Spiros Kotopoulis

Michiel Postema

Emmet Mc Cormack

Tore Bjørn

Odd Helge Gjertsen

Georg Gilja

Dimcevski

Bjørn Tore Gjertsen

Helge Odd

Gilja

Georg Dimcevski

Ultrasound fights cancer with microbubbles

teaching and research institutions in France or abroad, or from public or private research centers.

This ultimately had the effect of stabilising or decreasing the tumour volumes in 50 percent of the patients and increasing the median patient survival time from approximately 7 months to 18 months.

Future Work

Future work will include performing a larger-scale phase I/II clinical trial with international collaborators, and working to develop a microbubble compound optimised for targeted drug-delivery at low acoustic intensities. We will also seek to fully understand the mechanisms of sonoporation by using advanced mouse models and bioreactors.

Key Points

• e ro o e s r t e ro ont s to onths without increased chemotherapy dosage.


María Isabel Rivas Ginel
email: isabelrivasginel@gmail.com

Sarah Theroine
email: sarah.theroine@u-bourgogne.fr

María Isabel

Rivas Ginel

Machine Translation and Gender Biases in Video Game Localisation: A Corpus-Based Analysis

Keywords: machine translation, neural machine translation, video game localisation, gender biases, corpora

 and extracted the collocations and concordance lines that represented gender identity by analysing the patterns in the source language.

I CONTEXT

The video game industry

As a consequence of the increasing popularity of video games, the demands of the industry in terms of video game localisation to reach a larger public and increase the revenues generated by each game have more than doubled. Conversely, localisers' working conditions have not substantially improved over the last decade and, despite constant technological advances, they continue "to work in a double-blind process (no audiovisual context, no text linearity)" [Merino, 2013, 117]. In other words, localisers are not given access to the game itself and, even in the best conditions, struggle to identify the gender of the character or the addressee, among many other issues.

Motivation

The idea of focusing on the efficiency of Neural Machine Translation (NMT) by analysing gender-related issues in the field of video game localisation stems from three reasons. First, previous research on the degree of adoption of Machine Translation (MT) tools by video game localisers [Rivas Ginel, 2021, 171] has shown that even though MT remains largely unadopted (11,6% of regular users), "66% of agencies and 44% of in-house translation teams expect to invest in [MT] in 2020" [LIND, 2020, 50]. Furthermore, more than 70,37% of video game developers use Unity as their main game engine, which provides localisation management and instant MT options [Rivas Ginel, 2022, 320]. Therefore, it is likely that either developers or translation agencies might use MT and then send the text to video game localisers for postediting to cut costs in a saturated market.

The second motivation behind this study is that the video game industry is moving with the times and increasing the number of female, gender-neutral and non-sexualised characters, leaving behind the image of a predominantly male domain. Although this evolution reflects the present trend in society towards diversity and inclusion, these changes entail new challenges for video game localisers, forcing them to redouble their efforts to avoid gender bias and search for neutral yet natural translations. Moreover, the mechanisms used for inclusivity vary from one language to another, notably with gendered languages such as those from Indo-European countries. Languages such as French, which tend to use masculine grammatical forms, can easily become ambiguous and cause the under-representation of women due to the fact that a pronoun in its masculine form can refer to a group of men, to a mixed-gender group of people, a neutral group of people, or to a person whose gender is not precise nor defined.

The third reason is the increasing number of papers that focus on the performance of NMT systems and explore solutions to reduce gender bias in MT. NMT's performance can be affected by its ability to deal with Language Detection, Natural Language Processing and Natural Language Understanding; well-known notions in artificial intelligence used to detect, understand, and treat natural languages. Furthermore, the efficiency of these tools, especially if the source language is relatively neutral and the target language is grammatically gendered, is highly impacted by the methods used to train the artificial intelligence behind those systems. For example, an NMT system that translates a sentence without gender marks such as "the surgeon is very skilled" will automatically use the masculine form and produce the outcome "le chirurgien est très compétent".

