masculine' -7 'Very feminine'). Adjectives that have gender inflection, i.e. varying forms for masculine and feminine gender agreement, will be presented in both forms (e.g. petit/petite 'smallmasc/smallfem'), while those having a single form for masculine and feminine gender will be shown in their unique form (e.g. pratique 'practical/convenient'). Participants will be told not to deliberate over the task but instead to respond based on intuitions. Each participant will be assigned to between 50 and 70 adjectives (the exact number will depend on how many items will be produced in the adjective generation test), presented one at a time in random order. As an attention check, they will be asked from time to time to recall the previous word they saw. There will be one such attention check every 10 trials over the test.

As before, the test will end with demographic questions about participants' sex, age, native language, foreign language, and country of residence.

Sample sizes

For the adjective generation test, we will randomly generate 10 partitions of the object and person nouns into thirteen and three subsets of four pairs, respectively. We aim for a sample size of 160, i.e. 130 for the object noun condition and 30 for the person noun condition, thus with each noun being shown to 10 participants. As data will be collected in batches with the exclusion criteria applied after a batch is completed, we may end up with a slightly bigger sample size than 160.

For the adjective rating test, the exact sample size will depend on the number of adjectives to test. Each participant will rate between 50 and 70 adjectives. For each adjective, we aim for at least 25 ratings. Again, as data will be collected in batches with the exclusion criteria applied after a batch is completed, we may end up with a slightly bigger sample size than 25 per adjective.

Participants

Participants will be native French speakers, aged at least 18 years, who have not started learning a second language with a grammatical gender system before age 10, whose self-rated proficiency in any such language does not exceed 5 on a scale from 1 to 7, and who live in France. Participants in the adjective generation task will be paid 0.50€ and those in the adjective rating task 0.60€ for their time.

We will exclude participants who do not satisfy all our recruitment criteria. For both tests, participants who fail to complete the assigned task will be excluded from the analyses. If a participant took the study more than once, only the first set of responses will be kept. Finally, we will exclude data from participants who fail to answer all attention check questions correctly at the rating task.

Statistical analysis

We will first extract the mean rating on the masculine-feminine scale for each adjective from the rating task to define its female quality association index (FQA). The data from the generating task will be analyzed with a Bayesian linear mixed-effects model fitted with Stan (Carpenter et al., 2017), using uninformative priors. The dependent variable will be the FQA of the generated adjectives and the predictors will be the gender of the noun for which the adjective was generated (sum-coded), the type of entity denoted by the noun (object or person, treatmentcoded with object as the baseline), and their interaction. The model will include the maximal random effects structure for both participants and noun pairs (Barr et al., 2013). This includes random intercepts and random slopes for gender together with their correlation (gender is both within-participant and within-item), but no random slopes for object type, which is both between-participants and between-items. The Stan code for the model is provided in Appendix A1.

If grammatical gender does affect conceptualization, we expect the adjectives generated for an object noun with feminine grammatical gender to have a more feminine rating on average.

This would translate as a positive main effect of gender in our model. For person nouns, we strongly expect a clear effect of gender, so the interaction between gender and object type is expected to be positive. This interaction is therefore of little theoretical interest, but can be used to estimate the sensitivity of our design.

We will report the 95% HDI Credible Interval for the main effect of noun gender and its interaction with object type, as well as the posterior probability P(β>0) for each parameter. We will then compare the full model to a model without the main effect of gender, and report the Bayes factor. If the Bayes factor is superior to 3 and/or P(β>0) > .95, we will run the follow-up experiment with plurals to control for the role of gendered articles.

Experiment 2

One limitation of Experiment 1 is that we are unable to compare exactly the same word in the masculine vs. feminine form. While focusing on semantically related pairs within a language is a reasonable proxy, looking across languages at words with matched meanings but which differ only in their grammatical gender is arguably a "purer" test of the original theory (despite the fact that translation equivalents are rarely 100% equivalent). Thus, the aim of Experiment 2 is to extend our test of the gender effect hypothesis from within a single language to across languages.

This also brings us closer to the experiment summarized in [START_REF] Boroditsky | Language in Mind: Advances in the Study of Language and Thought[END_REF].

Here we will compare across French and German to investigate if grammatical gender influences native speakers' conceptualization of objects. In particular, we ask whether translation equivalents in French and German that have opposite grammatical gender (e.g., pont -Brücke 'bridge') will be associated differentially with more male vs. female qualities by native speakers of these two languages, such that speakers of both languages associate grammatically masculine and feminine nouns with typically male and female qualities, respectively. In contrast to [START_REF] Boroditsky | Language in Mind: Advances in the Study of Language and Thought[END_REF], instead of testing bilinguals in a non-gendered language like English, we instead test French and German speakers directly in their native language. We reason that if anything, doing this should increase the odds of finding an effect of grammatical gender on the femininity/masculinity of the adjectives produced, due to broad statistical associations that will likely have been built up between gender marked determiners and gender associated conceptual properties.

To address potential concerns about the influences of words' specific gender connotations, i.e. some words might be conceptually associated with males or females, we will run a control analysis with an added predictor for the gender association of English translations of the French/German pairs, measured independently.

Additionally, Experiment 2 will answer a secondary question of whether natural entities are more associated with female qualities and artifacts, with male qualities as suggested by previous studies (e.g. [START_REF] Mullen | Children's classifications of nature and artifact pictures into female and male categories[END_REF][START_REF] Sera | Grammatical and conceptual forces in the attribution of gender by English and Spanish speakers[END_REF] by comparing words for natural items vs.

artifacts.

Methods

We will manipulate two factors: language (French vs. German) and noun gender (masculine vs. feminine). Employing a similar method as for Experiment 1, we will test translation equivalent nouns that are assigned opposite grammatical gender in French and German (i.e. masculine in French and feminine in German, and vice versa). Unlike in Experiment 1, we only test nouns for inanimate entities.

Materials

We selected 59 pairs of translation equivalent nouns with opposite gender in French and German; 30 are masculine in French and feminine in German, and 29 are feminine in French and masculine in German (see Appendix B3). Among them, 23 nouns refer to natural entities (e.g., 'mountain'), 27 to artifacts (e.g., 'spoon'), and 9 cannot be easily categorized (e.g., 'milk').

Gender is balanced within each of these categories.

All nouns denote concrete objects, and none of them denotes an animal, body part, or clothing item. In addition, none has more than one, frequent, meaning in one of the languages (e.g. we excluded French bureau, which means both 'desk' and 'office'), and none has a language-specific cultural connotation (e.g., we excluded the pair masque -Maske 'mask', as the COVID-19 crisis might have induced different attitudes towards face masks in France and Germany). All French nouns are consonant-initial (such that a preceding definite article is gender-marked). 5

The French words contain between 1 and 3 syllables, the German ones between 1 and 4 (MFrench = 1.66; MGerman = 1.85; t(58) = -1.90; p = .06). Among the French words, there is no difference in number of syllables between masculine and feminine words (Mmasc = 1.80; Mfem = 1.52; t(57) = 1.75, p = .09), while among the German words, the feminine ones are longer than the masculine ones (Mmasc = 1.59; Mfem = 2.10; t(57) = -2.83, p < .006).

For the subset analysis that addresses the potential confound of gender association, we ran a pretest in a neutral language, English, that does not have a grammatical gender system. We (1 "Men" -7 "Women"). Words were presented in random order across participants.

Procedure

The procedure will remain identical to that of Experiment 1. Participants will be tested in their native language.

The nouns will be randomly divided into 15 subsets, with 14 of them containing 4 words 5 In order to select the pairs, we first retrieved a list of French nouns from the electronic dictionary Lexique (http://www.lexique.org/), which we ordered from highest to lowest lemma frequency according to Lexique's database of movie subtitles. Starting from the most frequent one, and taking into account the constraints mentioned above, we used an online French-German dictionary (https://fr.langenscheidt.com/francais-allemand) to look up the German translation equivalents. Whenever a French word had more than one translation, we only considered the first, most frequent, one. All pairs in the final selection were checked by a native speaker of German who has learned French and has lived in France for nearly two decades.

(2 masculine and 2 feminine in French) and one subset containing 3 words (2 masculine and 1 feminine in French). Participants will be randomly assigned to one of the 15 subsets and within each subset, words will be presented in random order.

The relevant sentences for the word bridge in French and German are shown in (3).

Sample sizes

For the adjective generation test, we aim for a sample size of 300 (150 for each language group), with each noun being presented to 10 participants. As data will be collected in batches with the exclusion criteria applied after a batch is completed, we may end up with a slightly bigger sample size than 300.

For the adjective rating test, the exact sample size will depend on the number of adjectives to test. Like in Experiment 1, each participant will rate between 50 and 70 adjectives.

For each adjective, we aim for at least 25 ratings. Again, as data will be collected in batches with the exclusion criteria applied after a batch is completed, we may end up with a slightly bigger sample size than 25 per adjective.

Participants

Participants will be native French and German speakers who live in France and Germany, respectively, aged at least 18 years, who have not started learning a second language with a grammatical gender system before age 10, whose self-rated proficiency in any such language does not exceed 5 on a scale from 1 to 7. Participants of the adjective generation task will be paid 0.50 € and those of the adjective rating task 0.60 € for their time. The exclusion criterion is identical to that for Experiment 1.

Statistical analysis

The data will be analyzed following the same procedure as Experiment 1. The predictors for this model will be noun gender (again, sum-coded), language (sum-coded), and their interaction. We will include the maximal random-effects structure, which this time includes random intercepts and gender slopes for participants, and random intercepts, gender and language slopes for noun pairs (but not their interaction), as well as all correlations. The Stan code for the model is provided in Appendix A2.

The effect of interest is the main effect of noun gender, for which we will report 95% HDI credible interval, posterior probability P(β>0), and the Bayes factor in favor of a model without this main effect.

In addition to this main analysis, we will run the following three control analyses: First, as word length might influence perceived conceptual gender, we will control for the number of syllables by removing all pairs in which the German word has three or four syllables (N = 8).

The remaining 51 word pairs (i.e. 23 masculine in French and feminine in German, 28 the reverse) show no difference in number of syllables between the French and German equivalents (t(49) = 0.60, p = 0.55), nor between masculine and feminine in either language (French: t(49) = 0.89, p = 0.38; German: t(49) = 1.50, p = 0.14).

53

Second, a strong association of certain items with either men or women (e.g., cigar, apron) could obfuscate a potential influence of grammatical gender. To control for this, we will run a model including gender association of the English translation of the word as a predictor, as well as its interaction with grammatical gender.

Finally, we will compare words for natural items vs. artifacts to test the hypothesis that natural entities are more associated with women and artifacts, with men [START_REF] Mullen | Children's classifications of nature and artifact pictures into female and male categories[END_REF][START_REF] Sera | Grammatical and conceptual forces in the attribution of gender by English and Spanish speakers[END_REF]. Leaving aside the nine items which are neither typically natural nor artificial, we would run a model similar to the main analysis, but with an extra predictor for object type (artifact vs. natural, sum-coded).

If the Bayes factor is superior to 3 and/or P(β>0) >.95 for the main analysis, and control analyses show that this effect is neither an artifact of word length nor gender association of the noun pairs, we will run the follow-up experiment with plurals to control for the role of gendered articles.

Pilot Studies Pilot 1

This pilot is similar to Experiment 1 in design. The object and person noun conditions in this pilot were run separately at different times, with different participant groups, and slightly different experimental designs. To be consistent with descriptions of Experiment 1, and to help readers make sense of the results, we present the two conditions together as a single pilot.

Person noun condition

We used the same stimuli as described in Experiment 1, and similarly, it included two tasks: adjective generation and adjective rating.

Materials

The items were the same as those in Experiment 1, consisting of 12 pairs of person nouns in which the two nouns are semantically related, with one referring to a male person and the other to the female counterpart (e.g. père 'father', mère 'mother') (see Appendix B1).

Procedure

Adjective generation. The procedure of this test was similar to that of Experiment 1, with two exceptions. First, we used a single-trial design: participants were randomly presented with only one of the 24 person nouns. Thus, noun gender was a between-subject factor. Second, the words were presented in plural forms preceded by the gender-neutral determiner les, as illustrated in (4).

(4) Person noun: père 'father'

Les pères sont très___ 'The fathers are very___'

We selected 23 adjectives that had been generated by at least two participants (range: 2 -13) (a total of 168 adjectives had been generated). These 23 adjectives represented 20% all responses.

Adjective rating. The procedure was similar to that described in Experiment 1.

Participants were presented with the 23 adjectives one by one in random order, but unlike in Experiment 1 where a Likert scale will be used, here they were asked to indicate on a response slider to what extent they thought the adjectives described a masculine or feminine characteristic.

There were two versions of slider, depending on whether the left and right endpoints were labeled Masculine ('Masculine') and Féminine ('Feminine'), respectively, or the reverse. The initial position of the indicator was placed at the midpoint of the slider, labeled as Neutre ('Neutral'). The slider version was counterbalanced across participants. Like in Experiment 1, adjectives with gender inflection, i.e. adjectives with different forms for masculine and feminine gender agreement, were presented in both forms, while those having a single form for masculine and feminine gender were shown in their unique form. Instructions on how to use the slider were shown to participants at the beginning of the test. The test ended with demographic questions about participants' sex, age, native language, and foreign language experience.

Participants

Using Foulefactory, we recruited 144 native French speakers (73 women and 71 men), aged between 19 and 68 y (M = 41, SD = 12.3), for the adjective generation task, and 80 different native French speakers (44 women and 36 men), aged between 19 and 69 y (M = 41, SD = 12), for the adjective rating task.

Object noun condition

The stimuli used here were different from that for Experiment 1. However, like in Experiment 1, this condition consisted of two tasks: adjective generation and adjective rating.

Materials

Twelve pairs of semantically related French nouns referring to objects were used as items (see Appendix B4). Within each pair, the nouns are semantically related, but have opposite grammatical gender (i.e. masculine vs. feminine). For example, table 'table' and bureau 'desk' are close in denotation, with the former being grammatically feminine and the latter masculine.

Items were divided into two lists of 12, each list comprising 6 masculine and 6 feminine nouns, and the two nouns of each pair were assigned to separate lists.

Procedure

Adjective generation. The procedure was different from that of Experiment 1, as there was a pretest before the adjective generation task, and for this task, the noun items were not presented in a sentence. However, like in Experiment 1, the nouns were shown with a preceding gender-marking determiner.

Participants first went through a pretest on their knowledge about 'adjectives'. They read a sentence and answered how many adjectives were present in the sentence. They then received either positive or negative feedback depending on their response. As part of the negative feedback, the correct answer was given and the sentence was shown again to them with all adjectives in the sentence being highlighted. Regardless of their response, they were able to move to the main test.

After the pretest, participants were shown 12 nouns, one at a time, and asked to generate three adjectives to describe the object denoted by it. They were randomly assigned to either list of 12 nouns; hence they saw only one noun of each pair. Thus, in this condition, noun gender was a within-subject factor. Within each list, the nouns were shown in random order one by one.

All nouns were presented with a preceding gender-marking article le (for masculine nouns) or la (for feminine nouns). At the beginning of each trial, participants were told that answers other than adjectives would not be accepted. The test ended with two demographic questions about participants' age and sex.

We selected 19 adjectives as stimuli for the next rating test. They were the most common adjectives (range: 5 -13 times) provided for each noun (280 adjectives had been generated in total). Again, these 19 adjectives represented 38% of all responses.

Adjective rating. The procedure for this task was similar to the description of Experiment 1, except that a response slider, instead of Likert scale, was used.

Another group of participants were shown the 19 adjectives one at a time in random order, and asked to rate on a response slider to what extent the adjectives describe characteristics related to men or to women. As in the person noun condition, there were two versions of the response slider and the slider version was counterbalanced across participants. Again, adjectives that have gender inflection were presented in both forms while those having a single form for masculine and feminine gender were shown in their unique form. The test ended with two demographic questions about participants' sex and age.

Participants

Using the crowdsourcing platform Foulefactory, we recruited 37 native French speakers (10 men and 27 women), aged between 28 and 67 y (M = 47, SD = 12), for the adjective generation task, and 35 different native French speakers (12 men and 23 women), aged between 58 23 and 64 y (M = 44, SD = 11.3) for the adjective rating task.

Results

A plot of FQA as a function of grammatical gender is shown in Figure 1. We performed the same analyses as planned for Experiment 1, except that the model did not contain a by-participants random slopes for gender in the person condition (as participants only saw one noun). The mean posterior value for the effect of gender on object nouns was 0.07 (CI: [-0.54, 0.68], P(β>0) = 0.60). As a comparison, the mean posterior value for the interaction between noun gender and noun type was 1.11 (CI: [0.20, 2.0], P(β>0) = 0.990). Comparing models with and without an effect of gender on object nouns, the Bayes factor in favor of the null hypothesis was 10.0. This value clearly is in favor of the null hypothesis, yet the discrepancies between the object and noun conditions and the small proportion of adjectives for which a rating was actually elicited cast doubt on the reliability of this result and call for a proper experiment with a cleaner design and higher sample size. Our Experiment 1 will address both problems (by testing more participants and introducing the intensifier très, which limits the class of possible adjectives, we should see less unique adjectives)

Pilot 2

This pilot is similar to Experiment 2 in terms of its cross-linguistic approach (French-German) and experimental procedure.

Methods

The stimuli used in this pilot were different from that for Experiment 2. However, similar to Experiment 2, it consisted in two tasks: adjective generation and adjective rating.

Materials

Twenty-four nouns spanning various categories, including settings (e.g. bridge, mountain), objects (e.g. key, arrow), animals whose biological sex is not obvious (e.g. mosquito, snake), and abstract concepts (e.g. thought, need) were selected as stimuli (see Appendix B5).

Half of these nouns were grammatically masculine in French and feminine in German, and the other half were grammatically feminine in French and masculine in German. One word, "rain", was included in the French test but not in the German one since it does not have a plural form in German.

Procedure

Adjective generation. The procedure was similar to that for Experiment 2, except in the following two aspects. First, here each participant only saw one noun, and the nouns were presented in plural forms. Thus, French nouns were preceded by the gender-neutral determiner les, and German nouns were not preceded by any determiner. Next, the adverb "very" was not present in the carrier sentences for the two language groups. See the example for bridge below in French (5a) and German (5b). For the following rating test, we selected 100 French adjectives that had been generated by at least two participants (range: 2 -88) (except the word diluvien "diluvian" which had been generated only once), and 19 German adjectives adjectives that had been used by at least two participants (range: 2 -7). (Three hundred French adjectives and 95 German adjectives had been generated in total). The 100 French and 19 German adjectives represented 73% and 51% of all responses of the two groups, respectively.

Adjective rating. The procedure was similar to that of Experiment 2, except that here a response slider was used instead of a Likert scale. For the French group, the set of 100 French adjectives was randomly divided into four lists of 25. French participants were randomly assigned to one list, the items of which were presented in random order, one at a time. For the German group, participants were presented with all 19 adjectives, one at a time, in random order.

As described in Experiment 2, French adjectives with gender inflection, i.e. having different forms for masculine and feminine gender agreement, were presented in both forms, while those having a single form for masculine and feminine gender were shown in their unique form. Unlike in French, German adjectives do not have gender inflected suffixes, and thus all items in German were displayed in their unique form. Participants were asked to indicate on a response slider to what extent they thought the adjectives described a masculine or feminine characteristic. There were two versions of slider, depending on whether the left and right endpoints were labeled 'Masculine' (French: Masculine; German: maskuline) and 'Feminine' (French: Féminine; German: feminine), respectively, or the reverse. The initial position of the indicator was placed at the midpoint of the slider, labeled as 'Neutral' (French: Neutre; German: neutrale). The slider version was counterbalanced across participants for each language group. The test ended with demographic questions about participants' sex, age, native language, and foreign language experience.

Participants

Using Foulefactory, we recruited 347 native French speakers (147 men and 200 women), aged between 21 and 69 y (M = 40, SD = 11), for the French adjective generation task, and 128 native French speakers (58 men and 70 women), aged between 19 and 68 y (M= 42, SD = 11.5), for the corresponding adjective rating task. None of them had participated in Pilot 1.

Using Prolific, we recruited 63 native German speakers (32 men and 31 women), aged between 18 and 60 y (M = 30, SD = 10.3), for the German adjective generation task, and 49 native German speakers (25 men and 24 women), aged between 20 and 58 y (M = 31, SD = 10.1), for the corresponding adjective rating task.

Results

A plot of FQA as a function of grammatical gender is shown in Figure 2. We ran the same analysis as planned for Experiment 2, except that there were no byparticipant random effects (since each participant only saw one noun). We found a mean main effect of gender of 0.30 (CI: [-0.32, 0.93], P(β>0) = 0.84). The Bayes factor in favor of the null hypothesis was 5.6. Here again, the Bayes factor is in favor of the null hypothesis, albeit less strongly so compared to Pilot 1. Nevertheless, the imperfect design of this pilot and the imbalance between the number of French and German participants prevent us from accepting the null hypothesis on the basis of this value alone. Only if the proposed Experiment 2 also returns a high Bayes factor (despite being more biased towards a positive result), would we feel confident about this null result.

Introduction

Languages belonging to various language families have sex-based grammatical gender systems [START_REF] Corbett | Gender[END_REF][START_REF] Gygax | A Language Index of Grammatical Gender Dimensions to Study the Impact of Grammatical Gender on the Way We Perceive Women and Men[END_REF]. In these languages, each noun has either masculine or feminine (or, in some languages, neutral) gender, triggering agreement in words such as articles, adjectives, and pronouns. When referring to groups of humans, the masculine and feminine plural genders are used asymmetrically. That is, masculine plural forms are typically used to refer to: 1/ groups of men only, 2/ groups of men and women, and 3/ groups for whom the gender of the referents is unknown. In the latter two cases the masculine gender has a generic meaning. Feminine plural forms, by contrast, can only be used to refer to groups unambiguously and exclusively composed of women.

An example from French is shown in (6). As the subject is presented in a masculine plural form (6a), the sentence can be interpreted in three ways: 1/ male cashiers are on strike; 2/ male and female cashiers are on strike; 3/ cashiers whose gender is unknown are on strike.

However, if presented in the feminine form (6b), it unambiguously indicates that only female cashiers are on strike.

(6) a.

Les caissiers sont en grève.

'The cashiersmasc are on strike.'

b.

Les caissières sont en grève.

'The cashiersfem are on strike.'

The asymmetric roles of the masculine and feminine forms have intersected with heated social debates about gender equality in France and other countries [START_REF] Bodine | Androcentrism in prescriptive grammar: Singular 'they', sex-indefinite 'he', and 'he or she'1[END_REF][START_REF] Elmiger | La féminisation de la langue en français et en allemand: Querelle entre spécialistes et réception par le grand public[END_REF], as this asymmetry in language might reproduce and perpetuate an unequal social status between men and women [START_REF] Menegatti | Gender bias and sexism in language[END_REF]; see also [START_REF] Ng | Language-based discrimination: Blatant and subtle forms[END_REF]. According to one view, the default for masculine forms to represent a mixture of both genders leaves women underrepresented in language and hence underrepresented in the mind. The idea is that in seeing or hearing the masculine form, people are less likely to think of women, which in turn affects the way that women's roles in society are mentally represented. Proponents of this view thus argue for the replacement of the generic use of the masculine by alternative, gender-fair, linguistic forms in order to increase the visibility of females in language, and consequentlyby hypothesis in people's mental representations (for a review, see [START_REF] Sczesny | Can gender-fair language reduce gender stereotyping and discrimination[END_REF].