II METHODOLOGY

Choice of systems and games

Systems

We decided to analyse the output of Google Translate and DeepL-NMT-based-as well as SmartCat (to represent Statistical Machine Translation (SMT) tools). As the company explains in their blog [Google AI Blog], Google Neural Machine Translation (GNMT), which is integrated into Google Translate, was developed in 2016 and modified in 2020. It provides language detection and includes various technologies based on Artificial Intelligence that allow it to handle 100+ languages. GNMT uses a hybrid model architecture that replaces the previous RNN-based GNMT model-used to identify data correlations and patterns-with a transformer encoder (that reads the source text and searches for correlations) and an RNN decoder for predictive typing [Google AI Blog]. These hybrid models improve the quality and lower the time of latency. Additionally, the 2020 update allows Google to web crawl using an embedding-based model rather than the previous phrase-based machine translation model of 2016 (dictionary-based crawler), thus improving the quantity and quality of the data and increasing the number of collected sentences [Google AI Blog]. Nevertheless, using parallel (or translated) texts as the linguistic data used in its training phase subjects the availability and quantity of paired texts and languages to their presence on the web, affecting the translation quality. Additionally, GNMT will be more accurate at translating terms or words from a source language to a target language rather than long sentences, entire texts, or complex idioms [START_REF] Yang | A Survey of Deep Learning Techniques for Neural Machine Translation[END_REF].

Once again using the company's own description [DeepL Blog], DeepL uses Deep Learning and Neural Networks and draws the linguistic data used for its training from Linguee, a massive corpus built around manually translated sentences, idioms, and texts. The quantity and diversity of the data utilised account for DeepL's degree of accuracy and performance in specialised domains and its capacity of offering translation alternatives such as synonyms and rephrased options [DeepL Blog]. Additionally, DeepL includes predictive typing which, combined with the translation alternatives function of DeepL, works similarly to translation memories and means that DeepL might be able to memorise the user's translation alternative when the latter changes a term or rephrases the entire sentence. In consequence, the user's alternative would increase the amount of data exploited by DeepL, which already uses Deep Learning to constantly train paired languages, allowing it to train with it and increasing the number of translation alternatives. In terms of MT, DeepL uses an API to provide restricted access to a glossary of terms which increases the accuracy. In addition, this API also limits the length of documents uploaded into DeepL meaning that the text is split into sentences, then translated and finally put back together [DeepL Blog].

Finally, as a representative of MT integrated into Computer Assisted Translation (CAT) tools and an example of SMT we chose SmartCat, which uses Yandex Free by default. This system is not based on translated texts or language rules but upon statistics, which means that the tool uses comparable corpora. SMT analyses source documents in one language and statistically compares them with related documents in another language first; then it gathers, relates, and aligns the data with parallel texts [Yandex Blog]. Another difference is that the system can easily and quickly be adapted when a language faces modifications (spelling, usage, new terms or idioms), which also means that it must be regularly updated to improve its quality. Yandex's language training is built around three models: a translation model, a language model, and a decoder. Those models are used together to sort all terms, idioms, and sentences extracted by language from the comparable corpora to find and match correlations of words, terms or sentences extracted from the parallel corpora [Yandex Blog]. The models draw statistical patterns from a first set of paired sentences and then use another set to constantly recalculate, compare, and match terms to find the more accurate equivalent in the target language. The translation is done by the decoder, which gathers all the translation alternatives for a given sentence or sequence, combines phrases from the translation model and statically classifies them in order of probability [Yandex Blog]. In this sense, the decoder's function can be assimilated to a phrased-based model or a Seq2Seq model. The decoder also uses the translation model to determine the highest probability of equivalence and frequency of use to improve the accuracy and idiomaticity.

Games

The games The Faces of the Forest, The Devil's Womb and DeltaRune were chosen due to the presence of female protagonists, non-binary characters, and non-sexualized characters. All of them are free to play and the .json documents containing the strings were either online or we were granted permission to use them for educational purposes. Given the difference in the number of words between the three documents, we decided to use the entirety of the two first games and their sum's equivalent in the case of DeltaRune. The Faces of the Forest has a little over 2 350 words in total and 11 characters: 4 females, 6 males and 1 non-binary; the main character is Ana. The Devil's Womb, an RPG game with almost 14 900 words and 4 possible endings, has over 30 characters, the protagonist is a female demon named Luna, the characters with the bigger roles are predominantly female (13 females), and there are many demons and minions whose gender was not specified. Finally, DeltaRune has more than 36 000 words (although only the first 17 900 were selected), it is an RPG as well, the main character is nonbinary and has two companions, a female, and a male. The selected part contains 40 characters, 18 of them (the enemies mostly) are non-binary or simply referred to as "it"; there are 15 male characters and 7 female characters.

Process

After establishing the MT systems and the games, the translatable strings were automatically extracted from the .json files using an ad-hoc custom computer programme. We decided to work with this file format since previous research showed that .json files were used by 65,17% of the 379 developers who isolated gameplay text using external files [Rivas Ginel, 2022, 307]. Then, the text was copied and pasted into Google Translate and DeepL and, in the case of SmartCat, the file was uploaded and automatically translated without any other interference in order to automate the process as much as possible. Once again, to reproduce video game localisation practices [Rivas Ginel, 2022, 307], we used Excel files to display the source text and the translations. Afterwards, we created so-called "character bibles" of every game to catalogue characters, display their gender (or lack thereof), and include a screenshot for better reference. The bibles were used when the text was ambiguous and we needed to use walkthroughs to determine the identity of the speaker or the addressee.

Image 1. Excel files and character bibles.

Then, a colour code was created to manually annotate gender-related issues by highlighting the affected cells to provide a visual representation of the errors:

• Blue: use of the masculine for a reference to a female character.

• Red: use of the feminine for a reference to a masculine character.

• Violet: references to non-binary or non-gendered characters.

• Green: wrong use of the masculine for a reference to an object.

• Orange: wrong use of the feminine for a reference to an object. Finally, we proofread, annotated, and reviewed individually at least once every document and then went together through them once more before removing all the lines that did not contain gender-related issues. Unfortunately, this included excluding segments where the translation was so poor that it was impossible to determine the type of error, a fairly common occurrence. Once the non-problematic lines were removed and a final check had been performed, we created a single document per colour for better visualisation and then proceeded to count all the errors per tool and type thrice (to make sure that the resulting number was consistent).

Image 2. Excel files per type of error.

III RESULTS

Colour code

The previous image (Image 2) already shows patterns regarding the type of error and tool: in the case of blue and green errors, we can easily observe a higher number of cells without issues in the column containing DeepL's translation. Conversely, the same tool appears to err more than the rest in the other three categories. If we look at the total number of errors per tool all categories confounded (Table 1), Google made 333 gender-related errors, DeepL made 261, and SmartCat 340. These figures represent 3.03%, 2.38% and 3.1% of the 10 980 segments, respectively. However, it is necessary to point out that SmartCat's translation quality was remarkably low and, thus, we were not able to distinguish the type of mistake made on numerous occasions. Therefore, the percentage of Yandex's errors should be much higher than the one listed above.

Figures 1 to 3 show the results arranged in pie charts and allow us to observe that all three tools had their highest number of errors when dealing with references to female characters (blue) even though DeepL performs better. DeepL shows a relatively higher tendency to favour feminine over masculine and has the highest percentages in the red and orange categories-and the lowest for blue and green. The differences in terms of percentages between the performance of Google and SmartCat are almost negligible although it would seem that SmartCat has a slightly higher tendency to overcompensate in the case of red and orange.

Corpus-based analysis

Subsequently, we performed a corpus-based analysis to provide concrete examples of the issues encountered in each category. First, all the Excel documents were exported into a text file, one for each tool. Then, they were aligned using Aligner and converted into a single multilingual tmx file with all the segments containing errors. Finally, the file was uploaded into SketchEngine to create a parallel corpus that allowed us to analyse the translations and genderrelated errors from a qualitative and a quantitative approach. In order to find relevant tokens for the analysis, a Wordlist search was carried out first to assert the frequency of appearance and use of all the words present in the corpus. After sorting the results, we decided to focus on "Luna", "Ana", "kid and kiddo" and finally on the pronouns "it", "they" and "you". These terms became the starting point of a more in-depth analysis with advanced parameters such as the parallel concordance function using the "simple" or the "lemma" options. Furthermore, the images have been modified post hoc to include the colour code to frame the sentences as a visual aid to highlight the previously discussed categories.

Nouns

The token "Luna" (the protagonist of The Devil's Womb) refers to a feminine character and thus, in French, the pronouns and adjectives must agree with it if it's the subject of the sentence. However, even if Google Translate and SmartCat both detected that Luna was the subject, they didn't apply the rule as there wasn't any other gender reference in the original and, by default, transformed feminine into masculine. On the other hand, DeepL did not make mistakes in this particular case (Image 3).