There are several gender-fair alternatives to the generic masculine form [START_REF] Abbou | Double gender marking in French: A linguistic practice of antisexism[END_REF].

One common one is a "double-gender" form, illustrated in ( 7).

(7) Les caissiers et caissières sont en grève.

'The cashiersmasc and cashiersfem are on strike'.

Another type of alternative is limited to written language only. It consists of the use of a contracted form, for instance by means of parentheses (les caissiers(ères)) or a slash (les caissiers/ères). In French, a more radical innovation in this area was instigated in 2015 by the Haut Conseil à l'Egalité entre les femmes et les hommes ('High Council for Equality between women and men'), namely a contracted form featuring a middot, as shown in (8).

(8) Les caissierères sont en grève.

'The cashiersmasc.fem are on strike'.

This form is largely known as écriture inclusive ('inclusive writing'), but here we will use the term "middot form", as écriture inclusive is really an umbrella term for multiple strategies against gender-stereotyped communication (see, for instance, the Manuel d'écriture inclusive by the French communication agency Mots-Clés6 ).

Replacing the generic masculine gender with an innovative and inclusive language form is not restricted to French. For instance, German has seen the introduction of gender-neutral nominalized adjectives and participles, e.g. die Studierenden 'the students' (cf. studieren 'to study') [START_REF] Sato | Altering male-dominant representations: A study on nominalized adjectives and participles in first and second language German[END_REF], as well as that of a word-internal capital 'I', as in LeserInnen 'readersmasc-fem' (cf. Leser 'readersmasc and Leserinnen 'readersfem'; note that all German nouns are spelled with an initial capital). The latter is a spelling innovation that to some extent resembles the French middot.

A possible skeptical position concerning the use of gender-fair alternatives to the masculine form argues that linguistic forms have little influence on how people think about gender roles. According to this view, the generic use of the masculine gender does not bias people's mental representation against women and hence it is unnecessary to use a longer double-gender or an unconventional, deliberately invented form. In France, stronger forms of skepticism are targeted specifically towards the middot form, which is particularly controversial, including among linguists. 7 This form is argued to damage orthography, creating confusion and obstacles in learning to read and write. In its solemn declaration, L'Académie Française admonished French society for the idea of "inclusive writing" (meant is the middot form),

warning people about its potential to estrange future generations from France's written heritage, undermine the status of French as a world language, and even put French in mortal danger. 8Accordingly, in 2017 the prime minister recommended not to use it in official texts.9 Going one step further, a number of parliamentarians proposed a bill in 2021, aiming to prohibit and penalize the use of the middot form in public administrations and organizations in charge of public services,10 and shortly after that, the minister of National Education ordered that it not be taught in schools.11 Despite these governmental restrictions, the middot form has become more and more widespread over the years. For instance, it appears in most Parisian universities'

brochures for some of their 2019-2020 undergraduate programs [START_REF] Burnett | Political dimensions of écriture inclusive in Parisian universities[END_REF].

Societal debates notoriously take place without reference to empirical evidence. Yet, there is a growing body of experimental work assessing the interpretation of both the masculine generic form and gender-fair alternatives in languages such as English, French and German (for a review, see [START_REF] Menegatti | Gender bias and sexism in language[END_REF]. Below, we will first review this research and then introduce our approach to addressing some outstanding questions in the current study.

Previous research

Previous studies on the interpretation of various linguistic forms have employed a variety of paradigms, with dependent measures such as sentence reading time, sentence plausibility judgment, proportion of women estimated to be present in a group of people described in a short text, and proportion of favorite women mentioned for a given profession. With regards to English, a so-called natural gender language (i.e. a language that marks gender on personal pronouns only), the generic singular pronoun he was found to favor the presence of men in people's mental representations compared to singular they and the alternative he/she (Gastil, 77 1990;[START_REF] Hamilton | Using masculine generics: Does generic he increase male bias in the user's imagery?[END_REF][START_REF] Martyna | What does 'he'mean? Use of the generic masculine[END_REF]. As for the masculine plural form of nouns, several studies have provided evidence that it likewise disfavors the presence of women in mental representations [START_REF] Brauer | Un ministre peut-il tomber enceinte? L'impact du générique masculin sur les représentations mentales[END_REF][START_REF] Braun | Können Geophysiker Frauen sein? Generische Personenbezeichnungen im Deutschen[END_REF][START_REF] Gabriel | Exchanging the generic masculine for gender-balanced forms-The impact of context valence[END_REF]Gygax et al., 2008[START_REF] Gygax | The masculine form and its competing interpretations in French: When linking grammatically masculine role names to female referents is difficult[END_REF]Gygax & Gabriel, 2008;Horvath et al., 2016;[START_REF] Irmen | What's in a (role) name? Formal and conceptual aspects of comprehending personal nouns[END_REF][START_REF] Irmen | Gender markedness of language: The impact of grammatical and nonlinguistic information on the mental representation of person information[END_REF][START_REF] Kollmayer | Breaking away from the male stereotype of a specialist: Gendered language affects performance in a thinking task[END_REF]Stahlberg et al., 2001). Most of them manipulated the gender stereotype of the nountypically a role name (e.g. golfer, cashier, or spectator) [START_REF] Brauer | Un ministre peut-il tomber enceinte? L'impact du générique masculin sur les représentations mentales[END_REF][START_REF] Braun | Können Geophysiker Frauen sein? Generische Personenbezeichnungen im Deutschen[END_REF]Gygax et al., 2008[START_REF] Gygax | The masculine form and its competing interpretations in French: When linking grammatically masculine role names to female referents is difficult[END_REF]Gygax & Gabriel, 2008;Horvath et al., 2016;[START_REF] Irmen | What's in a (role) name? Formal and conceptual aspects of comprehending personal nouns[END_REF][START_REF] Irmen | Gender markedness of language: The impact of grammatical and nonlinguistic information on the mental representation of person information[END_REF]. As such stereotypes are activated during reading [START_REF] Banaji | Automatic stereotyping[END_REF][START_REF] Cacciari | Further evidence of gender stereotype priming in language: Semantic facilitation and inhibition in Italian role nouns[END_REF][START_REF] Carreiras | The use of stereotypical gender information in constructing a mental model: Evidence from English and Spanish[END_REF][START_REF] Garnham | Are inferences from stereotyped role names to characters' gender made elaboratively?[END_REF]Gygax & Gabriel, 2008;[START_REF] Kennison | Comprehending Pronouns: A Role for Word-Specific Gender Stereotype Information[END_REF][START_REF] Reynolds | Evidence of immediate activation of gender information from a social role name[END_REF], the genericas opposed to the specific -interpretation of the masculine gender should be especially plausible for female-stereotyped groups. Yet, even for those groups the results revealed male biases. For instance, Gygax et al. (2008) presented French and German participants with two sentences. The first one named a group of professionals in the masculine plural form (e.g. les espions 'the spiesmasc'); the second sentence provided explicit gender information about one or more of the people in the group, and participants had to decide whether it was a sensible continuation of the first one. The authors compared three types of gender-stereotyped professions, chosen from a norming study they had run previously [START_REF] Gabriel | Au pairs are rarely male: Norms on the gender perception of role names across English, French, and German[END_REF]: masculine (e.g. spies), feminine (e.g. beauticians) or neutral (e.g. singers). Results showed that more positive responses were given when the second sentence explicitly referred to men rather than to women, regardless of the profession's stereotype. Thus, French and German speakers were more likely to match professionals presented in a masculine plural form with men than with women, even for femalestereotyped professions. (The experiment was also run in English, which does not have grammatically gendered nouns. English participants did show an effect of gender stereotype, such that continuation sentences referring to women or to men were deemed more likely for female-or male-stereotyped professions, respectively). [START_REF] Gygax | The masculine form and its competing interpretations in French: When linking grammatically masculine role names to female referents is difficult[END_REF] additionally found that this biased interpretation of masculine generics could be reduced but not suppressed if participants were explicitly reminded of the generic meaning of masculine forms.

Other studies have compared masculine plurals with gender-fair alternatives [START_REF] Brauer | Un ministre peut-il tomber enceinte? L'impact du générique masculin sur les représentations mentales[END_REF][START_REF] Braun | Können Geophysiker Frauen sein? Generische Personenbezeichnungen im Deutschen[END_REF][START_REF] Gabriel | Exchanging the generic masculine for gender-balanced forms-The impact of context valence[END_REF]Gygax & Gabriel, 2008;Horvath et al., 2016;[START_REF] Kollmayer | Breaking away from the male stereotype of a specialist: Gendered language affects performance in a thinking task[END_REF][START_REF] Sato | Altering male-dominant representations: A study on nominalized adjectives and participles in first and second language German[END_REF]Stahlberg et al., 2001;Stahlberg & Sczesny, 2001). Crucially, double-gender forms andin Germanthe innovative capital-I and nominalized forms typically yield a stronger representation of women than masculine forms.

Only a few studies have examined whether this effect of grammatical gender is modulated by stereotype, with mixed results: [START_REF] Braun | Können Geophysiker Frauen sein? Generische Personenbezeichnungen im Deutschen[END_REF] presented German participants with a short text about an annual meeting of a professional group, and asked them a few hours later to estimate the percentage of women present in the group. They found that compared to the masculine form, the double-gender form yielded higher estimated percentages of women for male-but not for female-stereotyped professional groups. Applying the same paradigm to French, however, [START_REF] Brauer | Un ministre peut-il tomber enceinte? L'impact du générique masculin sur les représentations mentales[END_REF] observed a global increase in estimated percentage of women when a double-gender form was presented, relative to when a masculine form was displayed, but this effect was not modulated by the gender stereotype.

Finally, there have been some empirical studies on the potential difference between double-gender and innovative gender-fair forms. For German, Stahlberg et al. (2001) asked participants to name famous people in a given category (e.g. singers or politicians). They found that the use of the capital-I form in the question yielded higher proportions of women than that of a double-gender form (the latter yielding no higher proportion of women than the masculine forma rare result). In Stahlberg & Sczesny (2001), participants were presented with the written name of a professional category, followed by a picture of a famous person; their task was to indicate whether the person belonged to the category. For female pictures, reaction times were faster when the name of the category was written in the capital-I form compared to the doublegender form. (Reaction times were slowest for the masculine gender condition.)

Concerning the effect of innovative forms, two more studies are worth mentioning. Both deal with Swedish, a largely non-gendered language but which, like English, has gender marking on personal pronouns. Interestingly, Sweden has introduced a gender-neutral pronoun, hen, complementing han 'he' and hon 'she'. Following a few years of debate, hen was officially adopted in 2015, quickly reaching widespread adherence and use [START_REF] Gustafsson Sendén | Introducing a gender-neutral pronoun in a natural gender language: The influence of time on attitudes and behavior[END_REF]. As shown by [START_REF] Tavits | Language influences mass opinion toward gender and LGBT equality[END_REF] and [START_REF] Lindqvist | Reducing a male bias in language? Establishing the efficiency of three different gender-fair language strategies[END_REF], hen boosts the presence of women in mental representations. For instance, participants in Lindqvist et al., (2019) read a job advertisement for a profession that according to official Swedish statistics is gender-balanced, followed by the description of an applicant. They then had to choose a picture of either a man or a woman, indicating who they thought the applicant was. When the applicant was referred to by means of a non-gendered noun (den sökande 'the applicant') the results showed a male bias; that is, a picture of a man was chosen more than 50%. By contrast, there was no such bias when the applicant was referred to by means of the paired pronouns han/hon 'he/she' or the gender-neutral pronoun hen, both yielding about 50% choices of a picture of a man.

This last study is important for another reason: To the best of our knowledge it is the only one with a clear quantitative inference concerning the presence or absence of a bias induced by a given linguistic form in mental representations. Indeed, as participants made a forced choice 80 between a male and a female applicant to a gender-neutral job, the data from each condition could be compared not only to that of the other conditions but also to the objective real-world baseline chance level of 50%. Sweden fares particularly well on closing the gender-equality gap (according to the 2020 Global Gender Gap Report of the World Economic Forum, it is ranked 4 th ), which makes the presence of the male bias when a neutral, non-gendered, noun is used particularly striking. (Note, though, that their experiment tested only a single profession.)

In summary, previous research with gendered languages such as French and German has shown that compared to the masculine plural form, the double-gender and innovative forms boost the presence of women in mental representations. Whether the effect of linguistic form is modulated by stereotype, though, is largely an open question. Furthermore, while in German there is a difference between double-gender forms and the innovative capital-I, with the latter yielding the largest difference compared to the masculine form, no research has yet examined the effect of the middot writing form in French, and its potential difference in comparison with a double-gender form. Finally, the question of whether in these languages a given linguistic form induces mental representations that consistently reflect the proportions of men and womenreal or perceivedin specific societal groups or in the society as a whole is yet unanswered. That is, establishing that the presence of women in mental representations differs depending on linguistic form is one thing; a quantified comparison with a benchmark (i.e. census data or normed estimates of real-world gender ratios) would additionally allow one to establish which linguistic formif anyinduces consistent mental representations, and to estimate the size of the bias (male-or female-oriented) induced by the other forms.

Current study

In order to shed light on the three open questions mentioned above, we conduct two on-line experiments on the mental representation of gender in text-based inferences in French. We compare the masculine, double-gender, and middot plural forms. Focusing on gender ratios in professional groups, we consider both gender-neutral professions (Experiment 1) and genderstereotyped ones (Experiment 2). Importantly, we use a ratio estimation task, which allows us to compare our participants' responses to independently normed estimates of the proportion of men and women in the relevant professions [START_REF] Misersky | Norms on the gender perception of role nouns in Czech, English, French, German, Italian, Norwegian, and Slovak[END_REF], Comparison to such a benchmark is of critical importance to the question whether a given linguistic form induces a bias in mental representations.

Our experimental paradigm is an adapted version of the one used by [START_REF] Braun | Können Geophysiker Frauen sein? Generische Personenbezeichnungen im Deutschen[END_REF] and [START_REF] Brauer | Un ministre peut-il tomber enceinte? L'impact du générique masculin sur les représentations mentales[END_REF], in which participants read a short text on a professional gathering and are asked to estimate the percentage of women present at the gathering. Our most important modifications are that we test a variety of professions, such as to ensure that any observed effect generalizes across professions, and that, for practical reasons, we ask participants to provide their estimate immediately after having read the text rather than a few hours later. Additionally, we control for a possible effect of question framing by asking participants to estimate the percentages of men and women on a response slider, counterbalancing the order of appearance of the words 'men' and 'women' and the corresponding slider layout. We also use a shorter text, with two instead of four occurrences of the crucial piece of information. Like in these previous studies, though, we test participants on a single trial, since exposure to multiple trials might make them become aware of the experimental manipulations and develop a response strategy. Lastly, the professions are chosen from the French part of a norming study in which native speakers estimated the proportions of men and women in a great many professions [START_REF] Misersky | Norms on the gender perception of role nouns in Czech, English, French, German, Italian, Norwegian, and Slovak[END_REF].

As in this norming study the influence of linguistic form was controlled at best (the endpoints of the rating scale showed the masculine and feminine forms, respectively, and the direction of the rating scale was counterbalanced across participants), these same norms also serve as the benchmark against which we compare our participants' estimates. (We acknowledge the fact that Misersky et al. collected their French data in Switzerland, while we test participants in France.

Yet, this difference is unlikely to impact the benchmark's validity, given that high correlations were obtained across all seven languages investigated in the norming study (the six others were English (UK), German, Norwegian, Italian, Czech, and Slovak).

Experiment 1

In this experiment, we compare three plural forms in French that can be used to refer to a group of mixed genders: the masculine, double-gender and middot forms. Importantly, we focus on professions with a perceived neutral stereotype, which should encourage participants to interpret the masculine plural form as generic, referring to both men and women, and hence potentially treat it on a par with the double-gender and middot forms. By comparing the masculine form to these alternatives, we test whether differences in linguistic form alter language users' inferences about gender ratios in the described scenarios. Specifically, we examine whether due to the ambiguity of the masculine form and its lack of explicit inclusion of female referents, this form disfavors women in mental representations relative to the other two forms. If this were the case, we should observe lower estimates of %-women in response to the masculine compared to the double-gender and middot forms. The latter two are both gender-fair but differ in two respects:

First, the middot is a more recent and more militant form than the double-gender, and second, the double-gender can be read aloud straightforwardly while the middot is essentially a spelling convention. We might therefore observe differential effects of these gender-fair forms, although it is unclear which form would be expected to boost the mental representation of women more.

Finally, we examine for each form the extent to which the mean estimate of %-women deviates from people's perception of real-world gender ratios in the professions at hand. We expect that in this respect, the double-gender and middot forms fare better (i.e., closer to a consistent representation) than the masculine form.

Unless otherwise specified, all aspects of the stimuli, procedure and analyses were preregistered (10.17605/OSF.IO/K649W).

Method

Stimuli

We selected six neutral-stereotyped professions whose French names have grammatical gender marking from the French part of [START_REF] Misersky | Norms on the gender perception of role nouns in Czech, English, French, German, Italian, Norwegian, and Slovak[END_REF]'s norming study. With one exception (employé de banque 'bank employee'), the masculine and feminine forms differ not only orthographically but also phonologically (The pattern of results was the same when we removed the trials with this noun from the analyses). The estimated proportions of women in these professions are between .47 and .51 (M = .49, SD = .01) (see Appendix A).

We constructed the short passage shown in (9), describing a fictitious scenario where an annual gathering of some professionals took place. The profession name appeared twice in the text and no referential pronoun was used.

(9)

Le rassemblement régional des PROFESSION NAME a eu lieu cette semaine à Amiens. La localisation centrale de cette ville a été particulièrement appréciée.

Les PROFESSION NAME ont aussi adoré l'apéro offert à l'hôtel de ville le premier jour.

'The regional gathering of PROFESSION NAME took place this week in Amiens.

The central location of this city was particularly appreciated. The PROFESSION NAME also loved the aperitif offered at City Hall on the first day.'

The words régional and Amiens were replaced with européen and Francfort respectively for three professions, i.e. mathématicien 'mathematician', douanier 'customs officer' and astronaute 'astronaut', for it would be more plausible for these professionals to have a Europewide gathering in a more internationally-oriented city than a regional one in a provincial city.

We constructed three versions of this passage, varying the linguistic form of the profession name (masculine vs. double-gender vs. middot plural), as exemplified for one of the professions in ( 10). We also constructed two multiple-choice questions about the text, to serve as attention checks:

(11) Attention check questions a. Qu'est-ce qui a été apprécié à propos d'Amiens ?

versions of it, depending on the order of the words for men and women in the sentence. One At the end of the survey, participants were asked to fill in information about their native language, country of residence, gender, and age.

Participants

We recruited 195 participants. The data from 42 of them were removed from the analysis for the following reasons: one participated in a related experiment not reported on here, one did not complete the survey, 17 responded incorrectly at one or both attention check questions, and 23 did not satisfy all of our recruitment criteria (three were non-native speakers, two did not live in France, and among the ones recruited on Foulefactory, 18 reported an age outside of the requested range). For the 41 participants who took the survey more than once, we only kept their first response.

The data analysis thus included 153 participants (67 women and 86 men). They were native French speakers living in France, aged between 22 and 39 years (M = 30, SD = 2.7).

Three of them were recruited on the crowd-sourcing platform Clickworker (https://www.clickworker.com/), and all others on Foulefactory (https://www.foulefactory.com), the preregistered recruitment platform, has a large number of French workers, but presents two disadvantages compared to Clickworker. First, it only offers pre-specified age ranges, although a customized age range can be obtained for an extra 500€. Here, we chose the pre-specified range 25-34. Second, it lacks a good screening function: workers can do a task more than once, leading to considerable data loss. We therefore completed our sample by collecting the last three datapoints on Clickworker, with a customary age range of 20-40 years).

Their random assignment to one of six conditions (three linguistic forms x two slider layouts) yielded a mean number of 25 participants (min = 24, max = 26) per condition.

Results and Discussion

Boxplots of the estimated percentages of women as a function of linguistic form are shown in Figure 3. These data were fit with a linear mixed-effects model by using the lme4 package [START_REF] Bates | Fitting Linear Mixed-Effects Models Using lme4[END_REF] in the programming software R (R Core Team, 2020) and Rstudio (RStudio Team, 2020) Statistical significance was assessed by means of the Anova function in the Car package [START_REF] Fox | An {R} Companion to Applied Regression (Third)[END_REF], and effect sizes were computed using the eta_squared function in the effectsize package [START_REF] Ben-Shachar | Compute and interpret indices of effect size[END_REF]. Linguistic form was contrast-coded and set as fixed effect; a random intercept was added for Profession. As we collected only one datapoint per person, we did not include a random factor for Participant. Note that this model differs from the one we preregistered in that it does not contain fixed factors for Slider version and its interaction with Linguistic form. As neither in this nor in the next experiment this counterbalancing factor or any of its interactions affected the estimated %-women, and as omitting these terms did not change any of the results, we report the simpler models in both experiments for the reader's convenience. (The only other studies we know of that looked at order effects are the norming studies by [START_REF] Gabriel | Au pairs are rarely male: Norms on the gender perception of role names across English, French, and German[END_REF] and [START_REF] Misersky | Norms on the gender perception of role nouns in Czech, English, French, German, Italian, Norwegian, and Slovak[END_REF]. For some languages, these studies reported higher estimates for women when the question framing and response slider showed a women-men order, but there was no such effect for French.)

The results of the mixed-effects model, shown in Table 1, revealed an effect of Linguistic form. Restricted analyses with corrections for multiple comparison (mvt method), carried out with the emmeans package [START_REF] Lenth | emmeans: Estimated Marginal Means, aka Least-Squares Means[END_REF], showed that compared to the masculine plural form, higher estimates of %-women were obtained for the double-gender ( = 9.92, SE = 2.64, t(146) = 3.76, p < .001) and the middot form ( = 9.63, SE = 2.63, t(146) = 3.67, p < .001). By contrast, there was no difference between the double-gender and middot forms (t < 1). To do this, we subtracted the normed %-women from the participant's estimate for each profession and each participant, and constructed intercept-only models with this difference score as dependent measure and a random intercept for Profession. In these models, a positive estimate for the intercept would thus indicate an overestimation of the presence of women compared to the benchmark and a negative estimate Furthermore, given the lack of a difference between the double-gender and middot forms in Experiment 1, we expect these two forms likewise to yield similar results. Finally, as in Experiment 1, we also examine to what extent participants' estimates in the experimental context reflect people's perceived gender ratios in the real world, by comparing the results to the norming data of [START_REF] Misersky | Norms on the gender perception of role nouns in Czech, English, French, German, Italian, Norwegian, and Slovak[END_REF]. If the double-gender and middot forms yield more consistent mental representations, they should fare better than the masculine form.

Unless otherwise specified, all aspects of the stimuli, procedure and analyses were preregistered on OSF (10.17605/OSF.IO/FCEWA).

Method

Stimuli

We selected six male-stereotyped professions (e.g. électricien 'electricianmasc'électricienne 'electricianfem') and six female-stereotyped ones (e.g., caissier 'cashiermasc'caissière 'cashierfem') from the same norming study as used in Experiment 1 [START_REF] Misersky | Norms on the gender perception of role nouns in Czech, English, French, German, Italian, Norwegian, and Slovak[END_REF]. For all professions, the feminine plural form of their French name differs from the masculine one not only orthographically but also phonologically. The mean estimated proportions of men or of women, respectively, were above .70 (male-stereotyped: Mmen = .81 SD = .03; female-stereotyped: Mwomen = .78, SD = .05; t(10) = 1.12, p = 0.3). The 12 professions, together with the estimates of %-women in those professionsaccording to Misersky et al.'s norming studyare shown in Appendix A.

We used the same testing passage in the same three versions as in Experiment 1, shown in ( 9) and (10) above. showed that compared to the masculine form, higher estimates of %-women were obtained for the double-gender form ( = 7.16, SE = 2.55, t(290) = 2.81, p < .02) and the middot form ( = 9.44, SE = 2.57, t(290) = 3.67, p < .001), while there was no difference between the latter two (t < 1).

In order to compare the results of this experiment to the ones by [START_REF] Braun | Können Geophysiker Frauen sein? Generische Personenbezeichnungen im Deutschen[END_REF] and [START_REF] Brauer | Un ministre peut-il tomber enceinte? L'impact du générique masculin sur les représentations mentales[END_REF], who tested only masculine and double gender forms across both stereotypes, we also performed the same regression analysis without the data for the middot form.

The results of this analysis, which was not preregistered, did reveal an interaction of small effect size ( = 2.45, SE = 1.27, t = 1.98, χ 2 = 3.92, p < .05, partial  2 = 0.02), such that for malestereotyped professions, the double form yielded higher estimates of %-women than the masculine form ( = 12.0, SE = 3.52, t(194) = 3.42, p < .001), while for the female-stereotyped professions no difference was found between the linguistic forms (t <1).

Finally, following the same procedure as in Experiment 1, we carried out nonpreregistered post-hoc analyses to compare the results to [START_REF] Misersky | Norms on the gender perception of role nouns in Czech, English, French, German, Italian, Norwegian, and Slovak[END_REF] norming data shown in Appendix A. (In two of the models, i.e. male stereotype with double-gender form, and female stereotype with middot form, the random factor was not taken into account by lmerTest because its estimated variance was zero or close to zero.) For the male-stereotyped professions, we found that the double-gender and middot forms yielded an overrepresentation of women (double-gender:  = 19.26, SE = 2.02, t = 9.52, p < .0001; middot:  = 19.18, SE = 3.00, t = 6.40, p < .003), with the masculine form trending in the same direction ( = 7.47, SE = 3.19, t = 2.34, p < .07). For the female-stereotyped professions, conversely, we found that all three forms induced an underrepresentation of women, whichas indicated by the values of the beta coefficientis numerically largest for the masculine and smallest for the middot form (masculine:  = -20.24, SE = 3.63, t = -5.57, p < .003; double-gender:  = -17.89, SE = 2.97, t = -6.02, p < .002; middot:  = -12.39, SE = 2.83, t = -4.37, p < .0001).

These results show that both stereotype and linguistic form affect inferences about gender ratios in male-and female-stereotyped professions. Note that the overall effect of linguistic form was similar to the one observed for neutral-stereotyped professions in the previous experiment:

the double-gender and middot forms yield higher estimates of %-women than the masculine form, and they do so to the same extent. The lack of a global interaction between linguistic form and stereotype is unexpected, since we did observe such an interaction in an almost identical pilot experiment with less participants (N=142); that is, the increase in the estimations with the gender-fair forms was restricted to male-stereotyped professions. Here, we observed the interaction only in a restricted analysis without the data for the middot form. The same interaction pattern was present in the German data of [START_REF] Braun | Können Geophysiker Frauen sein? Generische Personenbezeichnungen im Deutschen[END_REF], but not in the French data of [START_REF] Brauer | Un ministre peut-il tomber enceinte? L'impact du générique masculin sur les représentations mentales[END_REF]. As the effect sizes of the interactions in the present experiment and in our pilot experiment are both small, statistical power might be at issue to explain the overall now-you-see-it-now-you-don't pattern. We return to this point in the General Discussion.

As to the comparison with the norming data, the results suggest that none of the linguistic forms induce a consistent representation of the proportion of women for either male-or femalestereotyped professions. This contrasts with results for neutral-stereotyped professions in Experiment 1, where the gender-fair language forms indeed matched the normed ratios. Table 3 provides an overview of the comparisons with the norming data both for this experiment and the previous one, by showing the models' estimated differences, measured in percentage points, between our participants' estimates and the norms. A positive value indicates a female bias, a negative one a male bias. These data suggest that gender-fair language forms can rectify the male-biased representation induced by the masculine form for neutral-stereotyped professions, while they create a female bias for male-stereotyped professions and fail to correct the male bias for femalestereotyped professions.

General Discussion

In two on-line experiments, we investigated the influence of linguistic form and gender stereotype on the presence of women in mental representations of groups of people. French participants read a short text on a professional gathering and estimated the percentage of women present in the gathering. We deliberately opted for a complete between-participants design in which each participant was tested in a single trial, such as to avoid the emergence of response strategies. In each experiment we compared the masculine formwhich is ambiguous since its interpretation can be both specific (i.e., referring to men only) and generic (i.e., referring to men and women)to two unambiguous alternatives for mixed-sex groups, i.e. double-gender and middot form. In Experiment 1 we tested neutral-stereotyped professions, and in Experiment 2 male-and female-stereotyped ones. In addition, we compared all experimental results to norming data from [START_REF] Misersky | Norms on the gender perception of role nouns in Czech, English, French, German, Italian, Norwegian, and Slovak[END_REF]. These comparisons allowed us to establish for each stereotype which linguistic forms yield a mental representation in accordance with people's perception of gender ratios in the real world and which ones generate a biased representation. Our results can be summarized as follows.

In both experiments we observed lower estimates of %-women for the masculine form than for the double-gender and middot forms. Experiment 2 additionally revealed an effect of stereotype, with lower estimates for male-compared to female-stereotyped professions. This effect interacted with that of linguistic form only in a post-hoc analysis that left out the data for the middot form, showing higher estimates of %-women for male-but not for female-stereotyped professions when the double-gender form was shown. Compared to the norming data, for neutral-stereotyped professions we found a male bias with the masculine form but consistent estimates with the gender-fair forms. However, for male-stereotyped professions, this comparison showed consistent estimates with the masculine form but a female bias with the gender-fair forms, and for female-stereotyped professions it suggested a male bias with all linguistic forms.

As to the relatively increased representation of women induced by the gender-fair plural forms compared to the masculine plural, our results are in accordance with previous studies on both French [START_REF] Brauer | Un ministre peut-il tomber enceinte? L'impact du générique masculin sur les représentations mentales[END_REF]Gygax & Gabriel, 2008) and German [START_REF] Braun | Können Geophysiker Frauen sein? Generische Personenbezeichnungen im Deutschen[END_REF]Stahlberg & Sczesny;2001;Stahlberg et al., 2001;[START_REF] Gabriel | Exchanging the generic masculine for gender-balanced forms-The impact of context valence[END_REF]Horvath et al., 2016;[START_REF] Kollmayer | Breaking away from the male stereotype of a specialist: Gendered language affects performance in a thinking task[END_REF]. Both these languages have an innovative neutralizing form alongside the more conventional double-gender, i.e. middot in French and capital-I in German.

For German, there is evidence that capital-I yields an even higher representation of women than the double-gender form (Stahlberg & Sczesny, 2001, Stahlberg et al. 2001), while for French, no previous research has examined the effect of the middot form. Our study, however, suggests that there is no gradient effect of linguistic form, as we found no difference between the estimates for the double-gender and middot conditions in either experiment. Possibly, the diverging results are due to the fact that in German the innovative form is highly similar to the feminine form in writing and indistinct from it in pronunciation (German, e.g.: LeserInnen versus Leserinnen;

French, e.g.: électriciennes versus électriciennes, but caissierères versus caissières and éboueureuses versus éboueuses). In this respect, we can also recall the case of Swedish, a language that has introduced an innovative, neutral, personal pronoun hen, which complements male han 'he' and female hon 'she'. Hen reached widespread adherence in a few years, before its official adoption in 2015 [START_REF] Gustafsson Sendén | Introducing a gender-neutral pronoun in a natural gender language: The influence of time on attitudes and behavior[END_REF], which contrasts sharply with the situation in France, where the use of middot has remained an ideologically divisive issue. Yet, similar to what we found for French, Lindqvist el al. (2019) observed no difference in responses to the neutral hen compared to the double-gender form hen/hon regarding the presence of women in mental representations. More research, though, is necessary to examine possible differing effects of double-gender and middot forms in French.

There is one caveat to be mentioned concerning the results for the masculine form. Gygax & Gabriel (2008) showed that the interpretation of the masculine plural as specifically referring to men is enhanced when participants have just read short, unrelated, texts containing double-gender forms. (They did not test if using a middot has the same effect, but there is no reason to think it would not.) As participants come to an experiment with all their previous language experience, the co-existence of gender-fair forms and generically intended masculine forms might have made our participants on average less inclined to embrace the generic interpretation than would have been the case before the rise of gender-fair language. Hence, the estimates of %-women in response to the masculine form might have been lower than what we would have seen one or more decades ago. As long as generically intended masculine forms coexist with gender-fair forms, this pragmatic backlash effect is expected to similarly be present in people's text interpretations in real-life situations. For future research, it would be interesting to examine whether participants' use of, familiarity with, or even adherence to gender-fair language affects their interpretation of the masculine plural.

The effect of stereotype has been shown many times [START_REF] Brauer | Un ministre peut-il tomber enceinte? L'impact du générique masculin sur les représentations mentales[END_REF][START_REF] Braun | Können Geophysiker Frauen sein? Generische Personenbezeichnungen im Deutschen[END_REF]Gygax et al., 2008[START_REF] Gygax | The masculine form and its competing interpretations in French: When linking grammatically masculine role names to female referents is difficult[END_REF]Gygax & Gabriel, 2008;Horvath et al., 2016;[START_REF] Irmen | What's in a (role) name? Formal and conceptual aspects of comprehending personal nouns[END_REF][START_REF] Irmen | Gender markedness of language: The impact of grammatical and nonlinguistic information on the mental representation of person information[END_REF]. Given that none of the three linguistic forms imply anything about the gender ratio in groups of mixed gender, it is easy to see why stereotype information influences judgments on this ratio. One might expect, though, that male and female stereotypes have differential effects when one of the gender-fair forms is presented. Specifically, the use of a double-gender or middot form might boost the presence of women in mental representations to a larger extent for male-stereotyped than for female-stereotyped professions. We found only limited evidence for this, despite the clear presence of such an interactionalbeit with a small effect sizein our Pilot 3. Might this latter result have been a strike of luck? In the absence of a tool for computing power in linear mixed-effects models with interactions, this is hard to know.

We present here the results of a pooled analysis, for which we combined the data from Experiment 2 with that of the pilot. (None of the participants in Experiment 2 had participated in the pilot.) The pooled dataset contains a total of 447 participants aged between 20 and 40 (mean = 29.3, SD=5.6), with on average 71 participants per condition (min = 32, max = 42). The same regression model as the one for the analysis of Experiment 2 revealed not only effects of Stereotype and Linguistic form, but also an interaction, as shown in Table 4. The pattern of results of this pooled analysis is identical to that of the pilot analyzed separately: First, the effect of Linguistic form reveals that compared to the masculine form, higher estimates of %-women are obtained for the double-gender form ( = 11.2, SE = 2.19, t(435) = 5.11, p < .0001) and the middot form ( = 11.4, SE = 2.16, t(435) = 5.29, p < .0001), while there is no difference between the latter two (t < 1). Second, restricted analyses of the interaction show that this pattern is most prominent for male-stereotyped professions (masculine vs. double:  = 17.8, SE = 3.05, t( 438 of the interaction is smaller (0.02 vs. 0.05) but the χ 2 statistic is higher (10.6 vs. 6.53). This pooled data analysis, then, adds evidence supporting the hypothesis that gender-fair language forms increase the presence of women in mental representations especially for male-stereotyped professions. Yet, given its small effect size, we conjecture that a large sample size is needed in order to reliably observe the relevant interaction. Recall that the two previous studies that examined the effect of linguistic form across two stereotypes compared the masculine to a double-gender form only [START_REF] Braun | Können Geophysiker Frauen sein? Generische Personenbezeichnungen im Deutschen[END_REF][START_REF] Brauer | Un ministre peut-il tomber enceinte? L'impact du générique masculin sur les représentations mentales[END_REF]. Both adopted in essence the same paradigm as we did, but with just a single profession per stereotype, such that it is unknown whether their findings are generalizable across different professions. For French, [START_REF] Brauer | Un ministre peut-il tomber enceinte? L'impact du générique masculin sur les représentations mentales[END_REF] observed no interaction; with 73 participants, though, their sample size was probably too small. For German, by contrast, [START_REF] Braun | Können Geophysiker Frauen sein? Generische Personenbezeichnungen im Deutschen[END_REF] did report the expected interaction: the double-gender form increased the percentage of estimated women for male-but not for female-stereotyped professional groups. Further research would be welcome to shed more light on the issue of differential effects of various gender-fair language forms depending on the associated gender stereotype. One specific question in this respect concerns a possible difference between the double-gender and middot forms, as suggested by the fact that it is the middot form that prevents a global interaction in Experiment 2. That is, as the middot is still relatively infrequent, its processing might take up resources that would otherwise be allocated to proportions of women below .30 or above .70). For female-stereotyped professions, one may also wonder if putting the feminine form before the masculine, e.g., les caissières et caissiers 'the cashiersfem/masc', would render the presence of women in mental representations more salient, thus yielding more consistent representations. In everyday communication this 'feminine before masculine' presentation is standard in a few cases where a mixed-sex group of people is addressed (e.g., Mesdames et messieurs 'Ladies and gentlemen', and Bonjour à toutes et à tous 'Hello to allfem-masc of you'), but otherwise quite unusual. Previous research suggests that the order of words in a binomial phrase concurs with differential cognitive accessibility and relevance to a context [START_REF] Kesebir | Word Order Denotes Relevance Differences: The Case of Conjoined Phrases With Lexical Gender[END_REF][START_REF] Tachihara | Cognitive accessibility predicts word order of couples' names in English and Japanese[END_REF]. For instance, when asked to name familiar couples, people tended to mention first the person to whom they felt close (thus easier to be brought to mind) [START_REF] Tachihara | Cognitive accessibility predicts word order of couples' names in English and Japanese[END_REF]. [START_REF] Kesebir | Word Order Denotes Relevance Differences: The Case of Conjoined Phrases With Lexical Gender[END_REF] showed when "women" was mentioned before "men" in a binomial phrase, people were more likely to think of women as member of a group of activists, relative to when "women" was mentioned after "men".

Thus, reversing the order might indeed render the presence of women in mental representations more salient. (It's worth noting that the 'masculine before feminine' word order, more than a linguistic convention, maps stereotypical beliefs about the two sexes [START_REF] Hegarty | When gentlemen are first and ladies are last: Effects of gender stereotypes on the order of romantic partners' names[END_REF].

Mentioning women before men may therefore also help fight traditional gender stereotype.)

Finally, we briefly turn to the social impact of gender-fair language. Depending on one's view on gender roles, it might be argued that the mismatches we observed between our experimental results and people's perception of gender ratios in the real worldwith gender-fair language forms resulting in more balanced gender ratios for male-and females-stereotyped professions than those found in the norming data of Miserksy et al. ( 2013)are desirable.

Specifically, the practice of using gender-fair language could weaken stereotypes [START_REF] Chatard | Impact de la féminisation lexicale des professions sur l'auto-efficacité des élèves: Une remise en cause de l'universalisme masculin?[END_REF]Horvath & Sczesny, 2016;Vervecken et al., 2015;Vervecken & Hannover, 2015; but see [START_REF] Merkel | Shielding women against status loss: The masculine form and its alternatives in the Italian language[END_REF], and hence over time, traditionally male-dominated professions might attract more women and female-dominated ones, more men. In other words, the use of gender-fair language could play a normative role in promoting more balanced real-world gender ratios in the long term. In the short run, there may be some side effects from the backlash against the use of gender-fair language. For instance, female job applicants were evaluated less favorably in a hiring process when introduced with feminine job titles than with masculine ones [START_REF] Budziszewska | Backlash over gender-fair language: The impact of feminine job titles on men's and women's perception of women[END_REF][START_REF] Formanowicz | Side effects of gender-fair language: How feminine job titles influence the evaluation of female applicants[END_REF] and professions presented with gender-fair language were estimated to earn lower salaries than with masculine forms (Horvath et al., 2016). (The above-mentioned studies were run with Polish, German and Italian participants. A fourth, smaller-scale, study with French participants did not find any influence of gender-fair language on the evaluation of professions [START_REF] Gygax | Féminisation et lourdeur de texte[END_REF]. As observed by Gustafsson Sendén et al., (2015), people's attitudes toward gender-fair language become positive over time, thus any backlash effects might diminish with more exposure to the presence of gender-fair language forms.

To conclude, we showed that the generic use of the masculine plural and gender-fair alternatives differentially impact how people mentally represent and estimate gender ratios. In addition to adding important data to fuel public debate around gender-fair language, our results also potentially lead to new questions. For example, how do people prioritize consistency of mental representations vs. gender fairness when these come apart in their views about which linguistic forms are most desirable? And how do proponents of gender-fair language weigh the obvious orthographic drawbacks of the middot form against its potential advantage in terms of representational consistency compared to double-gender forms? Whatever the answers to these questions end up being, it is clear that existing and future empirical data should be a driving force in informing the trade-offs that must be considered in arriving at coherent policy decisions.

1994; [START_REF] Saint-Aubin | The influence of word function in the missing-letter effect: Further evidence from French[END_REF][START_REF] Staub | Failure to detect function word repetitions and omissions in reading: Are eye movements to blame[END_REF]. Thus, one might expect for grammatical manipulations on pronouns to have less of an impact than similar manipulations on profession names. In order to test this, we exploit the fact that not all French profession names have different forms for male and female gender. Specifically, we contrast two minimally different scenarios: In one, the profession name has gender marking (e.g., caissier 'cashiermasc'caissière 'cashierfem', used in the examples above) and there is no referential pronoun. In the other one, the profession name has no gender marking (e.g. artiste 'artistmasc/fem') but the grammatical gender information is present on a referential pronoun, i.e. elles 'shepl'. Moreover, we examine more directly to what extent the grammatical gender information is processed, by adding a multiplechoice question to test participants' recall of the crucial word after they have provided their estimate. We expect that if there is a difference, recall will be better when the crucial word is the profession name than when it is the pronoun.

Method

Stimuli

We selected 24 professions, twelve female-stereotyped and twelve male-stereotyped, from the French part of the same norming study [START_REF] Misersky | Norms on the gender perception of role nouns in Czech, English, French, German, Italian, Norwegian, and Slovak[END_REF] as mentioned before. The 12 professions for the noun condition that have varying forms for the masculine and feminine gender (i.e. gender-marked) were the same items as used for Experiment 2. The other 12 professions have a unique form (i.e. not gender-marked) (e.g. male-stereotyped: bagagiste 'portermasc/fem'; female-stereotyped: fleuriste 'floristmasc/fem') and are used in the pronoun condition. All professions were selected from among those with mean estimated proportions of men or of women, respectively, above .70 (male-stereotyped, gender-marked: Mmen = .81 SD for those in the pronoun condition, the three choices were: masculine plural pronoun (ils), feminine plural pronoun (elles) and Je ne sais pas.

Participants

The analysis included 201 (134 women and 67 men) native French speakers living in France, aged between 20 and 40 years (M = 28.2, SD = 6.2), who participated on the crowdsourcing platform Clickworker. Their random assignment to one of eight conditions (two gender stereotypes, two word types, and two slider layouts) yielded a mean number of participants per condition of 25 (min = 24, max = 26).

The data from an additional 41 participants were removed from analysis for the following reasons: one did not complete the survey, five took the survey for the second time, 17 responded incorrectly at one or both attention check questions, and the remaining ones did not satisfy all of our recruitment criteria (eight were non-native speakers, one did not live in France, and four were younger than 20, and five older than 40).

Results and discussion

Boxplots of the estimated percentages of women as a function of word type and gender stereotype are shown in Figure 5. These data were fit with a linear mixed-effects model by using the lme4 package [START_REF] Bates | Fitting Linear Mixed-Effects Models Using lme4[END_REF] in the programming software R (R Core Team, 2020) and Rstudio (RStudio Team, 2020) Statistical significance was assessed by means of the Anova function in the Car package [START_REF] Fox | An {R} Companion to Applied Regression (Third)[END_REF]. Stereotype (male vs. female) and Word type (nouns vs. pronoun) were contrast-coded and set as fixed effects together with their interaction term. A random intercept was added for Profession. As we collected only one datapoint per person, we did not include a random factor for Participant. Note that this model differs from the one we preregistered in that it does not contain fixed factors for Slider version and its interaction terms. As neither in this nor in the following experiments this counterbalancing factor or any of its interactions affected the estimated %-women, and as omitting these terms did not change any of the results, we report the simpler models throughout the article for the reader's convenience.

The results, shown in Table 5, revealed an effect of Word type, with higher estimates of %-women in the noun compared to the pronoun condition. By contrast, there was no effect of Stereotype nor an interaction. Next, we consider the responses to the memory question. Five participants, all in the pronoun condition, could not choose between the male-or female-inflected forms of the crucial word: they replied that they were unsure. Their responses were coded as incorrect. The mean percentages of gender recall accuracy as a function of word type and stereotype are shown in Figure 6. We fit the data with a logistic mixed-effects model with contrast-coded fixed factors Stereotype, Word type, and their interaction, and with a random intercept for Profession. The results, shown in Table 6, revealed an effect of Word type, as nouns were more likely to be correctly remembered than pronouns. By contrast, there was no effect of Stereotype nor was there an interaction. These results show that when grammatical information is unambiguous, i.e. indicating that a group of professionals consists entirely of women, participants' estimates of the %-women in the group are not influenced by the profession's stereotype. Thus, in this case gender stereotype does not override grammatical gender information, regardless of whether the gender marker appears on the noun or on a referential pronoun. The estimates, however, were not at ceiling (as in theory they should be), and, more importantly, they were lower when the grammatical information was present on a referential pronoun (mean: 74%) than when it was present on the noun (mean: 85%). Furthermore, gender recall of the crucial word was worse for pronouns (mean accuracy: 65%) than for nouns (mean accuracy: 93%), suggesting better processing of nouns than of pronouns, in accordance with previous research on differences between content and function words in reading [START_REF] Healy | Letter detection: A window to unitization and other cognitive processes in reading text[END_REF][START_REF] Saint-Aubin | The influence of word function in the missing-letter effect: Further evidence from French[END_REF][START_REF] Schindler | Error in proofreading: Evidence of syntactic control of letter processing?[END_REF][START_REF] Staub | Failure to detect function word repetitions and omissions in reading: Are eye movements to blame[END_REF].