Image 3. Token "Luna".

The token "Ana" (the protagonist of The Faces of the Forest) predictably shows the same results. In this case, Google Translate made three mistakes, SmartCat had it all wrong, and DeepL proved to be more efficient with only one mistake. In these sentences, as both the name of the protagonist and its coreference-the pronoun "I"-were present, the probability of gender-related errors should have been reduced. However, the results show the contrary and indicate that DeepL seems to be more performant than its competitors in terms of analysing the context and translating accordingly (Image 4).

Image 4. Token "Ana".

By using an advanced lemma parallel concordance for "kid", SketchEngine sorted all the results for the tokens "kid" and "kiddo", which serve as coreferences to various characters in DeltaRune and "Ana" in The Faces of the Forest (said by Ana's grandmother and a neighbour). These terms were problematic for every tool and were automatically translated using the masculine, being easily misled when processing English due to its gender-neutral form. Incidentally, SmartCat's results for "kiddo" were too corrupted and cannot be compared to the other tools since the system did not even translate the term into French (Image 5). Additionally, the lines framed in violet, from DeltaRune, illustrate the intentional use of non-binary English. This decision, clear for a human translator, would have entailed using a neutralisation strategy or inclusive writing in French since "gamin", "petit" and "le gosse" are gendered.

Image 5. Tokens "Kid & Kiddo".

Pronouns

In the following screenshot (Image 6), we can see that DeepL was the only tool that wrongly translated the pronoun "you". In the first example, even though it handled "Luna" properly, it made a mistake while translating "Luna tried talking to you, but you were so nervous". In this sentence, "you" is a coreference for the character Curly-a witch-and the adjective "nervous" should be feminine. In the final line, there is no explicit grammatical gender in the sentence although, if we analyse the context, we can observe that the pronoun "you" refers to an unnamed male demon. Nevertheless, as both Google Translate and SmartCat translated it by "vous" it is not possible to define whether or not they would have been misled too. Image 6. Token "You".

The pronoun "it" was consistently mistranslated by Google and SmartCat. The first sentence, "it got me a little worried", shows that Google and DeepL analysed the sentence perfectly and produced idiomatic solutions: "Cela m'a un peu inquiété" or "ça m'a un peu inquiété" respectively. In the second sentence, "I hope you find it useful", we can observe that the only system that took the context into account correctly was DeepL since the pronoun "it" refers to the company of a dog (without directly referring to the dog) and using the masculine article "le" is not appropriate. The third sentence, even though similar in construction to the first one, was correctly translated by both DeepL and SmartCat but not by Google. The seven next sentences, where "it" refers to a "key" and a "flower" (both feminine in French) show that Google and SmartCat translated the pronoun almost every time using the male article "il". To sum up, Google and SmartCat made respectively 9 and 8 gender mistakes on 10 randomly chosen sentences while DeepL did not make any mistakes. In addition, we have to highlight that SmartCat translated "it cannot be told" into "Cela ne peut pas être indicible" which does not make sense, making the sentence potentially irrelevant for this analysis.

Image 7. Token "It".

The translation of the pronoun "they" with little or no context is a recurrent issue in human translation as it can convey the notion of a group of people, objects, or a neutral form. In the following sentences (Image 8), "they" was the coreference for a group of female demons in The Devil's Womb. Both Google and SmartCat applied the grammatical rule of male as a generic and only DeepL succeeded in translating all the sentences correctly, showing once more that it is more efficient in analysing and memorising the context and the subject of the sentence. Finally, the last line shows that Google Translate and SmartCat failed to recognise that "they" referred to the Demon Kings and used the feminine.

Image 8. Token "They".

CONCLUSION

Creating this corpus allowed us to compare the use of gender in the source texts with the raw output of various MT systems to visualise the semantics, syntax, and linguistic differences between a neutral language such as English and a gendered language. By cross-referencing the information extracted from this corpus, we were able to determine the efficiency of each tool, how they analyse the context, their accuracy, and the quality of their translation. As such, DeepL has proved to avoid many gender biases while being more efficient than Google and SmartCat. In addition, even if Google uses NMT technology, our analysis shows that its architecture and models are closer to SmartCat's. On the other hand, DeepL seems more accurate and fluent, surpassing Google thanks to its use of Deep Learning, as we have seen across the paper. Recent approaches in Neural Machine Translation show that integrating explicit gender inflexion tags into NMT systems reduces the number of gender biases, especially when translating sentences where the gender referent (pronoun) is identified [START_REF] Saunders | Reducing Gender Bias in Neural Machine Translation as a Domain Adaptation Problem[END_REF]. A similar method, incorporating a 'speaker gender' tag into the training phase of MT systems, has also been developed to convey gender at a sentence level [START_REF] Vanmassenhove | Getting gender right in neural machine translation[END_REF]. Finally, another approach consists of adjusting the word embedding of NMT systems to reduce gender bias. Future research will focus on asserting the tools' bias in the context of gender-neutral choices by analysing the results for the token "Kris" (a non-binary character) in-depth as well as all the other errors in the violet category. Even though nowadays we can observe a higher demand for inclusivity and non-binary solutions, players are less familiar with inclusive writing, neutral phrasing or even gender-neutral pronouns, which could negatively affect the flow of the text and the player's immersion. The key factors of the use of inclusive language in video games are the client's intent, their perception of diversity and inclusivity along with the localisers' decisions and skills. The use of inclusive language techniques and constructions requires high awareness from developers and localisers, however, the audience's reception must be taken into account and the topic should be researched further. Furthermore, training a specific MT system applying gender-neutral tagging to indicate neutral referents in the field of video game localisation remains an interesting avenue for future research. Finally, reproducing the experiment with the latest upgrades of the same tools to observe their evolution compared to the April 2021's versions would allow us to examine the results of Deep Learning.

Figures 1

 1 Figures 1 to 3. Distribution of errors per tool.

http://jdmdh.episciences.org eISSN 2416-5999, an open-access journal https://doi.org/10.46298/jdmdh.9065 Table 1. Percentage of errors per tool and category.

Journal of Data Mining and Digital Humanities http://jdmdh.episciences.org eISSN 2416-5999, an open-access journal https://doi.org/10.46298/jdmdh.9065


Meredith Root-Bernstein

Creative Imagination and Practice as Embodied Cognition: Towards the Education of Homo Synosius

What does it mean to make and create? What does it mean to understand? Are these discrete processes-or parts of a larger whole? We concern ourselves here with the disconnect between personal, intuitive ways of knowing and public, symbolic forms of communicating what is known. Understanding, which we define as the ability to implement knowledge for practical purposes, requires both. We argue that the break between theory and practice can be healed by considering learning and creating as cognitive processes deeply embedded in embodied cognition.

In particular, attention to mental "tools for thinking" provides a vocabulary for situating creative processes within that larger framework-and for spanning the concerns and interests of various disciplines researching, through various methodologies, a range of issues related to three focal thinking skills: imaging, empathizing, and body thinking. Our neologism, Homo synosius, describes both the creative individual and our creative species as a rational being and a maker simultaneously, one whose sensually and emotionally embodied knowledge yields actionable and novel understanding.

Creative Imagination and Practice as Embodied Cognition:

Towards the Education of Homo Synosius by Meredith Root-Bernstein, Michele Root-Bernstein and Robert Root-Bernstein What does it mean to make and create? What does it mean to understand? Are these discrete processes-or parts of a larger whole? In search of a starting point, consider this real-life scenario: A group of middle-school teachers are given instructions about how to build mobiles as an exercise for developing basic knowledge about the physics of levers. Half the teachers are first taught how to build the mobiles and then asked to explain the physical principle governing the construction. The other half are given the theory first and then asked to build their mobiles.

The majority of those who could build mobiles cannot explain how they work while a majority of those who can explain the theory are unable to build a functioning mobile. This is not a what-if situation, but a real-life one. Some thirty years ago, in her studies of classroom teaching and learning, [START_REF] Bamberger | The laboratory for making things[END_REF] put her finger on the crux of the matter that concerns us here, which is the disconnect too often experienced in our modern world between personal, intuitive ways of knowing and public, symbolic forms of communicating what is known. Understanding, which we define as the ability to implement knowledge for practical purposes, requires both. Here we argue that the break between theory and practice can be healed by considering learning and creating as cognitive processes deeply embedded in bodily understanding characterized by knowing what we feel and feeling what we know.