Although with a single datapoint per participant we did not have sufficient statistical power to directly assess the effect of accuracy in the memory question on the estimate of %women, the data do suggest that incorrect responses to the memory question are associated with lower estimates of %-women, especially for male-stereotyped professions. This can be seen in Table 7, which shows the number of participants and mean estimates of %-women as a function of Word type, Stereotype, and Recall response. Note that on average, estimates of %-women by participants who were correct on the memory question still did not exceed 90%. Various factors might be involved in this lack of ceiling performance: Some of these participants may have taken into consideration persons who were not denoted by the profession names but were present at the gathering (e.g. organizers, hotel staff, or accompanying family members, all of whom might be male). For others, their answer to the memory question might have been a guess which happened to be correct. Or, some might have misinterpreted the response slider when providing their estimate (six of them indeed estimated the % of women to be lower than 50%, ranging from 11%for a female-stereotyped profession!to 43%, with a mean of 27.9%) Last but not least, some might not have paid enough attention to the task.

Results

Boxplots of estimated percentages of women as a function of linguistic form and stereotype are shown in Figure 7. As in Pilot 1, the data were fit with a linear mixed-effects model. The model contained fixed factors for contrast-coded Stereotype, Linguistic form, and their interaction, as well as a random intercept for Profession. The results, shown in Table 8, revealed effects of Stereotype and an interaction. However, only a marginal effect of linguistic form was found.

As found in previous experiments, lower percentages of women were estimated for malestereotyped professions (M = 26.5, SD = 17.3) than for female-stereotyped ones (M = 60.8, SD = 17.5). Conversely, double-gender pronoun (M = 47.3, SD = 21.3) only slightly increased the perceived proportion of women compared to the masculine form (M = 46.1, SD = 27.0). The influence of linguistic form, however, was dependent on stereotype. Restricted analyses with corrections for multiple comparison (mvt method) showed that for male-stereotyped professions, double-gender form increased the representation of women [ = 11.0, SE = 4.13, t(136) = 2.67, p < .01], while for female-stereotyped ones, no difference was found between the two linguistic forms (t < 1, p = 0.82).

Pilot 3

This pilot was included in the submitted manuscript. It is identical to Experiment 2 in the aspects of design, materials, and procedure.

Method

Stimuli

The stimuli were identical to those for Experiment 2.

Procedure

The procedure remained identical to that of Experiment 2 with one exception: the number of datapoints per profession within each group defined by stereotype, linguistic form, and slider direction was more variable.

Participants

Participants were native French speakers living in France (N = 142), 73 women and 69 men, aged between 21 and 40 years (M = 32, SD = 5.2). The mean number of participants per condition was 11 (min = 6, max = 17).

Results

Boxplots of estimated percentages of women as a function of linguistic form and stereotype are shown in Figure 8. Compared to female-stereotyped professions, lower percentage of women was estimated for male-stereotyped ones.

As to the main effect of linguistic form, the pattern of results is consistent with that of Experiment 2 and the pooled analysis described above. Compared to the masculine form, higher estimates of %-women were obtained for the double-gender form ( = 21.1, SE = 4.23, t(136) = 4.98, p < .0001) and the middot form ( = 15.1, SE = 4.0, t(131) = 3.78, p < .001). However, there was no significant difference between the two gender-fair forms ( = -5.94, SE = -4.10, t(135) = -1.45, p > .1).

Concerning the interaction, restricted analyses showed that this pattern is most prominent for male-stereotyped professions (masculine vs. double:  = 29.6, SE = 5.57, t(122) = 5.32, p < .0001; masculine vs. middot:  = 14.0, SE = 5.78, t(127) = 2.43, p < .05; double vs. middot:  = -15.6, SE = -5.69, t(132) = -2.74, p < .02); while for female-stereotyped professions, the

Appendices

Appendix A. French profession names used in Experiments 1, 2, and Pilots 1 (noun condition) and 3, with mean percentages of women as rated by participants in [START_REF] Misersky | Norms on the gender perception of role nouns in Czech, English, French, German, Italian, Norwegian, and Slovak[END_REF].

Stereotype

Introduction

The fields of Science, Technology, Engineering, and Mathematics (STEM) are indisputably male-dominated [START_REF] Shen | Inequality Quantified: Mind the Gender Gap[END_REF]. Despite the implementation of recent compensatory measures in STEM, women are still outnumbered by their male colleagues, especially in senior positions (James et al., 2019). The persistent underrepresentation of women has been attributed to multiple interacting factors, ranging from external barriers such as discriminatory hiring practices against women, to internal factors including gender differences in math abilities, lifestyle, and career choices (see [START_REF] Ceci | Women's underrepresentation in science: Sociocultural and biological considerations[END_REF][START_REF] Charlesworth | Gender in science, technology, engineering, and mathematics: Issues, causes, solutions[END_REF]. In particular, previous research has provided evidence of sex-based discrimination in academia, but it seems that the directionality of the bias varies depending on the context. For example, Moss-Racusin et al. ( 2012) asked professors at research-intensive universities to evaluate the CV of an undergraduate student for a lab manager position. All professors received the exact same CV while the experimenters manipulated the sex of the applicant by assigning them either a male or female name. Results revealed a significant bias in favor of the male student, who was rated as more competent and hirable and was offered more mentoring and a higher starting salary than the female applicant.

Similarly, a wealth of other studies found biased hiring processes in favor of males over female candidates, despite their comparable backgrounds [START_REF] Begeny | In some professions, women have become well represented, yet gender bias persists-Perpetuated by those who think it is not happening[END_REF][START_REF] Moss-Racusin | Science faculty's subtle gender biases favor male students[END_REF]Régner et al., 2019;[START_REF] Reuben | How stereotypes impair women's careers in science[END_REF]. Conversely, some other studies observed a gender bias favoring females [START_REF] Breda | Teaching accreditation exams reveal grading biases favor women in male-dominated disciplines in France[END_REF][START_REF] Breda | Professors in core science fields are not always biased against women: Evidence from France[END_REF][START_REF] Williams | National hiring experiments reveal 2: 1 faculty preference for women on STEM tenure track[END_REF]. For instance, employing a similar CV assessment method, [START_REF] Williams | National hiring experiments reveal 2: 1 faculty preference for women on STEM tenure track[END_REF] found that women were actually preferred over men for a tenure-track position across both mathintensive and non-math-intensive fields.

discrimination against females can be explained by their prior expectations about the degree to which hiring practices in academia are biased against women.

Finally, in Experiment 4 we examined one particular way in which moral commitment to gender equality can be expected to influence perceptions of scientific research on the issue: by making participants more likely to make an inadequate inference when the conclusion is proattitudinal. When "people believe a conclusion is true, they are also very likely to believe the arguments that appear to support it, even when these arguments are unsound" (Kahneman, 2011)-a fallacious form of reasoning called the "belief bias" (Pennycook, 2020). Specifically, we tested whether the increased moral commitment to gender equality would be associated with higher chances of viewing merely observational data that women are fewer than men in academia as proof that women are discriminated against because of their sex.

Experiment 1a

Using a research evaluation method adapted from [START_REF] Handley | Quality of evidence revealing subtle gender biases in science is in the eye of the beholder[END_REF], Experiment 1a

was designed to answer the question of whether individuals' moral commitment to gender equality affects their trust in evidence related to gender bias. Specifically, we tested whether individuals higher on moral commitment to gender equity would perceive research findings showing hiring discrimination against women as more accurate and the methods employed as more reliable, regardless of whether they were male or female. Moreover, we examined whether any hypothetical sex difference in the reception of evidence as reported in [START_REF] Handley | Quality of evidence revealing subtle gender biases in science is in the eye of the beholder[END_REF], would disappear after the variance explained by moral commitment was factored out.

All aspects of the experiment including the materials, procedure, and statistical analyses were pre-registered on OSF (10.17605/OSF.IO/UGPE4).

continuous variables (i.e. accuracy and reliability ratings, moral commitment and gender identity)

were centered by applying the scale function of R.

We first ran two simple linear regressions with sex as the sole predictor in the models.

Results showed no sex difference in the ratings of accuracy of the findings, despite numerically lower ratings of research accuracy provided by male participants (M = 6.40, SD = 2.14) than by female participants (M = 6.87, SD = 2.16; t = -1.70, p = 0.09). No sex difference was observed for the perceived reliability of the reported methods (men: M = 6.45, SD = 2.03; women: M = 6.42, SD = 1.96; t <1).

Then, we ran two linear regressions with moral commitment, sex and gender identity as predictors. Results showed that moral commitment positively predicted the perceived accuracy of the findings (β = 0.32, SE = 0.06, t = 5.17, p < .0001, η 2 = 0.10) and the perceived reliability of the methods (β = 0.18, SE = 0.06, t = 3.0, p < .003, η 2 = 0.10) of the summary reporting hiring bias against women in STEM. Again no sex difference nor any effect of gender identity was observed (all |t| <1).

We did not run the pre-registered mediation analysis as we did not observe any significant effects of sex and gender identity.

Plots of the research evaluations as a function of moral commitment and participant sex are shown in Figure 9.

Experiment 1b

To establish if the effects observed in Experiment 1a with U.K. participants can be generalized to another cultural context, Experiment 1b replicated Experiment 1a with U.S. participants.

Adopting the same design, we tested whether individuals higher on moral commitment to gender equality were more likely to trust research showing hiring discrimination against women, regardless of their sex. All aspects of the current study were pre-registered on OSF (10.17605/OSF.IO/2UG95).

Method

Participants

The data analysis included 419 U.S. participants (166 women and 253 men) aged between 18 and 88 years (M = 38, SD = 12.9) recruited on Amazon Mechanical Turk (https://www.mturk.com/). They were paid $0.50 for their participation. We determined the sample size by running a power analysis in G*Power 3.1 (Faul et al., 2009) which suggested a sample of 415 for a statistical power of 0.90. As data were collected in batches and we applied the exclusion criteria after each batch was complete, we ended up with a sample size slightly larger than the suggested one.

In total, we recruited 768 participants. Data from 349 participants were excluded as failed one of the two attention checks (Note that we performed the same analyses with the participants included, and a similar pattern of results was observed. Removing or including these participants did not qualitatively change the results.) and 62 took the survey twice (only their first response was kept).

Materials and procedure

Materials and procedure of Experiment 1b were identical to those of Experiment 1a, except in the following aspects. First, in order to mitigate chances that participants would be distracted by information of secondary importance, we removed the name of the scientific journal (PNAS) where Moss-Racusin et al., (2012)'s article was originally published, as well as the names of the authors except the lead author (see Appendix A).

Second, a short introduction was added before showing the stimulus summary in order to better prepare participants for the task: "In this survey, we are interested in how people think about scientific findings. You will be asked to read very carefully a brief summary of a research article that was published in a scientific journal and then give your opinions as non-expert about the research".

Finally, we replaced our 1-item measure of moral commitment to gender equality with a 3-item scale in order to increase the reliability of the measure. The three items, inspired from [START_REF] Skitka | Moral Conviction: Another Contributor to Attitude Strength or Something More[END_REF] were now: 1) "Achieving gender equality in society is an absolute moral imperative"; 2) "The conviction that we need to fight for gender equality is central to my identity"; and 3) "Furthering gender equality should be the government's utmost priority".

Response scales ranged from [0] "Strongly disagree" to [10] "Strongly agree", with [5] "I don't mind" as the default slider position. The three items (α = 0.89) were averaged as our measure of moral commitment to gender equality.

Results

We performed the same analyses here as we did for Experiment 1a. Similar to what was observed in Experiment 1a, men (M = 7.33, SD = 1.96) and women (M = 7.54, SD = 1.61) did not differ in the perceived accuracy of findings (t = 1.14, p = 0.26), nor in how reliable they perceived the methods to be (men: M = 7.44, SD = 1.83; women: M = 7.47, SD = 1.65; |t| < 1).

Replicating results of Experiment 1a, moral commitment to gender equality positively predicted perceived accuracy of research findings (β = 0.38, SE = 0.04, t = 10.6, p <.0001, η 2 = 0.22) and perceived reliability of the methods (β = 0.30, SE =0 .04, t = 8.30, p <.0001, η 2 = 0.22). Again, compared to moral commitment, sex and gender identity were not significant predictors of (Faul et al., 2009) which suggested a sample of 466 for a statistical power of 0.90. As data were collected in batches and we applied the exclusion criteria after each batch was complete, we ended up with a sample size slightly larger than the suggested one.

In total, we recruited 483 participants. Data from 16 participants were excluded for the following reasons: four did not meet our recruitment criteria (reported sex being "other"), 10 failed one of the two attention checks and two took the survey twice (only their first response was kept).

Materials and procedure

The materials and procedures were identical to those of Experiment 1b, except in the following respects. First, participants were presented with the exact same introduction to the study as in [START_REF] Handley | Quality of evidence revealing subtle gender biases in science is in the eye of the beholder[END_REF] before they saw the stimulus summary (see the ESM).

On the top of the following page, participants saw another short instruction on the evaluation samples, the more participants deemed pursuing gender equality in society as a moral imperative, the more they trusted research findings suggesting hiring bias against women in STEM. This result was found both when the research quality measures focused on the perceived accuracy of the findings and the perceived reliability of the methods employed (Experiments 1a and 1b), and when the composite measure of research quality of [START_REF] Handley | Quality of evidence revealing subtle gender biases in science is in the eye of the beholder[END_REF] -participants' agreement with the interpretation of the results, the perceived importance of the findings, the quality of the writing and their overall evaluation -was used (Experiment 1c).

By contrast, participants' sex had little effect on their trust in the research reporting hiring bias against women. While men judged the findings and the methods slightly less positively than women, the difference was not significant in Experiments 1a and 1b. It was only when adopting

Handley et al's composite index of research quality, in Experiment 1c, that the sex difference reached statistical significance -men rated the research less favorably than women. This sex difference, however, was smaller (d = 0.26) than in Handley et al's (d = 0.45) and the sex effect appears to be entirely explained by participants' moral commitment as the effect of participant sex disappeared when the variance accounted for by moral commitment was factored out. This overall pattern may be due to greater awareness of gender discrimination against females among men in 2020 than in 2015. After all, feminism has been on the rise during this period, especially among young people (e.g. the #MeToo movement took place https://metoomvmt.org/).

Experiment 2

Experiments 1a -1c showed that the more participants were morally committed to gender equality, the more they trusted evidence of gender bias against women in hiring in STEM sciences. The first goal of Experiment 2 was to gauge the generality of this finding by testing an additional research summary reporting bias against women. Second, Experiment 2 explored what would happen if the evidence reported gender bias favoring women in hiring, as has been found in some academic contexts (e.g. [START_REF] Williams | National hiring experiments reveal 2: 1 faculty preference for women on STEM tenure track[END_REF][START_REF] Breda | Teaching accreditation exams reveal grading biases favor women in male-dominated disciplines in France[END_REF]. We expected for a potential influence of wording, we also created a counterfactual version of each of these two (real) summaries. The counterfactual summaries were identical to the originals except that the results were reversed so that they indicated evidence of gender bias in the opposite direction than the originals (i.e. original: against women -> counterfactual: favoring women; original:

favoring women -> counterfactual: against women). All summaries had the same structure as in Experiment 1b (See Appendix A).

The procedure was identical to that of Experiment 1b except in the following aspects. In a 2 x 2 between-subjects design, participants were randomly presented with one of the four summaries (against women original; against women counterfactual; favoring women original;

favoring women counterfactual). Participants who saw the counterfactual summaries were informed at the end of the survey that they were in fact fictitious, and presented with the actual version. As in Experiment 1c, the order in which the moral commitment items and the research summary evaluation questions were presented was counterbalanced.

Results

We performed two stepwise linear regressions (direction being "both") with accuracy and reliability ratings as the dependent variables, respectively, and reported bias, moral commitment, sex, gender identity, presentation order, summary version, and all interactions as predictors.

Below we report results of the converged models.

Here, we added a random intercept for each individual summary in the linear model as there were four summaries tested. Results of the linear mixed-models were shown in Table 10. The results revealed a main effect of bias direction such that the findings of the "bias favoring women" summaries were rated as less accurate (M = 5.53, SD = 2.05) than those of the "bias against women" summaries (M = 7.07, SD = 1.79; β = 0.77, SE = 0.07, t = -10.4, p <.0001).

Likewise, the methods of the "bias favoring women" summaries were perceived as less reliable (M = 5.61, SD = 1.94) than those of the "bias against women" summaries (M = 6.69, SD = 1.86; β = 0.54, SE = 0.07, t = -7.32, p <.0001).

Overall, higher degree of moral commitment predicted higher perceived accuracy of findings (β = 0.14, SE = 0.04, t = 3.74, p <.001), and perceived reliability of the methods (β = 0.10, SE = 0.04, t = 2.70, p <.01). However, these effects of moral commitment were qualified by interactions with the reported direction of bias, as the post-hoc analyses showed significant effect of moral commitment on the perceived accuracy of the findings (β = 0.26, SE = 0.05, t = 5.61, p <.0001, η 2 = 0.09), and perceived reliability of the methods (β = 0.20, SE = 0.05, t = 4.02, p <.0001, η 2 = 0.05) when the summaries reported bias "against" women. By contrast, when the reported bias was "favoring" women, the effect of moral commitment disappeared (both p >.5).

Research methods were judged to be less reliable when the commitment items were presented before (M = 5.96, SD = 2.01) than after the evaluation task (M = 6.34, SD = 1.92; β = 0.17, SE = 0.07, t = 2.31, p = .02). Nevertheless, this order effect was characterized by its interaction with the direction of bias, as it was found marginally significant only for the "bias favoring women" summaries (β = 0.23, SE = 0.11, t = 2.09, p = .04), but not for the "bias against women" summaries (β = 0.12, SE = 0.10, t = 1.14, p = .26). No order effect was observed on ratings of accuracy of the findings (p > .2) for both types of summaries.

The converged model showed no sex difference nor effect of gender identity (all p > .5).

To test if there was any sex effect when the variance explained by moral commitment was factored out, we performed the regression analyses with bias direction, participant sex and their interaction term as predictors. Consistent with results shown above, the findings of the "bias favoring women" summaries were rated as less accurate than those of the "bias against women" summaries (β = 0.76, SE = 0.08, t = -10.2, p <.0001). Likewise, the methods of the "bias favoring women" summaries were perceived as less reliable than those of the "bias against women" summaries (β = 0.54, SE = 0.08, t = -7.17, p <.0001). In addition, we found an interaction between sex and bias direction (accuracy rating: β = 0.26, SE = 0.08, t = 3.48, p < .001, reliability rating: β = 0.17, SE = 0.08, t = 2.26, p = .02). For "bias against women" summaries, men (M = 6.75, SD = 1.86) rated the findings as less accurate than women (M = 7.39, SD = 1.65; t = -3.21, p <.001); similarly, men (M = 6.49, SD = 2.04) rated the methods as marginally less reliable than the women counterparts (M = 6.89, SD = 1.64; t = -1.96, p < .05).

Conversely, for the "bias favoring women" summaries, men rated the findings as equally accurate as women (t = 1.72, p >.05), and the same for the ratings of methods (t = 1.23, p >.1).

Plots of research evaluations (i.e. the perceived accuracy of findings and the perceived reliability of methods) as a function of moral commitment and participant sex are shown in Figure 10.

Discussion

Replicating results from Experiments 1a-1c, Experiment 2 found that individuals' moral commitment to gender equality affected their evaluations of the research demonstrating a hiring bias against women in STEM. People with positive moral attitudes on gender equity were more likely to accept evidence of women being discriminated against, while those with negative attitudes were more resistant to this evidence.

The influence of moral commitment seems to be restricted to the scenario where women were described as the victims of hiring bias but not when they were the beneficiaries, as participants scoring higher on moral commitment did not exhibit stronger resistance to the evidence of hiring preference for women (bias against men). One might argue that the effects of moral commitment on the evaluations of "bias against women" evidence could be attributed to the possibility that people who are morally concerned for gender equity also have overall higher trust in science. If this was true, we should have observed a similar pattern of effects for the "bias favoring women" summaries. However, this was not what we observed and this possibility should thus be ruled out.

Experiment 3

Experiments 1-2 found that moral commitment to gender equality positively predicted participants' level of trust in scientific evidence of hiring discrimination against females in academia. While this type of attitude-evaluation association is typically observed on polarizing issues, the psychological mechanism that underpins it is unclear. According to a narrow view, the positive correlation between participants' moral commitment to gender equality and their evaluations of specific evidence of discriminatory hiring practices against women may be In total, we recruited 520 participants. Data from three participants were excluded for the following reasons: two failed one of the two attention checks and one took the survey more than once (only their first response was kept).

Materials and procedure

As in Experiment 2, this experiment used a between-subjects design in which participants were randomly exposed to a research summary reporting evidence either of gender bias against or favoring women, with the former based on the article of [START_REF] Moss-Racusin | Science faculty's subtle gender biases favor male students[END_REF], and the latter on that of [START_REF] Williams | National hiring experiments reveal 2: 1 faculty preference for women on STEM tenure track[END_REF]. Contrary to Experiment 2 however, only the two original summaries were used (and thus no "counterfactual" scenarios were employed).

Moreover, each condition was composed of two tasks. First, participants read the summary of a scientific study about to be conducted on the issue of gender discrimination in hiring in academic sciences and were asked to predict its likely results. The research summaries were the same as in previous experiments, except that the study's methods were described in the future tense and no results were shown. Participants' predictions about the study's likely results were collected in the form of average scores they expected the male and female candidates to receive in the study, respectively (on a 0-100 slider scale with the slider initially positioned at 0) (see Appendix A).

Immediately after having made their predictions, participants saw the following message:

"The study that you just read about has been recently run by researchers. The research findings were published as an article in a scientific journal. On the next page, you are going to see a summary of the published article. Please read carefully and answer two questions". This time, participants saw the full research summary including its results (both in text and graphical format), presented in the past tense. Following previous experiments, they were asked to rate how accurate they found the research summary's results, and how reliable they found its methods to be.

As in Experiment 2, the order in which the moral commitment items and the two tasks (prediction and evaluation) were presented was counterbalanced across participants. The design was thus a 2 (bias against vs. favoring women) x 2 (commitment items before vs. after the prediction and evaluation tasks) between-subjects design.

Results

Linear regression analysis

We performed two stepwise linear regressions (direction being "both") with accuracy and reliability ratings as the dependent variables, and reported bias, moral commitment, prior beliefs, sex, gender identity, presentation order, and all interactions as predictors. Below we report results of the converged models.