In our studies of learning and creating, we have consistently found that creative individuals, i.e. those with proven track records of productive thinking, express reliance on a common set of imagistic, sensory, and embodied thinking skills or "mental tools" [START_REF] Root-Bernstein | Sparks of Genius: The Thirteen Thinking Tools of the World's Most Creative People[END_REF]. Tools for thinking include observing with all one's senses, imaging sights, sounds, smells, and so forth, abstracting out essential information, recognizing and forming patterns, empathizing with both animate beings and inanimate objects, as well as body thinking with muscle tensions and emotions. These and other thinking tools enable creators from all walks of life to initiate problem finding and problem solving in the absence of words, numbers or other symbolic signifiers. The result is a highly idiosyncratic, personal understanding distinct from and antecedent to public communication and discourse [START_REF] Polanyi | Personal knowledge. Towards a post-critical philosophy[END_REF].

Attention to lived experience with tools for thinking thus provides a vocabulary for situating a great deal of creative phenomenology within the larger framework of embodied cognition. According to [START_REF] Wilson | Six views of embodied cognition[END_REF], "embodied cognition holds that cognitive processes are deeply rooted in the body's interactions with the world…" (p. 625). Many of our cognitive activities, she continues, "bring sensory and motor resources to bear on mental tasks whose references are distant in time and space or are altogether imaginary… [or] in the form of mental simulations" (p. 635). Little of the literature on embodied cognition has directly addressed creative practice per se [START_REF] Stanciu | Embodied creativity: A critical analysis of an underdeveloped subject[END_REF]. Yet anecdotal accounts by innovative makers and doers describing the phenomenology of pre-linguistic, pre-symbolic thinking make it possible to consider the creative individual as not just embodied, but also embedded in a physical world, enactive with that world, and extended through their senses and actions through that world [START_REF] Malinin | How radical is embodied creativity? Implications of 4E approaches for creativity research and teaching front[END_REF]. As [START_REF] Anderson | Embodied cognition: A field guide[END_REF] notes, embodied cognition as a field of inquiry "focuses attention on the fact that most real-world thinking occurs in very particular (and often very complex) environments, [and] is employed for very practical ends…" (p. 1). Among these ends, we assert, are the cognitive territories of problem-raising and problem-solving. Here we look at three thinking tools-imaging, empathizing, and body (kinesthetic and proprioceptive) thinking -that uniquely prepare individuals in the arts, sciences, and social sciences to navigate those terrains for creative outcomes.

Imaging

Imaging is the ability to recreate sensory impressions and feelings mentally in the absence of extrinsic or direct physical stimulation from our eyes, ears, nose, tongue, hands or body. We can recall the taste of the eggs we had for breakfast, for instance, or the song of the chickadee outside our window. When we think of a close friend, a visual image of their face flashes across our inner eye. Imaging is tied to that larger web of cognitive skills we call imagination, which generally refers to our mental images and conceptions, but also to what we can do with those images. We can alter, combine, synthesize, and otherwise manipulate sensory inputs to form images of things never wholly perceived before, by us or others. We may plan for the future with a "mental rehearsal" of actions. We may "reverse engineer" from present evidence what happened in the past, sight unseen. We may conjure things that do not yet exist or never will, as in make-believe play or daydreams. Imaging is a common and commonly shared personal, non-symbolic skill. Yet it can also purposely serve in the creative generation of scientific ideas, artistic inspirations, and other problem-probing insights.

Take the set of tracks in snow provided in Figure 1. Who or what left these prints? To essay an answer is to imagine-or more precisely, to image-certain animals engaged in a series of actions that "tell a story." The well-known American industrial designer George Nelson, for many years director of furniture design for Herman Miller, spoke of deliberately relying on images and visual narratives or "fantasies" to guide research: "If you deal with fantasy as productive input…you find that fantasy becomes a component in a whole process, because a fantasy can give you certain pictures which then connected to reality, can become a plan, and plan can be intellectually worked out and it could be made to become a reality" (cited in Rosner & Abt, 1970, p. 260). Many scientists and writers share this reliance on imaging, as did the pioneering plant adaptation researcher, Monica Gagliano. Participating in ritual experiences with indigenous peoples, she experienced interactions with hallucinations of plant spirits that revealed to her, without using words, research questions about plant behaviour and the experiments necessary to test them [START_REF] Gagliano | Thus spoke the plant[END_REF].