Results of linear regressions are shown in Appendix B1. As observed in Experiment 2, the "bias favoring women" summary (M = 5.86, SD = 2.05) received lower accuracy ratings than the "bias against women" summary (M = 7.36, SD = 1.81; β = 0.77, SE = 0.08, t = -9.49, p <.0001); and the method reported in the "bias favoring women" summary (M = 5.99, SD = 1.95)

were also rated as less reliable than that of the "bias against women" summary (M = 6.98, SD = 1.81; β = 0.51, SE = 0.08, t = -6.27, p <.0001).

Again, overall moral commitment positively correlated with the perceived accuracy of research findings (β = 0.10, SE = 0.04, t = 2.53, p =.01) and the reliability of methods (β = 0.11, SE = 0.04, t = 2.74, p <.01). However, these effects of moral commitment were again qualified by their interactions with the reported direction of bias (accuracy: β = 0.13, SE = 0.04, t = 3.31, p = .001; reliability: β = 0.10, SE = 0.04, t = 2.33, p = .02), such that when the summary reported Effect13 of priors: β = 0.05, p <.0001; Proportion of the total effect that is mediated: β = 0.16, p <.0001), and between moral commitment and the ratings on the reliability of research methods (Average Causal Mediating Effect of priors: β = 0.04, p <.01; Proportion of the total effect that is mediated: β = 0.16, p <.01).

Similarly, participants' moral commitment partially mediated the positive correlations between moral commitment and the ratings on the accuracy of the research findings (Average Causal Mediating Effect of priors: β = 0.007, p <.01; Proportion of the total effect that is mediated: β = 0.17, p <.01), and between prior beliefs and the ratings on the reliability of research methods (Average Causal Mediating Effect of priors: β = 0.03, p <.01; Proportion of the total effect that is mediated: β = 0.17, p <.01).

Taken together, these findings suggest the distinct effects of prior beliefs and moral commitment on people's evaluations of "bias against women" evidence.

Discussion

In line with results from previous experiments, Experiment 3 found that higher moral commitment to gender equality predicted greater trust in evidence of hiring bias against women in STEM in men and women alike. This suggests that (in 2021) individuals' moral concern for gender equality more than their sex explains the level of credence they give to evidence of discrimination against women. Moreover, the results suggested that the effect of moral commitment on evaluations is not reducible to people's prior expectations about the extent to which women are discriminated against in hiring and that people's moral attitudes and prior beliefs have concurrent but differing impacts on their appraisal of evidence.

Experiment 4

Experiments 1-3 showed that participants' moral commitment to gender equality predicts how much they trust evidence of hiring discrimination against women. Experiment 4 focused on another likely consequence of moralization: the propensity to make an imprecise inference when one agrees with the conclusion. More specifically, we hypothesized that increased moral commitment to gender equality would make people more prone to infer sex-based hiring discrimination against women from the mere observation that the profession comprises more males than females.

The literature remains controversial as to the role of external bias, relative to innate or socialized individual differences in math abilities, lifestyle, and career choices in the underrepresentation of women in STEM fields [START_REF] Breda | Girls' comparative advantage in reading can largely explain the gender gap in math-related fields[END_REF][START_REF] Ceci | Women's underrepresentation in science: Sociocultural and biological considerations[END_REF]Ceci & Williams, 2010[START_REF] Abbou | Double gender marking in French: A linguistic practice of antisexism[END_REF][START_REF] Charlesworth | Gender in science, technology, engineering, and mathematics: Issues, causes, solutions[END_REF]. These factors are often intertwined and interacting with each other. To detect the effect of external bias, one needs to have the other factors maximally constant as any relationships observed in correlation studies are likely to be confounded, thus not necessarily causal. For example, Moss-Rocusin et al. ( 2012) provided clear, unequivocal evidence of sex-based discrimination as factors other than the sex of the applicant were well controlled for in the experiment. However, the mere observation of larger proportions of male research trainees in science labs is not statistical evidence of external bias as factors other than hiring bias (e.g. the base rate of male and female applicants for the positions, and their credentials) can also be in play [START_REF] Sheltzer | Elite male faculty in the life sciences employ fewer women[END_REF].

wrote the conclusion of the summary in such a way that it did commit the fallacy. The key passage of the summary was formulated as follows (see Appendix A):

Results: [Graph showing a greater proportion of male than female postdocs] "On average, laboratories comprised significantly fewer female postdocs than male postdocs."

Conclusion: "The study provides clear evidence of women being discriminated against in academia because of their sex, a characteristic that should not matter for research work."

The experimental procedure of Experiment 4 was identical to that of Experiment 1b except that an additional item was introduced to measure participants' ability to spot the fallacy:

"To what degree do you think the researchers' conclusion is justified by the research results?".

Participants responded on an 11-point scale (0 "Not at all justified -10 "Absolutely justified").

Results

As shown in Table 11, people with higher commitment to gender equality were more likely to take sex imbalance as evidence of gender discrimination (β = 0.44, SE = 0.08, t = 5.62, p < .001, η 2 = 0.10). Replicating the results of previous experiments, the more people regarded gender equality as a moral imperative, the more they believed the reported finding that the research labs comprised a larger proportion of male than female post-docs to be accurate (β = 0.34, SE = 0.06, t = 5.68, p < .001, η 2 = 0.10), and the research methods to be reliable (β = 0.42, SE = 0.07, t = 6.11, p < .001, η 2 = 0.12). Contrary to the order effect observed before in Experiments 2 and 3, the perceived accuracy of findings was higher this time when participants reported their moral commitment before seeing the summary (β = 0.27, SE = 0.12, t = 2.30, p = .02, η 2 = 0.02), and the same trend was observed for the perceived reliability of methods (β = 0.33, SE = 0.13, t = 2.47, p = .01, η 2 = 0.02). However, participants' propensity for imprecise inference was not affected by the presentation order of the commitment items and stimulus summary (β = 0.26, SE = 0.15, t = 1.71, p = .09, η 2 = 0.01).

No effect of participant sex was found either when moral commitment was factored in or out (all p > .05).

As an exploratory analysis, we performed a one-way Anova test comparing the three types of research ratings: accuracy, reliability, justification. Results showed that ratings on the three items were significantly different (F (2, 789) = 16.5, p < .0001), such that the conclusion was thought of being justified (M = 5.61, SD = 2.57) to a lesser degree than the findings were rated to be accurate (M = 6.75, SD = 1.99; p < .0001) and the methods to be reliable (M = 6.09, SD = 2.28; p < .04); also, the methods were judged as reliable to a lesser degree than the findings were considered as accurate (p < .003).

Plots of research evaluations as a function of moral commitment to gender equality and participant sex are shown in Figure 13. scientific research, results of Experiment 3 suggest that people's prior expectations about the likelihood of women being discriminated against in hiring processes because of their sex and their moral concern for gender equity exert distinct influences on their appraisals of evidence that females suffer sex-based hiring bias in academia. Participants' research evaluations reflected both their pre-existing beliefs and their initial moral attitudes. Furthermore, Experiment 4 demonstrated that people's reasoning is subject to the influence of their moral stand on an issue such that participants with greater moral commitment to gender equality conflated correlation with causation.

Uncovering the reason why people have diverging reactions to scientific evidence of gender bias disfavoring women is critical to the establishment of gender equality in society.

Relative to previous research showing that males were more resistant than females to evidence of hiring bias against women in STEM fields [START_REF] Handley | Quality of evidence revealing subtle gender biases in science is in the eye of the beholder[END_REF][START_REF] Moss-Racusin | Can evidence impact attitudes? Public reactions to evidence of gender bias in STEM fields[END_REF], here we found that people's moral convictions about gender equality, no matter if they are biologically male or female, affect their acceptance of such evidence. An individual can have multiple social identities defined by categories including their sex, profession, ideology and moral views and these identities may not be mutually exclusive. For example, being a male does not preclude one from sympathizing with females in their suffering of unequal treatment and in consequence, seeing gender equality as a moral imperative. Given the objectivity and universality nature of moral convictions [START_REF] Skitka | The Psychology of Moral Conviction[END_REF], it is not surprising that individuals' moral identity has more profound impacts on their judgments than any other non-moral identities (e.g. biological sex, profession).

By comparing people's evaluations of research reporting a hiring bias against vs.

favoring women, Experiment 2 and 3 suggested that the influence of moral commitment to gender equity is dependent on the depicted direction of bias. The extent to which individuals feel morally concerned about gender equality affected their reception of "bias against women" evidence, but moral concern did not influence individuals' judgment about "bias favoring women" research results. The differing impacts of moral commitment may be explained by the ambivalent feelings triggered in participants after seeing the unexpected or unfamiliar information that women were actually favored in academia. That is, for individuals who were morally engaged in improving women's status, the message that women have an advantage in academic hiring could be "good" and "bad" news at the same time. It is good news because, for people who value gender equality, any practice that helps to increase women's representation in male-dominated fields seems desirable, consistent with their goals for equality. Nevertheless, it can also be bad news as counter-attitudinal information could undermine collective mobilization for the cause (Petersen, 2020). Participants who interpreted the "bias favoring women" evidence as "good news" might rate the research more favorably than those regarding it as "bad news". In this way, the positive and negative effects of moral commitment simply evened out.

Considering the role of moral commitment and prior beliefs in people's treatment of new information, results of Experiment 3 suggest the concurrent but distinct functioning of the two factors in influencing people's reactions to evidence of gender bias against females in the STEM fields. Individuals' responses to the "bias against women" research are likely to result from the combinatory works of "motivated thinking" [START_REF] Kunda | Motivated Inference: Self-Serving Generation and Evaluation of Causal Theories[END_REF][START_REF] Kunda | The case for motivated reasoning[END_REF] and Bayesian reasoning.

People who hold positive moral attitudes on gender equality are more receptive of "bias against women" research findings not just because they find the information palatable, but also that it fits with their prior knowledge and understanding of the state of affairs. When asked to make judgments pertaining to a moralized issue, individuals rely on both how they feel about the information and how likely according to their prior knowledge the information appears to be true.

Put in another way, they calibrate their trust in evidence by coordinating the works of 'cold' cognition and 'hot' emotion on the mind.

Furthermore, the influences of moral commitment and prior expectations are distinct from each other as reflected by the partial mediation effects shown in Experiment 3. Indeed, individuals' prior factual beliefs about a situation do not always correspond to how much they care about a cause and their moral involvement in it. A person can be well aware of the dire consequences of gender discrimination for women but remain indifferent to it for reasons such as they are not identified with the female gender group or they see the existence of inequality as justified [START_REF] Napier | The joy of sexism? A multinational investigation of hostile and benevolent justifications for gender inequality and their relations to subjective wellbeing[END_REF].

By varying the strength of evidence, we ruled out the mundane explanation for the effects of moral attitudes on people's trust in science that participants scoring higher on moral commitment happen to be better at recognizing reliable scientific evidence. Results of Experiment 4 indicated that individuals with higher moralization of gender equality are inclined to make imprecise inferences when they find the conclusion congenial to their moral stand.

However, the results of Experiment 4 do not imply that the participants who did not confuse the correlational data of gender imbalance with sex-based discrimination succeeded at detecting the inherent logical flaw, as they too may have simply distrusted any evidence that appeared to justify a counter-attitudinal conclusion without deliberation. It is likely that once people agree/disagree with a claim, they tend to accept/reject any evidence seemingly in support of it.

The current study has its own limitations. For example, it revealed a correlation between moralization and people's research evaluations, but it remains unclear whether or not moralization actually caused the differing perception of evidence. To answer this question, future studies can manipulate participants' level of moral concern through moral priming before exposing them to research summaries. In addition, our study showed that people with high moral commitment tend to make an invalid inference to reach a congenial conclusion, but we are unsure if those who resisted such an inference actually identified its potentially fallacious nature or they simply responded based on attitudes. Future research can address this question by eliciting reasons and arguments from participants after they complete the evaluation task and see if they have justifications for their judgments or they make attitude-motivated decisions. Finally, results of the study should be interpreted with one caveat: responses were collected with nonrepresentative samples. Future studies are welcome to look if the effects hold with national representative samples.

To conclude, the study showed that people's moral stand on gender equality affects their trust in scientific evidence of gender bias and this effect is dependent on the described direction of bias. The effects of moral commitment are not entirely reducible to people's prior factual beliefs about the likelihood of a gender bias disfavoring women happening in a hiring process.

Furthermore, the moralization of an issue leads to inadequate inferences when people see invalid evidence as valid when it seems to support a conclusion congenial to their attitudes.

A3. Introductory text preceding the stimulus summary (identical to [START_REF] Handley | Quality of evidence revealing subtle gender biases in science is in the eye of the beholder[END_REF] in

Experiment 1c

In the scientific world, peer experts judge the quality of research and decide whether or not to publish it, fund it, or discard it. But what do everyday people think about these articles that get published? We are conducting an academic survey about people's opinions about different types of research that was published back in the last few years. You will be asked to read a very brief research summary and then answer a few questions about your judgments as non-experts about this research. There is no right or wrong answer and we realize you don't have all the information or background. But just like in the scientific world, many judgments are made on whether something is quality science or not after just reading a short abstract summary. So to create that experience for you, we ask that you just provide your overall reaction as best you can even with the limited information. You will also be asked to provide demographic information about yourself.

A7. The stimulus study and instructions for the prediction task in the "bias against women" condition in Experiment 3

Is there a gender bias in hiring?

Background: There are ongoing debates about gender bias in various professions. This study attempts to find out whether there exists a gender bias in hiring in academic sciences or not.

Design:

The present study will ask science faculty members (N = 127) from research-intensive universities to rate the application materials of a student for a laboratory manager position (which, in scientific labs, is often occupied by a student). The student's application materials will be shown to two different groups of professors. Half of the professors will be randomly assigned to "Group A," where they will see the candidate presented with a male name, while the other half will be randomly assigned to "Group B," where they will see the candidate presented with a female name. Crucially however, all of the other application materials will be perfectly identical. This will allow the researchers to assess whether there is any bias in the evaluation process that is solely due to the gender of the candidate. In both groups, faculty members will be asked to rate the student's perceived competence and hireability on a scale from 0 to 100. A comparison between average ratings of student's perceived competence and hireability will be conducted between faculty members assigned to Groups A and B (i.e. professors who saw the candidate presented as a male and those who saw the candidate presented as a female).

Now please make predictions about the likely results of the study.

What do you think will be the average ratings of the two groups?

A9. The "bias against women" research summary based on the article of [START_REF] Sheltzer | Elite male faculty in the life sciences employ fewer women[END_REF] Overview Despite many good intentions and initiatives to recruit and retain more women, a wealth of evidence shows that gender inequality is still rife in the fields of science, technology, engineering, and mathematics (STEM). This study measured the proportion of male to female postdoctoral researchers (postdocs, who are research trainees under the direction of senior professors of a laboratory) in labs run by senior professors. The results showed that there was a much larger percentage of men than women postdocs in the labs investigated. These results provide clear evidence of women being discriminated against in academia because of their sex, a property that should be irrelevant to their fitness for scientific research.

Methods

In order to examine the gender distribution of biomedical scientists in academia, we collected information on professors, and postdocs, employed in 39 departments at 24 of the highest-ranked research institutions in the United States. We focused on departments that study molecular biology, cell biology, biochemistry, and/or genetics. In total, we obtained information on 2,062 professors and 4,904 postdocs in the life sciences. We examined the proportions of male vs. female postdocs across those labs.

Results

On average, laboratories comprised significantly fewer female postdocs than male postdocs.

Conclusion

The study provides clear evidence of women being discriminated against in academia because of their sex, a characteristic that should not matter for research work. Put in another way, I question if the assignment of object nouns to the masculine gender class would make speakers associate these objects with male qualities and vice versa for nouns assigned to the feminine gender class. The two psycholinguistic experiments test the hypothesized language effect within French (Experiment 1) and cross-linguistically between

French and German (Experiment 2). As the article in which this study is described has been submitted as a registered report for peer review, the experiments have not been conducted at the moment. Here, I mainly present a summary of the experimental design and results of two pilot experiments.

Conflicting results have been reported in previous studies using various paradigms (see [START_REF] Bassetti | Bilingualism and thought: Grammatical gender and concepts of objects in Italian-German bilingual children[END_REF][START_REF] Beller | Culture or language: What drives effects of grammatical gender?[END_REF][START_REF] Bender | Grammatical gender in German: A case for linguistic relativity[END_REF]Bender et al., , 2016a;;[START_REF] Boroditsky | Language in Mind: Advances in the Study of Language and Thought[END_REF][START_REF] Boutonnet | Unconscious effects of grammatical gender during object categorisation[END_REF][START_REF] Cubelli | The Effect of Grammatical Gender on Object Categorization[END_REF][START_REF] Kousta | Investigating linguistic relativity through bilingualism: The case of grammatical gender[END_REF][START_REF] Mickan | Key is a llave is a Schlüssel: A failure to replicate an experiment from Boroditsky et al[END_REF][START_REF] Sato | Grammatical gender affects gender perception: Evidence for the structural-feedback hypothesis[END_REF]. Some of them employed explicit methods that might have led to participants' use of response strategies, a result of task demands (e.g. [START_REF] Clarke | Gender perception in Arabic and English[END_REF][START_REF] Sera | Grammatical and conceptual forces in the attribution of gender by English and Spanish speakers[END_REF][START_REF] Sera | When language affects cognition and when it does not: An analysis of grammatical gender and classification[END_REF]. To avoid this happening, we employ a word association paradigm built on the work of [START_REF] Boroditsky | Language in Mind: Advances in the Study of Language and Thought[END_REF]. In addition, to minimize an experimenter bias in item selection, we ask participants to create the materials for Experiment 1. Based on extensive piloting work (see Pilot Studies of Chapter 2) as well as the findings reported in [START_REF] Mickan | Key is a llave is a Schlüssel: A failure to replicate an experiment from Boroditsky et al[END_REF], we assume that any influence of grammatical gender on object representations is either weak or non-existent, and thus we adopt an approach of "stack the deck" in favor of the original hypothesis. That is, the experiments are designed in such a way that the odds of detecting any underlying language effects were maximized. To do this, firstly, the prospective participants will be tested in their native language instead of a language with no grammatical gender as did in [START_REF] Boroditsky | Language in Mind: Advances in the Study of Language and Thought[END_REF]. Secondly, we increase the likelihood of detecting a language effect (if there is one to be found) by showing gender marked determiners with the relevant noun items, as making grammatical gender information more salient would again serve to enhance the chance of observing any underlying effects. And lastly, to ensure that any null effect we find is not due to a lack of statistical power, we will run Bayesian analyses that will allow us to quantify our confidence in null or positive results.

Specifically, we will ask native speakers of French and German to produce adjectives for grammatically masculine and feminine nouns in their native language, and then we will ask another group of native participants to assess these adjectives in terms of how likely they can be associated with male and female qualities. In Experiment 1, we will test semantically related

French nouns that are assigned opposite grammatical gender in French. Experiment 2 will extend the investigation across languages by testing French and German translation-equivalents that have opposite grammatical gender in the two languages. We will commence data collection once the article gets in-principle acceptance from an academic journal. Our previous pilot results suggested null effects of grammatical gender on how objects are conceived of by native French and German speakers.

The second study (Chapter 3) examined the influence of language forms on the prominence of women in people's mental representations. Focusing on French, we compared the three generic forms: masculine, double-gender and middot. Participants were shown a short text to read, which described the taking place of a professional gathering, and then asked to estimate the proportions of men and women present at the gathering by responding on a slider. Aside from language forms, we manipulated the gender stereotypicality of the professions: genderneutral (Experiment 1), and male-and female-stereotyped (Experiment 2). The results showed a summary of [START_REF] Moss-Racusin | Science faculty's subtle gender biases favor male students[END_REF] research article that reported discriminatory hiring practice in STEM favoring male applicants, and we asked them to evaluate the quality of the research in terms of how accurate they found the research findings and how reliable they deemed the methods to be. In addition, we asked participants to report their degree of moral commitment to the cause of gender equality, as a way to measure their moral attitudes on the issue. Results revealed a positive effect of moral attitudes such that individuals with higher commitment to gender equity tended to see the research findings as more accurate and the methods as more reliable. Contradicting the results of [START_REF] Handley | Quality of evidence revealing subtle gender biases in science is in the eye of the beholder[END_REF] that people's sex affected their research evaluations -men rated less favorably than women scientific evidence suggesting discriminatory hiring practices against women in academia -our results did not show any effect of sex.

In Experiments 2 and 3, we extended the investigation to varied scenarios regarding the directionality of the reported hiring bias and the diversity of evidence by using as stimuli multiple research summaries that documented hiring bias against vs. favoring women.

Experiment 3 additionally tested if the effect of moral attitudes could be explained by participants' pre-existing expectations about the likelihood of hiring discrimination against women happening in STEM by asking them to provide predictions of the research results (in terms of how much the hiring committee's evaluations of women are biased). The results of Experiments 2 and 3 were that, overall, the "bias favoring women" summaries received lower ratings of accuracy and reliability compared to the "bias against women" summaries. Prior beliefs and moral commitment had varying effects on people's trust in evidence of a bias against and favoring women: both prior beliefs and moral attitudes predicted the evaluations of "bias against women" summaries, while neither of the two factors showed any effect on the ratings of the "bias favoring women" summaries Results of the mediation analyses suggested that moral attitudes and prior beliefs have distinct influences on people's research evaluations.

Furthermore, Experiment 4 of the study addressed the question of whether moral convictions made people more prone to imprecise inferences when faced with an attitudinal conclusion. Here, we presented participants with a research summary demonstrating the status quo that female post-doctoral research trainees were outnumbered by the male counterparts in research labs of life sciences based on results of the study [START_REF] Sheltzer | Elite male faculty in the life sciences employ fewer women[END_REF]. (despite being true, these findings cannot serve as statistical evidence of gender discrimination as other factors such as women's career preferences could contribute to the observed gender imbalance.)

However, at the end of the summary, we intendedly made an invalid conclusion that women were being discriminated against in academia because of their sex (based on the smaller proportions of female post-docs in these labs). Participants were asked to judge how much they considered the conclusion as justified by the research results shown in the summary. We found that moral commitment affected people's judgments such that individuals with higher moralization of gender equality were more inclined to take gender imbalance as solid evidence of sex-based discrimination.

Limited Influences of Language on Mental Representations

In spite of the debates, the Neo-Whorfian hypothesis has gained empirical support from various domains [START_REF] Boroditsky | Does Language Shape Thought?: Mandarin and English Speakers' Conceptions of Time[END_REF][START_REF] Davies | A cross-cultural study of colour grouping: Evidence for weak linguistic relativity[END_REF][START_REF] Gilbert | Whorf hypothesis is supported in the right visual field but not the left[END_REF][START_REF] Haun | Cognitive cladistics and cultural override in Hominid spatial cognition[END_REF][START_REF] Loewenstein | Relational language and the development of relational mapping[END_REF][START_REF] Lupyan | Language is not just for talking: Redundant labels facilitate learning of novel categories[END_REF][START_REF] Majid | Can language restructure cognition? The case for space[END_REF][START_REF] Thierry | Unconscious effects of language-specific terminology on preattentive color perception[END_REF]. Now the field has seen a shift of focus from questioning the existence of linguistic influences on thought to when it happens, how it operates and what factors account for the strength and durability of such influences [START_REF] Bender | Gender congruency from a neutral point of view: The roles of gender classes and conceptual connotations[END_REF]. Earlier research on this topic seems to suggest that thinking can be affected by language before, during and after language use [START_REF] Wolff | Linguistic relativity[END_REF]. For example, the thinking for speaking [START_REF] Slobin | From" thought and language" to" thinking for speaking[END_REF][START_REF] Slobin | Language and thought online: Cognitive consequences of linguistic relativity[END_REF] mechanism was responsible for the before effect, as demonstrated in the eye movement differences between speakers of English, German and Greek when they were asked to watch motion events and then to describe them verbally [START_REF] Gennari | Motion events in language and cognition[END_REF][START_REF] Papafragou | Does language guide event perception? Evidence from eye movements[END_REF]. They may sound trivial as it is not surprising that people attend to the aspects of an event for which their language provides ready-to-use expressions when they asked to complete a task of verbal reproduction.

The during effect is explained by a mechanism of thinking with language [START_REF] Wolff | Linguistic relativity[END_REF], or actively employing language when performing a task. Here, language serves as a conceptual tool that can facilitate certain mental activities that would be difficult or impossible without language, such as numerical cognition [START_REF] Dehaene | Sources of mathematical thinking: Behavioral and brain-imaging evidence[END_REF][START_REF] Gordon | Numerical cognition without words: Evidence from Amazonia[END_REF], the understanding of false beliefs [START_REF] Milligan | Language and theory of mind: Meta-analysis of the relation between language ability and false-belief understanding[END_REF][START_REF] Pyers | Language promotes false-belief understanding: Evidence from learners of a new sign language[END_REF], and category learning [START_REF] Lupyan | Language is not just for talking: Redundant labels facilitate learning of novel categories[END_REF]. And finally, language can highlight certain aspects of the world by having them regularly encoded in the lexicon and syntax. After a long process of language learning and language use in which people repeatedly practice a certain way of categorizing the world entities, their access to these highlighted aspects are reinforced and even become unavoidable when asked to perform tasks for which language is not required. Such kind of after effect is shown in the differing preferences and proficiency between language groups regarding the utilization of absolute, intrinsic and relative spatial frames of reference [START_REF] Haun | Cognitive cladistics and cultural override in Hominid spatial cognition[END_REF][START_REF] Levinson | Returning the tables: Language affects spatial reasoning[END_REF], and similarly in the differing sensitivity to the distinction between a loose and tight fit between objects [START_REF] Mcdonough | Understanding spatial relations: Flexible infants, lexical adults[END_REF].

As the literature suggests, the structure of the language one speaks contributes to the diversity in people's conceptualizations and construal of the reality. However, we should be aware that any linguistic working on the human mind is not irreversible, for that language does not change the fundamental cognitive machinery that human beings evolved to share in common.

For example, Korean speakers may be relatively more attentive to the distinction between a loose and tight fit of objects in a containment than speakers of English. But, this is not to say that English speakers are unable to make such a distinction at all (otherwise, one would doubt the stability of all three-dimensional structures constructed by English speakers). Instead, one can view these effects of language as the impacts of habituation. After years and years of experience in a specific way of thinking/problem solving, people become more adept and efficient in analyzing the world from that perspective, being reinforced by the language structure. Thus, when faced with a new similar problem, they are more inclined to approach it from what they regard as the vantage point and find solutions by utilizing their cognitive toolkit that has been proved useful in the past.

Although previous research remains inconclusive with respect to the hypothesized influence of grammatical gender on object cognition [START_REF] Bassetti | Bilingualism and thought: Grammatical gender and concepts of objects in Italian-German bilingual children[END_REF][START_REF] Beller | Culture or language: What drives effects of grammatical gender?[END_REF][START_REF] Bender | Grammatical gender in German: A case for linguistic relativity[END_REF]Bender et al., , 2016a;;[START_REF] Boroditsky | Language in Mind: Advances in the Study of Language and Thought[END_REF][START_REF] Boutonnet | Unconscious effects of grammatical gender during object categorisation[END_REF][START_REF] Cubelli | The Effect of Grammatical Gender on Object Categorization[END_REF][START_REF] Haertlé | Does grammatical gender influence perception? A study of Polish and French speakers[END_REF][START_REF] Imai | All giraffes have female-specific properties: Influence of grammatical gender on deductive reasoning about sex-specific properties in german speakers[END_REF][START_REF] Kousta | Investigating linguistic relativity through bilingualism: The case of grammatical gender[END_REF][START_REF] Mickan | Key is a llave is a Schlüssel: A failure to replicate an experiment from Boroditsky et al[END_REF][START_REF] Saalbach | Grammatical Gender and Inferences About Biological Properties in German-Speaking Children[END_REF][START_REF] Saalbach | Grammatical Gender and Inferences About Biological Properties in German-Speaking Children[END_REF][START_REF] Sato | Grammatical gender affects gender perception: Evidence for the structural-feedback hypothesis[END_REF][START_REF] Sera | When language affects cognition and when it does not: An analysis of grammatical gender and classification[END_REF], taken together, the body of literature suggests that any effects of language on the gendered conceptualizations of objects are likely to be limited.

Language may not change human cognitive machinery, but it may tweak our attention and memory in a subtle way. For example, speakers of grammatical gender languages are required to mind the gender class of a noun and the behavior of the words that appear with it. By so doing, they may conditionally assign more similar qualities to nouns of the same gender class, especially when the task prompts them to make associations between these words and when grammatical gender can be employed to solve the problem at hand [START_REF] Beller | Culture or language: What drives effects of grammatical gender?[END_REF][START_REF] Clarke | Gender perception in Arabic and English[END_REF][START_REF] Guiora | A Cross-Cultural Study of Symbolic Meaning-Developmental Aspects[END_REF][START_REF] Sera | Grammatical and conceptual forces in the attribution of gender by English and Spanish speakers[END_REF][START_REF] Sera | When language affects cognition and when it does not: An analysis of grammatical gender and classification[END_REF]. But if the condition is taken out (e.g. task demands, cultural connotations), the effects of grammatical gender should be largely reduced or removed, as demonstrated in [START_REF] Beller | Culture or language: What drives effects of grammatical gender?[END_REF].

As to the relationship between language and mental representations of persons, however, our study in Chapter 2 added consistent evidence of grammatical gender influencing the perceptions of men and women in a group. People perceived fewer women group members when the masculine form was used, where the female gender was made implicit/hidden and thus less accessible in the memory; conversely, gender-fair forms rendered the female gender salient, hence prompting more female associations in the minds of the perceivers. This speaks to the old saying "Out of sight, out of mind". When we think with language, we are likely to have our attention tweaked by grammatical gender that also affects how a certain category in our memory is accessed. Language plays an important role in shaping people's mental representations of gender groups and this influence is of great societal importance, in terms of how women are evaluated and considered for certain professions [START_REF] Braun | Cognitive effects of masculine generics in German: An overview of empirical findings[END_REF][START_REF] Gabriel | Au pairs are rarely male: Norms on the gender perception of role names across English, French, and German[END_REF]Gygax et al., 2008[START_REF] Gygax | The masculine form and its competing interpretations in French: When linking grammatically masculine role names to female referents is difficult[END_REF]Gygax & Gabriel, 2008;[START_REF] Hansen | The Social Perception of Heroes and Murderers: Effects of Gender-Inclusive Language in Media Reports[END_REF][START_REF] Sato | Altering male-dominant representations: A study on nominalized adjectives and participles in first and second language German[END_REF]Stahlberg et al., 2001;Stahlberg & Sczesny, 2001;[START_REF] Stout | When he doesn't mean you: Gender-exclusive language as ostracism[END_REF][START_REF] Vervecken | Ambassadors of gender equality? How use of pair forms versus masculines as generics impacts perception of the speaker[END_REF], how women's roles are viewed in general [START_REF] Koniuszaniec | Language and gender in Polish[END_REF][START_REF] Merkel | Shielding women against status loss: The masculine form and its alternatives in the Italian language[END_REF][START_REF] Mucchi-Faina | Visible or influential? Language reforms and gender (in) equality[END_REF], and how policies related to gender equality is treated [START_REF] Tavits | Language influences mass opinion toward gender and LGBT equality[END_REF]. In addition to the social impact, gender-fair language also helps to improve the overall consistency of representations people have of gender distributions across professions that are otherwise male-biased when the masculine form is used. As demonstrated in Chapter 3, genderfair forms removed a male bias in the representations of gender-balanced professional group, and they reduced some bias favoring males for occupations where female is the majority gender.

Although gender-inclusive forms induced a female bias for the male-dominated professions, overall, the perceivers formed more consistent representations after seeing gender-fair forms compared to the masculine form.

Stereotype, Ideology and Truth

Gender stereotypes contributes to the formation of people's gender role beliefs and moral attitudes toward gender equality. Stereotypes such as women are less competent than men, math is not for girls, women are emotional and not assertive, and women are family-centered constantly characterize women as intellectual inferiors with lesser career aspirations. Depending on how these gender stereotypes are treated by individuals, different ideologies such as gender essentialism and egalitarianism have been developed [START_REF] Knight | One egalitarianism or several? Two decades of gender-role attitude change in Europe[END_REF]. According to [START_REF] Knight | One egalitarianism or several? Two decades of gender-role attitude change in Europe[END_REF], people who hold what is known as the gender-essentialist ideology believe in the existence of innate sex differences between men and women and that these inherent differences account for the differing accomplishments of the two sexes; those embracing a flexible egalitarianism dismiss the idea that women were born less intelligent than men but partially accept the gender stereotypes, thus attributing gender disparities in society to free or constrained personal preferences; beyond these two, there are also advocates of liberal egalitarianism who reject all the traditional gender stereotypes and aspire to a society of gender equality [START_REF] Knight | One egalitarianism or several? Two decades of gender-role attitude change in Europe[END_REF]. Next, to allow for a more holistic assessment of the costs and benefits of language reform for the society, future studies can provide more empirical evidence that is currently absent. For instance, more empirical data are needed regarding the effects of different gender-fair language forms on the mental representations of gender groups, such as contracted forms with a slash (e.g. étudiant/es) or a dash (e.g. étudiant-e-s), and the feminine-before-masculine double-gender form (e.g. étudiantes et étudiants) that were not covered in our study. Each of these forms may have their own advantages and drawbacks that should be validated with scientific methods.

Additionally, by investigating professions of more varied gender stereotypicality (since our study only tested occupations that are gender-balanced, or extremely male-and femalestereotyped), futures studies can shed more light on the varying influence of language form and its relations with gender stereotype. Another issue that has been recurrently brought up as counterargument for gender-fair language is that it makes language learning more difficult (than it already is with masculine forms) for people with special conditions (e.g. dyslexia). Future

studies can help answer this question by investigating language learners with such conditions. In addition to the cognitive effects of language forms, future efforts can also consider the social impact of gender-fair language in France, such as how women's roles are viewed when genderfair language is used, how language reform affects the evaluation of women in a hiring process and whether people will be more aware of gender inequality problems.

Finally, about the impact of morality on trust calibration, prospective studies can examine the underlying factors that are accountable for the differing gender attitudes, say one's personality, cultural and socioeconomic background, and political ideology. Our study only revealed that individuals' moral attitudes affected their evaluation of evidence, but we still need to address the question of what leads some individuals but not others to be morally concerned about gender inequality and have strong attitudes on it. Furthermore, as the framing of information may have influences on how it is processed and interpreted by the recipients which in consequence leads to differing reactions, future studies are welcome to investigate what effects the framing of evidence can have on the level of credibility it induces in individuals.

  asked a group of native English speakers (N = 107, 27 men and 80 women), aged between 18 and 65 years (M = 33, SD = 11.2), living in the UK, to indicate on a 7-point Likert scale to what extent they associated the English translation equivalents of our items with men or with women

  Le pont est très _____b. GermanDie Brücke ist sehr_____ 'The bridge is very_____'

Figure 1 .

 1 Figure 1. Female quality association (FQA) of the adjectives as a function of

Figure 2 .

 2 Figure 2. Female quality association (FQA) of the adjectives as a function of

( 10 )

 10 Three forms of sample profession musicien 'musician' a. masculine: musiciens b. double-gender: musiciens et musiciennes c. middot 12 : musicien.ne.s

  version was framed as Selon vous, quels étaient les pourcentages d'hommes et de femmes dans ce rassemblement?('In your opinion, what were the percentages of men and women in the gathering?') (men-women version) and the other, Selon vous, quels étaient les pourcentages de femmes et d'hommes dans ce rassemblement? ('In your opinion, what were the percentages of women and men in the gathering?') (women-men version). There were likewise two versions of the response slider, such that the labels for the left and right endpoints, i.e. pictograms of a man and a woman, reflected the framing of the test question. Instructions on how to use the slider were shown with the question and remained visible to participants during the test. (See Appendix D for the slider and instructions.) Slider version (and hence, question framing), was counterbalanced within each of the three groups.

Figure 3 .

 3 Figure 3. Boxplots of estimated percentages of women as a function of linguistic form. Medians

  ) = 5.84, p < .0001; masculine vs. middot:  = 12.4, SE = 3.07, t(435) = 4.05, p < .0003; double vs. middot:  = -5.40, SE = 3.05, t(438) = -1.74, p > .1); 102 for female-stereotyped professions, the differences between the masculine form on the one hand and the gender-fair forms on the other hand, are indeed smaller and significant only for the middot form (masculine vs. double:  = 4.59, SE = 3.15, t(432) = 1.46, p > .1; masculine vs. middot:  = 10.4, SE = 3.04, t(435) = 3.47, p < .002; double vs. middot:  = 5.84 SE = 3.06, t(435) = 1.91, p > .1). Compared to the results of the pilot experiment, the effect size (partial  2 )

Figure 5 .

 5 Figure 5. Boxplots of estimated percentages of women as a function of word type and gender

Figure 6 .

 6 Figure 6. Mean percentages of gender recall accuracy as a function of word type and stereotype.

Figure 7 .

 7 Figure 7. Boxplots of estimated percentages of women as a function of linguistic form and

Figure 8 .

 8 Figure 8. Boxplots of estimated percentages of women as a function of linguistic form and

Figure 9 .

 9 Figure 9. Research evaluations as a function of participants' degree of moral commitment

Figure 10 .

 10 Figure 10. Evaluations of research showing evidence of "bias against women" and "bias

  Figure 11, and plots of research evaluations as a function of predicted gender bias (i.e. the

Figure 11 .

 11 Figure 11. Evaluations of research showing evidence of "bias against women" and "bias

Figure 12 .

 12 Figure 12. Evaluations of research showing evidence of "bias against women" and "bias

Figure 13 .

 13 Figure 13. Research evaluations as a function of moral commitment to gender equality

  used in Experiment 4 Elite faculty in the life sciences employ fewer women Sheltzer et al. Massachusetts Institute of Technology, Cambridge, MA 02139

  Gender attitudes and ideology influence individuals' perception of inequality and their trust in scientific evidence of discriminatory practices that undermine the advance of gender equity. Individuals who are morally concerned about the well-being of women are more likely to detect any practices or external barriers that discourage women from pursuing academic Additionally, future studies can enrich the data on the relationship between grammatical gender and the perceived properties in objects by examining language groups outside the Indo-European family. There are more than a hundred grammatical gender languages around the world that have diversified gender structures and many of them are understudied. Most of the existent literature documented the Indo-European languages that possess two to three gender classes. Future research can extend the investigations to languages with a larger number of gender classes, like the Niger-Congo languages (e.g. Swahili), that may show different patterns of results.

Table 1 .

 1 Results of linear mixed-effects model for Experiment 1

			SE	t	χ 2	Df	p	partial  2
	Form				18.54	2	< .0001	0.11
	double	3.41	1.53	2.23
	middot	3.11	1.52	2.04
	Next, we carried out non-preregistered post-hoc analyses to compare the results to
	Misersky et al.'s (2013) norming data shown in Appendix A.

Table 2 .

 2 Results of linear mixed-effects model for Experiment 2

			SE	t	χ 2	Df	p	partial  2
	Stereotype(male)	-13.2	1.73	-7.64	58.4	1	< .0001	0.85
					14.8	2	< .001	0.05
	Form	1.62	1.48	1.10
	double	3.91	1.49	2.62
	inclusive				3.82	2	0.15	0.01
	Stereotype  Form	2.66	1.48	1.80
	male:double	-0.38	1.49	-0.26
	male:middot
	Relative to female-stereotyped professions (M = 60.8, SD = 19.6), lower percentages of
	women were obtained for male-stereotyped ones (M = 34.6, SD = 18.7;  = -13.2, SE = 1.73, t =
	-7.64, p < .001). Restricted analyses with corrections for multiple comparison (mvt method)

Table 3 .

 3 Estimated percentage point differences between participants' estimates in Experiments 1 and 2 and Misersky et al.'s (2013) French norms. Note: Significant values are shown in boldface type, with positive ones indicating a female bias, and negative ones a male bias.

	Linguistic form

Table 4 .

 4 Results of linear mixed-effects model for pooled data analysis (Experiment 2 and Pilot

	3)
			SE	T	χ 2	Df	p	partial  2
	Stereotype(male)	-14.3	1.69	-8.48	71.9	1	< .0001	0.87
					36.2	2	< .0001	0.08
	Form	3.66	1.27	2.90
	double	3.88	1.25	3.12
	middot				10.6	2	.005	0.02
	Stereotype  Form	4.08	1.27	3.23
	male:double	-1.54	1.25	-1.24
	male:middot

Table 5 .

 5 Results of linear mixed-effects regression

		SE	t	χ 2	Df	p	partial  2

Table 6 .

 6 Results of logistic mixed-effects regression

		SE	Z	χ 2	Df	p

Table 7 .

 7 Number of participants and mean estimates of %-women as a function of Word type,

	Stereotype, and Recall response
	Word type Stereotype	Recall response	Nb	Mean %-women SE
	Noun	Male	correct	46	89.5	2.63
			incorrect	5	20.4	8.56
		Female	correct	50	88.9	1.75
			incorrect	2	50.5	0.50
	Pronoun	Male	correct	31	89.7	4.08
			incorrect	19	40.9	3.68
		Female	correct	33	86.9	3.62
			incorrect	15	56.6	5.63

Table 8 .

 8 Results of linear regression for Pilot 3

			SE	t	χ 2	Df	p	partial  2
	Stereotype(male)	-17.0	2.56	-6.64	44.1	1	< .0001	0.81
	Form(double)	2.56	1.35	1.89	3.58	1	0.058	0.03
	Stereotype(male)  Form(double)	2.96	1.35	2.18	4.77	1	0.03	0.03

Table 9

 9

	revealed effects of

Table 9 .

 9 Results of linear mixed-effects model for the Pilot study

			SE	t	χ 2	Df	p	partial  2
	Stereotype(male)	-17.0	1.92	-8.88	78.9	1	< .0001	0.91
					27.9	2	< .0001	0.17
	Form	9.00	2.40	3.75
	double	3.07	2.25	1.36
	middot				6.53	2	0.04	0.05
	Stereotype  Form	6.06	2.40	2.53
	male:double	-3.58	2.25	-1.59
	male:middot

Table 10 .

 10 Results of linear regression

	DV	IV	β	SE	t	p
	Accuracy	Bias (favoring)	-0.77 0.07	-10.4	<.0001
		Moral commitment	0.14	0.04	3.74	<.001
		Bias (favoring)*Moral commitment -0.12 0.04	-3.37	<.001
	Reliability Bias (favoring)	-0.54 0.07	-7.32	<.0001
		Moral commitment	0.10	0.04	2.70	0.007
		Order (com->summary)	-0.17 0.07	-2.31	0.02
		Bias (favoring)*Moral commitment -0.10 0.04	-2.68	0.007

Table 11 .

 11 Results of linear regression

	DV	IV	β	SE	t	p
	Accuracy	Moral commitment	0.34	0.06	5.68	< .001
		Order (com ->task)	0.27	0.12	2.30	0.02
	Reliability	Moral commitment	0.42	0.07	6.11	< .001
		Order (com ->task)	0.33	0.13	2.47	0.01
	Justification	Moral commitment	0.44	0.08	5.62	< .001
		Order (com ->task)	0.26	0.15	1.71	0.09

  B2. Results of mediation analysis with "prior beliefs" as the mediator for Experiment 3 representations of objects such that asexual objects are conceived of possessing gender qualities.

	B3. Results of mediation analysis with "moral commitment" as the mediator for Experiment 3
	DV DV	Statistic Statistic	Estimate 95% CI Lower 95% CI Upper Estimate 95% CI Lower 95% CI Upper p p
	Accuracy ACME ACME	0.045	0.017 0.007	0.002	0.08	0.01	<.0001 0.002
	Accuracy	ADE ADE	0.236	0.132 0.035	0.020	0.34	0.05	0.002 <.0001
		Total Effect Total Effect	0.281	0.170 0.043	0.028	0.39	0.06	<.0001 <.0001
		Prop. Mediated 0.160 Prop. Mediated	0.068 0.170	0.050	0.29	0.37	<.0001 0.002
	Reliability ACME ACME	0.036	0.013 0.006	0.0009	0.06	0.01	0.002 0.004
	Reliability	ADE ADE	0.183	0.055 0.029	0.015	0.31	0.04	<.0001 <.0001
		Total Effect Total Effect	0.219	0.083 0.034	0.021	0.34	0.05	<.0001 <.0001
		Prop. Mediated 0.164 Prop. Mediated	0.062 0.165	0.031	0.41	0.39	0.002 0.004

For a discussion, see https://madame.lefigaro.fr/societe/lecriture-inclusive-peut-elle-vraiment-changerla-place-des-femmes-dans-la-societe-040621-196755

See https://www.cidj.com/metiers/infirmiere-infirmier

See https://madame.lefigaro.fr/societe/lecriture-inclusive-peut-elle-vraiment-changer-la-place-desfemmes-dans-la-societe-040621-196755 for a discussion

https://www.motscles.net/ecriture-inclusive

See for instance https://www.marianne.net/agora/tribunes-libres/une-ecriture-excluante-qui-s-imposepar-la-propagande-32-linguistes-listent-les

https://www.academie-francaise.fr/actualites/declaration-de-lacademie-francaise-sur-lecriture-diteinclusive

9 https://www.legifrance.gouv.fr/jorf/id/

JORFTEXT000036068906 10 https://www.assemblee-nationale.fr/dyn/15/textes/

l15b4003_proposition-loi 11 https://www.education.gouv.fr/bo/21/Hebdo18/MENB2114203C.htm

The middot "‧" was replaced with the normal dot "." in the two experiments reported here, as is often the case in everyday language use.

Despite the parameter name, the analyses were correlational as the data were observational and we did not have a treatment condition.