Empathizing

Empathizing involves a Zen-like "becoming of the thing" under study, an integration of 'I' and 'other'. It involves our capacity to experience for ourselves the emotional valence of behaviors and processes we see at some remove. In the last few decades, neuroscience has confirmed that the brain has "intricate circuitry for understanding other people's thoughts and feelings" [START_REF] Zimmer | A career spent learning how the mind emerges from the brain[END_REF]. To see a picture of someone stubbing their toe is to activate areas of the brain involved when you stub your own toe. As Michael Gazzaniga, a veteran founder of cognitive neuroscience, notes, "When I have an empathetic moment, I literally feel your pain" (cited in [START_REF] Zimmer | A career spent learning how the mind emerges from the brain[END_REF].

If our capacity to empathize is hardwired in the brain, our interpretation of our empathic experience can be trained to many creative purposes in the arts, sciences, and social sciences [START_REF] Root-Bernstein | Sparks of Genius: The Thirteen Thinking Tools of the World's Most Creative People[END_REF]. We take it as given that actors, novelists, painters and healthcare providers feel the pain of other people. It is only recently, however, that we have come to accept subjective feelings of the body in scientific thinking. Late 20 th-century advances by primatologists such as Jane Goodall, Shirley Strum, Robert Sapolsky and Franz de Waal, for instance, have been built on careful recognition of empathic responses to chimpanzees and baboons as a means of generating testable hypotheses about intentionality and behavior.

The same might be said of the embodied thinking practice of scientists such as Nobel Prize winner Barbara McClintock, who made "friends" (her word) with the chromosomes she studied, or her fellow Nobel laureate, chemist Peter Debye, who instead of trying to force carbon atoms to do what he wanted them to do, asked them instead "what did [they] want to do?" [START_REF] Root-Bernstein | Sparks of Genius: The Thirteen Thinking Tools of the World's Most Creative People[END_REF]. Similar empathic responses come into play in interpreting Figure 1. What do the animals we image want to do-and why? Making sense of the tracks they leave in the snow requires that we feel for ourselves something of their purposes. Indeed, understanding the other, whether inanimate or animate, animal or human, requires a heightened awareness as to how the empathic emotions affect the researcher's field experience and its interpretation (Kucklick, 2001;[START_REF] Jokinen | When bodies do not fit: an analysis of postgraduate fieldwork[END_REF][START_REF] Stodulka | Affective scholarship: Doing anthropology with epistemic affects[END_REF]). Learning to be empathetic means learning not to endow the 'other' with one's own feelings, but rather to gain perspective on how to feel like the 'other'.

Body Thinking

Empathizing is clearly related to thinking with the body. Body thinking may involve not only emotions or feelings such as pain (the typical focus of empathy), but a wider set of body sensations. It also goes beyond representation of bodily feeling and emotion to encompass highly metaphorical or abstract thinking [START_REF] Myers | Rendering life molecular. models, modelers, and excitable matter[END_REF]. Reflect on our immediate mental response to the following question: When buttoning a shirt, which hand pushes the button through the hole? Chances are the "answer" does not come initially in words. It comes, rather, as an imagemaybe visual, maybe muscular-of the button, the hole, the hand (right or left?) or a feeling of movement (or movement intention) in the hands. This is kinesthetic and/or proprioceptive thinking, the way we know a thing or process in images tied up with tensions, postures, movements, and core feelings of the body. It is what Auguste Rodin had in mind when he sculpted his famous "Thinker," a man cogitating not just with "brain," but, as Rodin expressed it, with "knitted brow" and "every muscle of arms, back and legs…" (Root-Bernstein & Root-Bernstein, 1999) By the same token, we may use "every muscle" in our imaginative efforts to comprehend the animal tracks in Figure 1. Can we feel our way into what happened here? Can we reenact the encounter?