Acknowledgements

A2. Actual "bias against women" research summary based on the article of Moss-Rocusin (2012) used in Experiments 1b, 1c, 2, and 3 A6. Counterfactual "bias favoring women" research summary based on the article of Moss-Rocusin (2012) used in Experiment 2

// gender predictor (sum-coded: masc=-0.5, fem=+0.5) vector [N] language; // language (sum-coded: DE=-0.5 or FR=+0.5) int<lower=1,upper=N_subj> subj [N]; // subject identifier int<lower=1,upper=N_pair> pair [N] 'What was being appreciated about Amiens?' b. Qu'est-ce qui a été offert à l'hôtel de ville ? 'What was offered at the City Hall?'

Procedure

The experiment was run via Qualtrics online software (https://www.qualtrics.com). Each participant was tested on a single trial and was paid 0.50 € for their time.

Participants were randomly assigned to one of the three linguistic forms (masculine, double gender, or middot). Within each group, they were randomly presented with one profession from the relevant list.

Once they agreed on the informed consent, participants were told that in the survey, they would be shown two very short texts to read and answer a few questions about. After reading the first text, which unbeknownst to the participants was a warm-up text, they had to answer two multiple-choice questions related to its contents (see Appendix C for the text and the questions), with the text still being visible. Depending on their responses, they received either positive or negative written feedback. Before they moved on to the next page of the survey and were presented with the target text on the professional gathering, they were told that questions about the following text would be more difficult. This was done to prompt them to read the following text with full attention. Then, they first read the text at their own pace; after a button press, the text disappeared and three questions were shown. The first two were the attention check questions shown in (11) above; if participants made at least one error, they were still able to finish the experiment but their data were excluded from the analyses. The third question asked them to provide their estimate of the gender ratio in the fictional gathering. There were two an underestimation. We used the lmer function of the lmerTest package [START_REF] Kuznetsova | lmerTest package: Tests in linear mixed effects models[END_REF] such as to obtain p-values. We found that the masculine form yielded an underrepresentation of women compared to the benchmark ( = -10.66, SE = 2.73, t = -3.91, p < .02), while estimates for the double-gender and middot forms did not differ from the benchmark values (double:  = -0.80, |t| < 1; middot:  = -1.01, |t| < 1). In other words, these results suggest that masculine plural induces an 11% point of male bias, while both the alternative forms induce a consistent representation of the proportion of women.

No previous study has focused specifically on a neutral stereotype. Yet, our finding that participants inferred a higher percentage of women when the double-gender or middot form was presented relative to the masculine form meshes well with the results of Gygax et al. (2008[START_REF] Gygax | The masculine form and its competing interpretations in French: When linking grammatically masculine role names to female referents is difficult[END_REF], who examined neutral-stereotyped role names alongside male-and female-stereotyped ones. Indeed, using a different paradigm they observed a male bias regardless of stereotype in both French and German. Similarly, the finding that the masculine form induces a male bias is in accordance with the Swedish study of [START_REF] Lindqvist | Reducing a male bias in language? Establishing the efficiency of three different gender-fair language strategies[END_REF].

Experiment 2

Experiment 1 showed an influence of linguistic form on estimations of gender ratios for professions without a gender stereotype. In this experiment, we focus on male-and femalestereotyped professions, and compare the same linguistic forms as before, i.e. masculine, doublegender and middot. This design allows us to examine whether the effect of linguistic form is modulated by stereotype. As double-gender and middot forms might promote women's visibility especially in cases where they are typically a minority gender, we expectif anythinga larger effect of linguistic form for male-stereotyped professions than for female-stereotyped ones.

Procedure

Participants were randomly assigned to one of 12 groups obtained by crossing the two stereotypes, three linguistic forms, and two slider versions. Within each group, participants were randomly shown one of the six professions from the relevant list (male-or female-stereotyped).

The procedure was otherwise identical to the one for Experiment 1.

Participants

We recruited 438 participants. The data from 133 of them were removed from the analysis for the following reasons: 33 did not complete the survey, 36 participated in Experiment 1 or a related experiment not reported in this article, 28 responded incorrectly at one or both attention check questions, and the remaining ones did not satisfy all of our recruitment criteria: 15 were non-native speakers, two did not live in France, 12 recruited on Foulefactory were older than 34, and seven recruited on Clickworker were younger than 20 (For the same reason as in Experiment 1, the selected age range for participants on Foulefactory was 25-34, while the range for those on Clickworker was 20-40. The data from the 12 on Foulefactory who indicated being older than 34 were again removed because of the conflict with the registered age in Foulefactory's database, even though they indicated being younger than 40). We also excluded the second response of 38 participants who took the survey twice.

The data analysis thus included 305 participants (158 women, 145 men, and 2 other gender). They were native French speakers living in France, aged between 20 and 40 years (M = 28, SD = 5.3). They participated on the crowd-sourcing platforms Foulefactory (N = 79) and Clickworker (N = 226) and none of them had participated in the previous experiment.

The random assignment of participants to one of 12 groups (two stereotypes x three linguistic forms x two slider layouts) resulted in a mean number of 25 participants per condition (min = 24, max = 28).

Results and Discussion

Boxplots of estimated percentages of women as a function of linguistic form and stereotype are shown in Figure 4. As in Experiment 1, the data were fit with a linear mixed-effects model. The model contained fixed factors for contrast-coded Stereotype, Linguistic form, and their interaction, as well as a random intercept for Profession. The results, shown in Table 2, revealed effects of Stereotype and Linguistic form, but no interaction.

processing information on stereotype.

Next, we turn to the question as to whether gender-fair language forms induce consistent representations. We have assumed throughout that representations are consistent if they reflect people's perceived gender ratios, as indicated by Miserky et al.'s (2013) norming data, rather than real-world gender ratios (which are currently not available for France). There is some evidence that people can reliably estimate real-world gender distributions. That is, in a study on the distribution of men and women in professions in the UK, [START_REF] Garnham | True gender ratios and stereotype rating norms[END_REF] found a good correlation between the norming data provided by the English sample in [START_REF] Misersky | Norms on the gender perception of role nouns in Czech, English, French, German, Italian, Norwegian, and Slovak[END_REF] and real-world data from governmental sources. Yet, as English marks gender only on personal pronouns, it would be useful to run a similar study in French (or German). Indeed, one might wonder to what extent norming data are themselves influenced by linguistic representations, either as encountered in daily life or as used in the norming questionnaire. As to the latter, the endpoints of the rating scale for gender-marked profession names in [START_REF] Misersky | Norms on the gender perception of role nouns in Czech, English, French, German, Italian, Norwegian, and Slovak[END_REF] showed the masculine and feminine forms, respectively, and the direction of the rating scale was counterbalanced across participants. The influence of language forms on perceived gender ratios was thus experimentally controlled at best. We tentatively conclude that the choice of benchmark data should not make much of a difference.

Recall that our results showed that the gender-fair forms yield consistent representations only for professions with a neutral stereotype. For male-stereotyped professions they overshoot their objective, while for female-stereotyped ones they fail to provide enough of a boost. It would be interesting to consider professions in a larger range of stereotypicality, as we only tested professions for whom the norming data either showed an almost perfect gender balance (estimated proportions of women between .47 and .51) or a largely unbalanced one (estimated

Pilot Studies

Pilot 1

This pilot (not included in the submitted manuscript) is similar to the two experiments described in the chapter with respect to its design and procedure. It has three aims. First, we seek to validate our paradigm by focusing on the French feminine grammatical form exclusively, which unambiguously refers to women-only groups. Thus, if the grammatical information is processed correctly, we should observe overall high estimates of %-women. In order to minimize the chances that the profession name is erroneously processed as if it were shown in the masculine form, we use names for which the feminine plural is not only written but also pronounced differently than the masculine one.

Second, we investigate whether the influence of gender stereotype can override that of grammatical gender. To do this, we compare male-vs. female-stereotyped professions. For female-stereotyped professions the stereotype is in accordance with the grammatical gender, but for male-stereotyped professions the two types of information conflict. Thus, if stereotype information overrides linguistic information, we should observe lower estimates of %-women for male-stereotyped than for female-stereotyped professions, where the latter should be at or near ceiling, i.e. 100%.

Third, we examine a potential difference according to whether the linguistic information is present on a noun or on a pronoun. Compared to content words, function wordsincluding pronounsare shorter, more frequent, more predictable and more often redundant, and there is evidence that they are processed in less depth during reading [START_REF] Carpenter | What your eyes do while your mind is reading[END_REF][START_REF] Healy | Letter detection: A window to unitization and other cognitive processes in reading text[END_REF]03; male-stereotyped, not gender-marked: Mmen = .80 SD = .02; female-stereotyped, gendermarked: Mwomen = .78, SD = .05; female-stereotyped, not gender-marked: Mwomen = .78, SD = .08). An Anova with the factors Stereotype and Gender-marking showed no main effect and no interaction (Stereotype: F(1,20) = 1.07, p > .1; Gender-marking and Stereotype  Gendermarking: F < 1). The 24 professions, together with the estimates of %-women in those The short text about the professional gathering was similar to the one used in the two experiments. Same as the previous experiments, in the passage for the noun condition, exemplified in (12a), the feminine plural form of the profession name appeared twice in the text and no referential pronoun was used. In the passage for the pronoun condition, exemplified in (12b), the profession name had no gender marking and its plural form was shown only once, but a referential feminine plural pronoun appeared twice; this pronoun thus revealed the gender information. Hence, in both conditions the relevant grammatical information appeared twice.

(12) a. Passage for noun condition with sample profession:

Le rassemblement régional des caissières a eu lieu cette semaine à Amiens. La localisation centrale de cette ville a été particulièrement appréciée. Les caissières ont aussi adoré l'apéro offert à l'hôtel de ville le premier jour. 'The regional gathering of cashiersfem took place this week in Amiens. The central location of this city was particularly appreciated. The cashiersfem also loved the aperitif offered at the City Hall on the first day.'

b. Passage for pronoun condition with sample profession:

Le rassemblement régional des fleuristes a eu lieu cette semaine à Amiens. Elles ont particulièrement appréciée la localisation centrale de cette ville. De plus, elles ont adoré l'apéro offert à l'hôtel de ville le premier jour. 'The regional gathering of floristsmasc/fem took place this week in Amiens. Theyfeminine particularly appreciated the central location of this city. Theyfeminine also loved the aperitif offered at the City Hall on the first day.'

The words régional and Amiens were replaced with européen and Francfort respectively for three professions, mathématicien 'mathematician', douanier 'customs officer' and astronaute 'astronaut', for it would be more plausible for these professionals to have a Europe-wide assembly in a more internationally-oriented city than a regional one in a provincial city.

Procedure

The pilot followed the same procedure as for Experiment 1 and 2 except in the aspects described below.

Participants were randomly assigned to one of four groups defined by crossing word type (noun or pronoun) and stereotype (male or female). Within each group, participants were randomly assigned to one profession from the relevant list.

After the rating task, participants were asked a multiple-choice question to test how well they recalled the gender-marked profession name or the pronoun from the text they had seen.

The question was framed as Quel mot était présent dans le texte ? ('Which word was shown in the text?') and three choices were shown below the question. For participants in the noun condition, the three choices were: profession name in masculine plural form (e.g., caissiers), profession name in feminine plural form (e.g., caissières), and Je ne sais pas ('I don't know');

These factors could of course also be at play for the participants who were incorrect on the memory question. Despite the presence of such noise in the data, our paradigm appears to be adequate for testing the influence of grammatical gender on the perception of biological gender, especially when the gender information is present on the noun denoting the profession rather than on a referential pronoun. In the remaining experiments, we therefore focus on grammatical gender-marked profession names, and hence use the kind of noun passage exemplified in (5a) above.

Pilot 2

Pilot 2 (not included in the submitted manuscript) was similar to Pilot 1 in terms of the materials and procedure. In this pilot experiment, we compared the masculine plural pronoun ils 'theymasc' and its double-gender alternative ils et elles 'theymasc and theyfem'. We did not include the inclusive writing form iels as it seems extremely unfamiliar to French speakers.

Method

Stimuli

The stimuli used in this pilot were the same as for the pronoun condition of Pilot 1. They were 12 profession names with a unique form for the masculine and feminine gender (see

Appendix B).

Procedure

The procedure for this pilot was identical to that of Pilot 1 except in the following aspects.

First, we only had a pronoun condition as we removed the noun condition described in Pilot 1.

Second, no memory question was being asked after the estimation task. Third, participants were randomly assigned to one of four groups (2 gender stereotype x 2 linguistic form), and within each group, they were randomly shown one profession name from the relevant list.

Participants

Participants were native French speakers living in France (N = 146), 80 women and 66 men, aged between 20 and 68 years (M = 43, SD = 12). They participated on the crowd-sourcing platform Foulefactory.

The mean number of participants per condition was 18 (min = 8, max = 25). differences between masculine and the gender-fair forms are smaller and significant only for the middot form (masculine vs. double:  = 12.5, SE = 6.38, t(133) = 1.97, p > .1; masculine vs. middot:  = 16.2, SE = 5.54, t(134) = 2.93, p < .02; double vs. middot: t < 1). Appendix B. French profession names used in Pilots 1 (pronoun condition) and 2, with mean percentages of women as rated by participants in [START_REF] Misersky | Norms on the gender perception of role nouns in Czech, English, French, German, Italian, Norwegian, and Slovak[END_REF].

Stereotype

Profession name English translation %-women 'Move the indicator to respond:

Male

If the indicator is at the utmost left end, you estimate that there is 100% women and 0% men.

If the indicator is at the utmost right end, you estimate that there is 0% women and 100% men.

If the indicator is at the midpoint, you estimate that there are women as many as men.

Of course, your choice is not restricted to the three

Abstract

In a context of increasing gender equality in Western societies, systematic differences and possible biases in how people weight evidence of gender discrimination against women have garnered much public attention. However, the ultimate sources of those are unclear. Some previous work [START_REF] Handley | Quality of evidence revealing subtle gender biases in science is in the eye of the beholder[END_REF] suggests that participant's gender is a key factor, such that men rate less favorably than women strong (experimental) scientific evidence suggesting discriminatory hiring practices against women. Here, we explore a potentially more powerful source of variation in how people evaluate evidence of gender discrimination: their level of moral commitment to gender equality.

Across a series of six experiments, we focus on perceptions of discriminatory hiring practices based on gender in academic contexts. We find that people's degree of moral commitment to gender equality is a robust predictor of their trust in statistical evidence of gender discrimination against women, and that the correlation between moral commitment and evaluations cannot be explained by factual prior beliefs. Moreover, this holds whether the evidence of hiring bias is strong (experimental) or weak (only correlational, thus leading to confusion between gender imbalance and discriminatory hiring). Our results additionally show, in contrast to previous work in this area, that participant sex does not predict evaluations of evidence of discrimination. Taken together, our findings suggest a new picture of the origins of systematic differences in people's appreciation of evidence of gender bias in academia.

Keywords: Gender bias, Moral commitment, STEM, Prior beliefs, Trust, Research evaluations While a wealth of evidence suggests that women do suffer sex-based discrimination in academia, there is significant variability in how people react to this fact [START_REF] Danbold | Men's defense of their prototypicality undermines the success of women in STEM initiatives[END_REF][START_REF] Handley | Quality of evidence revealing subtle gender biases in science is in the eye of the beholder[END_REF][START_REF] Moss-Racusin | Can evidence impact attitudes? Public reactions to evidence of gender bias in STEM fields[END_REF]. For instance, [START_REF] Handley | Quality of evidence revealing subtle gender biases in science is in the eye of the beholder[END_REF] difference in reactions as in-group favoritism, a mechanism by which men protect their identity as the dominant gender group in STEM by resisting information that threatens this identity [START_REF] Danbold | Men's defense of their prototypicality undermines the success of women in STEM initiatives[END_REF][START_REF] Handley | Quality of evidence revealing subtle gender biases in science is in the eye of the beholder[END_REF].

In this work, we approach people's differing reactions to evidence of gender bias from a novel angle: by examining the possible influence of moral commitment to gender equality. Moral commitment (or conviction) to a cause refers to the degree to which individuals deem the issue as an unnegotiable moral imperative. People highly committed to an issue typically see it as objectively and universally important, and as central to their sense of moral identity. They display strong emotional reactions-such as anger and disgust-at people, practices, representations, and institutions that they think to impede the advancement of their cherished cause [START_REF] Skitka | The Psychology of Moral Conviction[END_REF][START_REF] Skitka | Moral Conviction: Another Contributor to Attitude Strength or Something More[END_REF]. Drawing on these considerations, we hypothesized that individuals' moral commitment to gender equality may be a key moderator of their trust in research on the issue of gender bias in academia. A long tradition of research has shown that people's moral attitudes modulate their processing of new information-whether this springs from prior beliefs only, or involves emotional processes as in "motivated thinking" [START_REF] Kunda | Motivated Inference: Self-Serving Generation and Evaluation of Causal Theories[END_REF][START_REF] Kunda | The case for motivated reasoning[END_REF][START_REF] Lord | Biased Assimilation and Attitude Polarization: The Effects of Prior Theories on Subsequently Considered Evidence[END_REF]. For example, scientific articles highlighting the role of human activities in global warming are more likely to have the credibility of their methods or the probity of their authors questioned by conservatives than liberals (Kahan et al., 2011a). Proponents of the death penalty put studies suggesting its inefficiency in deterring murder under closer scrutiny than people who forcefully oppose it [START_REF] Edwards | A disconfirmation bias in the evaluation of arguments[END_REF][START_REF] Lord | Biased Assimilation and Attitude Polarization: The Effects of Prior Theories on Subsequently Considered Evidence[END_REF]. Scientists tend to discount manuscripts under review that run against their favored theory than those supporting their theoretical convictions (Koehler 1997).

Current study

Following these lines of research, we expected that individual differences in moral commitment to gender equality may be associated with differences in how persuasive evidence of gender discrimination in academia is perceived as being. Specifically, we hypothesized that greater commitment to gender equality should predict increased trust in research reporting evidence of hiring discrimination against females, regardless of participants' sex. Experiments 1a, 1b, 1c, and 2 look specifically at this question.

Influences of moral attitudes on judgments raise the important question of whether those influences can be reduced to people's prior factual beliefs/expectations on the issue at hand [START_REF] Lord | Biased Assimilation and Attitude Polarization: The Effects of Prior Theories on Subsequently Considered Evidence[END_REF]Pennycook, 2020;Tappin et al., 2020aTappin et al., , 2020b)). In order to shed light on this question, we also explored in Experiment 3 if the (theorized) relationship between individuals' moral commitment to gender equality and their trust in research reporting evidence of hiring

Method

Participants

The data analysis included 268 UK participants (171 women and 97 men) aged between 18 and 74 years (M = 35, SD = 13.1). They were recruited on the crowd-sourcing platform Prolific (https://prolific.co/) and were paid £0.50 for their participation. We determined the sample size by running power analysis using the applications "mc_power_med" and "schoam4" (Schoemann et al., 2017) in R (R Core Team, 2020) via Rstudio (RStudio Team, 2020). The applications suggested a sample size of 250 for a statistical power of 0.87. As data were collected in batches and we applied the exclusion criteria after each batch was complete, we ended up with a sample size slightly larger than the suggested one.

In total, we recruited 288 participants. Data from 20 participants were removed for the following reasons: one did not meet our recruitment criterion (reported sex being "other"), 17

failed one of the two attention checks, and two took the survey more than once (only their first response was kept).

Materials and procedure

We On the next page, participants passed a second attention check by answering the question:

"The summary you've just read is about". They could choose from "Poverty economics", "Modern literature", "Gender bias", and "Quantum physics". Participants who chose answers other than "Gender bias" were removed from the analyses.

Then, participants were asked to report their degree of moral commitment to gender equality by indicating the extent to which they agreed with the statement: "Achieving gender equality in society is a moral imperative" on a slider scale ranging from [0] "Strongly disagree" to [10] "Strongly agree" with [5] "Neither agree nor disagree" as default slider position.

Next, they reported their sex and gender identity in random order. The question for biological sex was "Assuming sex is a biological notion that refers to your physical anatomy, what is your sex?". Participants chose from "Male", "Female" and "Other" as responses. There were two versions of the question on gender identity in order to counterbalance the order in which the words "masculine" and "feminine" appeared in the text. One version of the question was framed as "Assuming gender refers to how masculine or feminine you feel with respect to your identity, where would you position your gender?" (Masculine-Feminine version), and the other version, as "Assuming gender refers to how feminine or masculine you feel with respect to your identity, where would you position your gender?" (Feminine-Masculine version).

Consistent with the question framing, there were two versions of response scales depending on whether the left [0] and right [10] endpoints were labeled as "Strongly masculine" and or "Strongly feminine", respectively (Masculine-Feminine version), or the reverse (Feminine-Masculine version). The slider was initially positioned at [5] "Gender neutral" on both scales.

Participants were randomly assigned either version of the gender identity question / scale.

Responses on the Feminine-Masculine scale were reverse coded.

The survey ended with a question about participants' age, and a 1-item measure of political orientation.

Results

All data cleaning and analyses reported in this paper were conducted in R (R Core Team, 2020) via RStudio (RStudio Team, 2020). Linear regression analyses were run using the lme4 package [START_REF] Bates | Fitting Linear Mixed-Effects Models Using lme4[END_REF]. The categorical variable (i.e. sex) was contrast-coded and the research evaluations (all |t| < 1). For the same reason as described in Experiment 1a, the preregistered mediation analysis was again not run.

Plots of the research evaluations as a function of moral commitment and participant sex are shown in Figure 9.

Experiment 1c

Unlike [START_REF] Handley | Quality of evidence revealing subtle gender biases in science is in the eye of the beholder[END_REF] who reported that males were less receptive to evidence demonstrating a hiring bias against women than female participants, we found an effect of moral commitment on individuals' research evaluations across cultures in Experiments 1a and 1b, while no sex difference was observed. There were a few possible explanations for the absence of sex difference in the perception of evidence in our experiments. One is that our dependent measures, which were different from those of [START_REF] Handley | Quality of evidence revealing subtle gender biases in science is in the eye of the beholder[END_REF], failed to capture the sex difference (if it exists). Another possibility is that men and women reached more consensus on the issue of gender bias over the last few years and thus any sex difference observed before has diminished. To answer this question, here we ran an exact replication of Handley et al's design again with a U.S. sample, by using their original dependent measures in order to allow for a more accurate comparison. All aspects of the current study were pre-registered on OSF (10.17605/OSF.IO/7UW85).

Method

Participants

The data analysis included 467 U.S. participants (233 women and 234 men) aged between 18 and 68 years (M = 35, SD = 11.8) recruited on Prolific. They were paid £0.50 for their participation. We determined the sample size by running a power analysis in G*Power 3.1

A second change from our previous experiments was that we counterbalanced the order in which the moral commitment items and the research evaluation questions were presented.

Finally, in this study and the other studies presented below, we kept only the Masculine-Feminine version of the gender identity question and response scale.

Results

We ran the same analysis as before. This time, the sex effect in Handley et al ( 2015 That said, the sex difference vanished (β = 0.05, SE = 0.04, t = 1.10, p = 0.27) when moral commitment was factored in. Consistent with results of previous experiments, moral commitment positively predicted the perceived overall quality of the research summary (β = 0.19, SE = 0.02, t = 12.06, p < .0001, η 2 = 0.26). Additionally, unlike Experiment 1a and 1b, here we observed an interaction between moral commitment and participant sexthe effect of moral commitment was more pronounced among males than females (β = 0.04, SE = 0.02, t = 2.67, p < .01, η 2 = 0.02). Results also suggested a three-way interaction between moral commitment, presentation order and sex (β = 0.04, SE = 0.02, t = 2.81, p < .01, η 2 = 0.02). Restricted post-hoc analysis revealed that the effect of commitment on evaluations was greater in male than in female participants when the moral commitment scale was presented before the research summary (t = 4.34, p < .001); however, the effect was the same on both sexes when the research summary preceded the moral commitment items (t < 1, p > .9).

evidence of hiring bias favoring women to face more skepticism than that of women being discriminated against, and that the skepticism would be amplified by participants' moral commitment to gender equality. All aspects of the current experiment were pre-registered on OSF (10.17605/OSF.IO/W9KUS).

Method

Participants

The data analysis included 636 U.K. participants (319 women and 317 men) aged between 18 and 76 years (M = 36, SD = 13.2), recruited on Prolific. They were paid £0.50 for their time. Again, we determined the sample size by applying the same criterion as described in Experiments 1b and 1c. We ran a power analysis in G*Power 3.1 (Faul et al., 2009) which suggested a sample of 618 for a statistical power of 0.90. For the same reason as in previous experiments, we ended up with a sample size slightly larger than the suggested one.

In total, we recruited 660 participants. Data from 24 participants were excluded for the following reasons: two did not meet our recruitment criteria (reported sex being "other"), 20 failed one of the two attention checks and two took the survey twice (only their first response was kept).

Materials and procedure

The materials used in Experiment 2 were four summaries reporting evidence of gender discrimination that in two cases described a hiring bias "against women" and in the other two cases a hiring bias "favoring women". One of the "against women" summaries was based on the article by [START_REF] Moss-Racusin | Science faculty's subtle gender biases favor male students[END_REF], as used in previous experiments, and one of the "favor women" summaries was based on the article by [START_REF] Williams | National hiring experiments reveal 2: 1 faculty preference for women on STEM tenure track[END_REF] which reported evidence of hiring bias favoring women in STEM. In order to vary our stimuli while controlling explained entirely by their prior expectations about the degree of discrimination that women would face in the relevant scenario. Alternatively, it may be that the effect of moral commitment on evaluations of scientific evidence goes over and above these prior expectations in such a way that we can consider any such effects to be conceptually separate from those of specific prior expectations.

In order to examine the extent to which an association between moral commitment and research evaluations, when it is found, can be reduced to participants' expectations about the likely size of the hiring bias, Experiment 3 adopted a design that allowed participants to both predict how much discrimination against women they thought would be observed in the study before it was conducted, and to evaluate how credible they perceived the study once its results

were available. Similar to Experiment 2, it also manipulated the direction of the bias described in the summaries: hiring bias against vs. favoring women.

All aspects of the current study concerning the materials, procedure, and analyses were pre-registered on OSF (10.17605/OSF.IO/BVKJC)

Method

Participants

The data analysis included 517 UK participants (265 women and 252 men) aged between 18 and 80 years (M = 36, SD = 13), recruited on Prolific. They were paid £0.50 for their time.

Again, we determined the sample size by running a power analysis in G*Power 3.1 (Faul et al., 2009) which suggested a sample of 502 for a statistical power of 0.90. For the same reason as in previous experiments, we ended up with a sample size slightly larger than the suggested one.

hiring bias against women, participants' with higher degree of moral commitment rated the findings as more accurate (β = 0.24, SE = 0.05, t = 4.73, p <.0001, η 2 = 0.11), and the methods as more reliable (β = 0.22, SE = 0.05, t = 4.15, p <.0001, η 2 = 0.06). Conversely, when the summary reported hiring bias favoring women, the effect of moral commitment disappeared (both p > .5).

Next, higher prior beliefs of gender bias against women predicted higher ratings on the accuracy of research findings (β = 0.01, SE = 0.006, t = 2.03, p = .04), and this effect was moderated by the reported direction of bias (β = 0.02, SE = 0.006, t = 3.72, p <.001). For the "bias against women" summary, expectations about the likelihood of gender discrimination happening positively predicted ratings on the accuracy of research findings (β = 0.04, SE = 0.008 t = 4.55, p <.0001, η 2 = 0.07), but again the effect of priors disappeared for the "bias favoring women" summary (β = 0.01, SE = 0.008, t = 1.30, p = .20).

As before, participants who reported their moral commitment before the prediction and evaluation tasks tended to rate the findings as marginally less accurate (β = 0.15, SE = 0.08, t = 1.82, p = .07) and the methods as less reliable (β = 0.19, SE = 0.08, t = 2.40, p = .02). This order effect was conditioned on the reported direction of bias (accuracy: β = 0.19, SE = 0.08, t = 2.38, p = .02; reliability: β = 0.22, SE = 0.08, t = 2.73, p <.01). The results of the "bias favoring women" summary were rated as less accurate (β = 0.36, SE = 0.13 t = -2.87, p < .01, η 2 = 0.03), and its methods as less reliable (β = 0.42, SE = 0.12 t = -3.50, p <.001, η 2 = 0.05) when participants saw the commitment items before the prediction and evaluation tasks than in the reversed order. Conversely, for the "bias against women" summary, no order effect was observed (both p >.5).

Similar to results of Experiment 2, when moral commitment was factored in, no effect of sex or gender identity, nor any interaction with other factors was found (all p > .05). However, when the variance explained by moral commitment was factored out, an interaction between sex and the reported direction of bias was found (accuracy: β = 0.30, SE = 0.08, t = 3.64, p <.001; reliability: β = 0.23, SE = 0.08, t = 2.81, p < .01). For the "bias against women" summary, men rated the findings as significantly less accurate (Men: M = 6.96, SD = 1.74; Women: M = 7.73, SD = 1.73; t = 3.28, p <.01) and the methods as slightly less reliable (Men: M = 6.86, SD = 1.81;

Women: M = 7.25, SD = 1.79; t = 1.69, p = 0.09) than did women. In comparison, for the "bias favoring women" summary, men rated the findings as slightly more accurate (Men: M = 5.99, SD = 2.05; Women: M = 5.55, SD = 2.04; t = 1.87, p = 0.06) and the methods as significantly more reliable (Men: M = 6.28, SD = 2.01; Women: M = 5.75, SD = 1.89; t = 2.29, p = 0.02) as did women.

Correlational mediation analyses

To further assess the triangular relationships between prior beliefs, moral commitment and research evaluations, we further performed correlational mediation analyses by following the steps set forth by Baron and Kenny (1986), using the R package mediation (Tingley et al., 2014).

These analyses were run only for the "bias against women" condition, aiming to test two (theorized) mediation effects: 1) the relationship between moral commitment and research evaluations is mediated by priors, and 2) the relationship between priors and research evaluations is mediated by moral commitment. The results, obtained with 1000 times bootstrap simulations, showed two significant partial mediation effects (see Appendices B2 and B3)

First, participants' prior beliefs partially mediated the positive correlations between moral commitment and the ratings on the accuracy of the research findings (Average Causal Mediating

Method

Participants

The data analysis included 264 UK participants (198 women and 66 men) aged between 18 and 62 years (M = 29, SD = 10.9) recruited on Prolific. They were paid £0.50 for their time.

As in previous experiments, we determined the sample size by running a power analysis in G*Power 3.1 (Faul et al., 2009) which suggested a sample of 255 for a statistical power of 0.90.

For the same reason as described above, we ended up with a sample size slightly larger than the suggested one.

In total, we recruited 280 participants. Data from 16 participants were excluded for the following reasons: one did not meet our recruitment criteria (reported sex being "other"), 13 did not complete the survey and two failed one of the two attention checks.

Materials and procedure

The stimulus summary was based on the research article of [START_REF] Sheltzer | Elite male faculty in the life sciences employ fewer women[END_REF], presented in the same format as the summaries tested before (see Appendix A). In the original study, the authors examined the gender distribution of biomedical scientists in academia by collecting information on post-doctoral researchers and professors employed in 39 departments at 24 of the highest-ranked research institutions in the United States. They focused on departments studying molecular biology, cell biology, biochemistry, and/or genetics. The original results reported that the labs employed fewer female than male post-docs in labs run by senior professors. Importantly, the report did not take this observed gender imbalance as evidence of gender discrimination specifically targeted at women. This would imply committing a fallacy, as women may be underrepresented in a profession because they simply are less interested in the job, for instance, and consequently apply less. Nonetheless, we intentionally

Discussion

Consistent with results of previous experiments, individuals having higher moral commitment to gender equity were more inclined to accept the finding that women are outnumbered by men in academia and to consider the research methods employed to obtain this finding as reliable. When faced with weak evidence, participants overall showed more skepticism about the reliability of the research methods and the extent to which the conclusion was supported by the reported results. However, as predicted, individuals who saw gender equality as a moral imperative were more likely to make an imprecise inference (i.e. the existence of gender bias against women) from the observation of lower proportions of female than male post-docs in research labs.

General discussion

Across six survey-based experiments, we investigated the influences of moral commitment to gender equality on people's trust in scientific research on gender bias. Overall, the experiments consistently revealed a positive relationship between the moralization of gender equality and reactions to evidence of women being discriminated against in academia. Specifically, Experiments 1 -3 found that participants, regardless of their sex, who scored higher on moral commitment to gender equity tended to rate research findings demonstrating a hiring bias against women as more accurate and the research methods adopted as more reliable. This effect of moral commitment was limited to research summaries reporting a gender bias to the disadvantage of women. By comparing two opposing directions of hiring bias (i.e. against vs. favoring women),

Experiment 2 additionally showed that moral conviction moderated people's evaluations of "bias against women" evidence, but not when the evidence pointed to a "bias favoring women".

Regarding the role of prior beliefs in the relationship between moral commitment and trust in Appendix A. Stimuli A1. Actual "bias against women" research summary based on the article of Moss-Rocusin (2012) used in Experiment 1a

Proceedings of the National Academy of Sciences USA 109(41):16474-16479 Science faculty's subtle gender biases favor male students C. A. Moss-Racusina, J. F. Dovidio, V. L. Brescoll, M. J. Grahama, and J. Handelsman

Background:

Despite efforts to recruit and retain more women, a stark gender disparity persists within academic science. Abundant research has demonstrated gender bias in many demographic groups, but has yet to experimentally investigate whether science faculty specifically exhibit a bias against female students that could contribute to the gender disparity in academic science.

Design:

The present study asked science faculty members (N = 127) from research-intensive universities to rate the application materials of a student for a laboratory manager position (which, in scientific labs, is often occupied by a student). The student applicant was randomly given a male or female name, but was described as having exactly the same skills in both groups. In both groups, faculty members were asked to: rate the student's perceived competence and hireability, propose a starting salary, and offer a certain amount of career mentoring to the student. A comparison between average ratings of student's perceived competence, hireability, proposed salary and career mentoring was conducted between the male student and the female student groups.

Results:

• Science faculty members rated the male student as significantly more competent and hireable than the (identical) female student.

• Faculty members also offered more career mentoring to the male student and selected a higher starting salary.

• The gender of the faculty did not affect their ratings, such that female and male faculty were equally likely to exhibit bias against the female student.

Conclusions:

These results suggest that well-documented bias against females also exists in academia Science faculty's subtle gender biases favor male students Moss-Racusin et al. Yale University, New Haven, CT 06520

Background:

Despite efforts to recruit and retain more women, a stark gender disparity persists within academic science. Abundant research has demonstrated gender bias in many demographic groups, but has yet to experimentally investigate whether science faculty specifically exhibit a bias against female students that could contribute to the gender disparity in academic science.

Design:

The present study asked science faculty members (N = 127) from research-intensive universities to rate the application materials of a student for a laboratory manager position (which, in scientific labs, is often occupied by a student). The student applicant was randomly given a male or female name, but was described as having exactly the same skills in both groups. In both groups, faculty members were asked to: rate the student's perceived competence and hireability, propose a starting salary, and offer a certain amount of career mentoring to the student. A comparison between average ratings of student's perceived competence, hireability, proposed salary and career mentoring was conducted between the male student and the female student groups.

Results:

Science faculty members rated the male student as significantly more competent and hireable than the (identical) female student.

 Faculty members also offered more career mentoring to the male student and selected a higher starting salary.  The gender of the faculty did not affect their ratings, such that female and male faculty were equally likely to exhibit bias against the female student.

Conclusions:

These results suggest that well-documented bias against females also exists in academia.

A4. Actual "bias favoring women" research summary based on the article of [START_REF] Williams | National hiring experiments reveal 2: 1 faculty preference for women on STEM tenure track[END_REF] used in Experiment 2

National hiring experiments reveal 2:1 faculty preference for women on STEM tenure track W. M. Williams and S. J. Ceci Cornell University, Ithaca, NY 14853

Background:

In life and social sciences, women now earn the majority of doctorates, but they make up a minority of assistant professors. The underrepresentation of women in academic science is typically attributed, both in scientific literature and in the media, to sexist hiring.

Design:

In the present study, 363 faculty members (182 women, 181men) were asked to evaluate hypothetical narrative summaries describing identically qualified female and male applicants for tenure-track assistant professorships in biology, engineering, economics, and psychology. The profiles were systematically varied to disguise identical academic credentials; applicants shared the same lifestyle (e.g., single without children, married with children); and the profiles were counterbalanced by gender across faculty.

Results:

Contrary to prevailing assumptions, our data revealed that men and women faculty members from all four fields preferred female applicants 2:1 over identically qualified males with matching lifestyles (single, married, divorced), with the exception of male economists, who showed no gender preference.

Conclusions:

Our findings, supported by real-world academic hiring data, suggest advantages for women to launch careers in academic science.

A5. Counterfactual "bias against women" research summary based on the article of [START_REF] Williams | National hiring experiments reveal 2: 1 faculty preference for women on STEM tenure track[END_REF]

Background:

In life and social sciences, women now earn the majority of doctorates, but they make up a minority of assistant professors. The underrepresentation of women in academic science is typically attributed, both in scientific literature and in the media, to sexist hiring.

Design:

In the present study, 363 faculty members (182 women, 181men) were asked to evaluate hypothetical narrative summaries describing identically qualified female and male applicants for tenure-track assistant professorships in biology, engineering, economics, and psychology. The profiles were systematically varied to disguise identical academic credentials; applicants shared the same lifestyle (e.g., single without children, married with children); and the profiles were counterbalanced by gender across faculty.

Results:

In line with prevailing assumptions, our data revealed that men and women faculty members from all four fields preferred male applicants 2:1 over identically qualified females with matching lifestyles (single, married, divorced), with the exception of male economists, who showed no gender preference.

Conclusions:

Our findings, supported by real-world academic hiring data, suggest that women encounter gender discrimination when launching careers in academic sciences.

Science faculty's subtle gender biases favor female students

Moss-Racusin et al. Yale University, New Haven, CT 06520

Background:

Despite efforts to recruit and retain more women, a stark gender disparity persists within academic science. Abundant research has demonstrated gender bias in many demographic groups, but has yet to experimentally investigate whether science faculty specifically exhibit a bias against female students that could contribute to the gender disparity in academic science.

Design:

The present study asked science faculty members (N = 127) from research-intensive universities to rate the application materials of a student for a laboratory manager position (which, in scientific labs, is often occupied by a student). The student applicant was randomly given a male or female name, but was described as having exactly the same skills in both groups. In both groups, faculty members were asked to: rate the student's perceived competence and hireability, propose a starting salary, and offer a certain amount of career mentoring to the student. A comparison between average ratings of student's perceived competence, hireability, proposed salary and career mentoring was conducted between the male student and the female student groups.

Results:

 Science faculty members rated the female student as significantly more competent and hireable than the (identical) male student.  Faculty members also offered more career mentoring to the female student and selected a higher starting salary.

 The gender of the faculty did not affect their ratings, such that female and male faculty were equally likely to exhibit bias in favor of the female student.

Conclusions:

These results suggest that well-documented bias against females does not always exist in academia.

A8. The study for the prediction task in the "bias favoring women" condition in Experiment 3

Is there a gender bias in hiring?

Background:

There are ongoing debates about gender bias in various professions. This study attempts to find out whether there exists a gender bias in hiring in the field of academic sciences or not.

Design:

In the present study, 363 science faculty members (182 women, 181 men) will be asked to evaluate hypothetical narrative summaries of applicants for tenure-track assistant professorships in biology, engineering, economics, and psychology. The applicants will be depicted as having the exact same academic credentials and lifestyles (e.g., single without children, married with children). Importantly, however, applicants will be given a female name in group A, and a male name in group B. This will allow the researchers to assess whether there is any bias in the evaluation process that is solely due to the gender of the candidate.

Each faculty member will be randomly assigned to either group A (female applicant) or group B (male applicant). In both groups, they will be asked to rate the applicant's profile on a scale from 0 to 100. A comparison between average ratings will be conducted between faculty members assigned to groups A and B (i.e. professors who saw the candidate presented as a male and those who saw the candidate presented as a female).

Now please make predictions about the likely results of the study.

What do you think will be the average ratings of the two groups? The natural, linguistic and social facets of gender are intertwined, and together they play an important role in shaping the structure of languages, the social norms and role beliefs about men and women, as well as people's moral attitudes and ideologies. As a linguistic feature, grammatical gender has been argued to have consequences for the mental representations of objects and persons. A wealth of research efforts has been devoted to the question of whether the classification of nouns denoting objects into masculine and feminine gender classes influences language users' conceptualizations of objects. At the same time, the unequal treatment of the masculine and feminine grammatical gender across languages has been questioned as a source and reflection of gender stereotypes and gender role beliefs that contribute to the status quo of gender inequality. Furthermore, people's ideologies and attitudes built on gender stereotypes and social role beliefs show impacts on their perception of gender inequality and their trust in research on gender bias.

In this concluding chapter, I first summarize findings of the three empirical studies presented in previous chapters. Then I discuss the theoretical and empirical implications of the three studies. I will end the chapter by pointing out the limitations of the research and directions for future investigations.

Summary

The first study (Chapter 2) investigates the relationship between language and thought from the angle of grammatical gender, as an attempt to test the Neo-Whorfian hypothesis that language structure influences people's conceptualizations of the world. In this study, I ask if the grammatical gender system of a language has consequences for the speakers' mental that compared to the masculine form, both the double-gender and middot forms increased the perceived proportions of women across the three types of professions. The two gender-fair forms did not differ from each other in terms of increasing women's presence in mental representations.

The observed language effects were not moderated by the gender stereotype of professions.

Consistent with previous research on English and German [START_REF] Braun | Können Geophysiker Frauen sein? Generische Personenbezeichnungen im Deutschen[END_REF][START_REF] Gastil | Generic pronouns and sexist language: The oxymoronic character of masculine generics[END_REF][START_REF] Hamilton | Using masculine generics: Does generic he increase male bias in the user's imagery?[END_REF][START_REF] Irmen | Gender markedness of language: The impact of grammatical and nonlinguistic information on the mental representation of person information[END_REF][START_REF] Martyna | What does 'he'mean? Use of the generic masculine[END_REF], these findings provided further evidence of the impact of gender-fair language in promoting the salience of women in the minds of perceivers.

To establish the consistency of representations, we compared the %-women provided by our participants with real-world estimates obtained in Misersky et al.'s (2013) norming study for each profession. Results of the comparison showed that gender-fair language had varying effects on the consistency of the perceived proportions of women. Both double-gender and middot forms induced consistent representations for gender-balanced occupations; however, they introduced a female bias for male-dominated occupations, demonstrated by the overestimates of %-women compared to the normed data; and finally, for female-dominated professions, the gender-fair forms failed to provide enough boost such that a bias favoring male was still present in participants' estimates. In line with a previous study that investigated only gender-neutral professions in Swedish [START_REF] Lindqvist | Reducing a male bias in language? Establishing the efficiency of three different gender-fair language strategies[END_REF], our results regarding the gender-balanced professions added proof of the existence of a male bias induced by the masculine generics in people's mental representations as well as the efficacy of using gender-fair language in removing such a bias.

In the last study (Chapter 4), we looked at the role of morality in people's differing trust in scientific evidence related to gender discrimination. In Experiment 1, we showed participants attainment. Consistent with the awareness of gender discrimination in society, they are more receptive of research findings confirming the existence of sex-based bias against women. On the contrary, people who do not feel morally engaged in the cause of gender equity are less sensitive to any external biases that may create obstacles in the way to women's success, and in consequence, they tend to discard any information showing the opposite. As demonstrated in Chapter 4, people holding positive attitudes on gender equality find research evidence of gender discrimination against women in STEM fields more credulous than those with negative attitudes on this issue. Accordingly, the individuals who reported moral commitment to gender equity may be advocates of the liberal egalitarian ideology; while the others who were less morally concerned may be proponents of gender essentialism or flexible egalitarianism.

The influence of ideology on individuals' trust calibration can be two-fold. First, if a person's pre-conceptions are built on the accumulation of accurate information, then assigning more trust to new, attitudinal information is not only unproblematic but also efficient, since it would cost us a large amount of time and energy to deliberate over every single piece of new information we encounter. However, if a person's prior beliefs are themselves biased, based on misinformation, as is the case for COVID-19 vaccine opponents [START_REF] Roozenbeek | Susceptibility to misinformation about COVID-19 around the world[END_REF] and global warming deniers [START_REF] Zhou | Confirmation Bias and the Persistence of Misinformation on Climate Change[END_REF], attitude-based evaluations of new information will lead them further away from the truth.

Limitations and Directions for Future Research

To establish the cognitive effect of grammatical gender on object conceptualization, future studies can focus on developing more varied, reliable research methods as the existent literature suggests the lack of valid, reproducible paradigms. For instance, the study in Chapter 2 adopted a word association approach, but more innovative research methods would be a welcome addition.

ABSTRACT

The various facets of gender play an important role in shaping our cultures. People are categorized into males or females based on their biological sex; human languages differ in how gender is encoded in the language structure; and in society, different gender ideologies exist concerning what roles and positions men and women should occupy. The relationships between these facets are often intertwined. In this dissertation, I first investigate the relationship between language and people's mental representations of gender (Chapters 2 and 3). In particular, I ask if assigning grammatical masculine or feminine gender to nouns denoting inanimate objects would make native speakers think of these objects as having "male" or "female" qualities, a language effect as postulated by the Neo-Whorfian hypothesis that linguistic categories affect people's construal of the world entities.

Extensive piloting work on this topic suggests null effects of grammatical gender on speakers' conceptualization of objects. Unlike object nouns, the grammatical gender of person nouns is meaningful in that it has a semantic underpinning (i.e. malemasculine; female -feminine). I then examine the influences of grammatical gender on people's perceptions of male-female distributions across various professions in two experiments, and found that different language forms induce differential male and female associations, some of which are consistent, others biased.