There is a physical logic to body thinking not readily expressed in words or numbers, yet capable of communicating information intuitively. Dancers rely on this logic to transmit both narrative and emotion. Scientists use it to explore the physical possibilities of interaction and process. Bacteriologist John Cairns provides an example. Working on how bacterial genes regulated each other to perform specific functions, he came up with what he thought was an elegant experiment. He explained his plans to a colleague, Bob Edgar, on the way, as it just so happened, to a square dance: "Edgar proceeded to convert my beautiful design into instructions for an imaginary square dance, prancing from one side of the road to the other as he acted out a dance of bacteriophage particles, each marked with a different isotope, pairing and separating, moving in lines, re-assorting themselves and so on. This lasted for the 300 yards between his classroom and the lawn with its waiting human dancers, where he plunged off into the golden twilight" (Cairns, 2004, 23).

In the time it took to dance those three football fields, Cairns realized two things: First, that every experiment involves a series of manipulations of materials that interact in some way that the investigator must not only foresee but embody. Second, that his experiment wouldn't work, for it required some parts of the genes to be in two places at once. Body thinking his way through the experimental protocol had saved him weeks of useless lab work [START_REF] Cairns | The usefulness of parody[END_REF].

For Cairns, as well as others, the body can function as a "tool" for probing experience to some creative purpose. It may be metaphorically used to probe what we think about what we know. Indeed, one of us (Meredith) recruits the bodily feelings associated with crossing boggy terrain while writing papers such as this one. Constructing her argument is like trying to find a path through a wetland whose topography and texture constantly reveals itself as she "moves." Shuffling, teetering, jumping, or stomping through the landscape, she gets from one logical point to another. As she puts it, "Sometimes you see a way forward from a raised area, but as you cut your way through the dense reeds of evidence, you become lost. When you return to the wetland under new conditions, sometimes the landscape has changed and new routes to new positions reveal themselves to the probing body." See Figure 2 for how she renders this experience as a visual image.

Embodied Cognition: Combining Imaging, Empathizing, and Body Thinking

As [START_REF] Varela | The embodied mind, cognitive science and human experience[END_REF] point out, embodied cognition not only depends on the experience of the body and its sensorimotor capacities, these capacities have impact on and are embedded in biological, psychological and cultural contexts. Consider how the digital structure of the hand inextricably links with the development of mathematics. Most societies around the world count in blocks of ten, reflecting the number of fingers on both hands. But what if we had six fingers on each hand? (See Figure 3.) Only one in 500 babies are born with this form of polydactyly, but that doesn't keep dozenal (base 12) enthusiasts around the globe from arguing that counting on twelve fingers affords us a far more efficient mathematics, with potentially profound consequences for human numeracy [START_REF] Anonymous | Duodecimal. Wikipedia[END_REF][START_REF] Wolchover | What If Our Hands Had 6 Fingers? LiveScience[END_REF]. Think as well of how our technologies (such as the keyboard upon which we are composing this chapter) might be configured differently for a dozenal individual. The body as a whole must similarly influence our phenomenological understanding of creative thinking skills and their incorporation within larger, theoretical considerations of embodied cognition. Indeed, the methodological concerns of various disciplines may filter and account for the body's experience and the creative use of imaging, empathizing and the feelings of body thinking in various exploratory ways. Within the fields of anthropology and human geography, for instance, some social theorists interested in certain aspects of embodied cognition have talked about technology as forms of human "prostheses," that is, as extending the human body and with bodies, such tango dancers, horse and rider, or courting birds, integrate their body images. There is clear scope for further exploration of the cognitive aspects of embodied thinking, and their implications for how we understand autonomy, animism, and sociality beyond the simply human.

Anthropologists have also paid close attention to how bodies incorporate and enact social and biological phenomena [START_REF] Myers | Rendering life molecular. models, modelers, and excitable matter[END_REF]. Kucklick (2001) traces the history of the body within fieldwork. The 19 th -century polymath John Tyndall "made his body into a research tool, perilously edging his way over deep glacier crevasses in order to prove that glaciers moved in their beds as solid objects" (Kucklick, 2001 p. 13). As fieldwork emerged as part of science practice in the 19th century, it was validated as a form of bodily conditioning leading to moral development and self-control (Kucklick, 2001;[START_REF] Brooks | The road to character[END_REF]. Suffering leading to bodily and emotional control allowed sciences such as ethology and anthropology to justify interpretive and individualistic field methods (Kucklick, 2001).

Contemporary anthropologists and geographers interact with their research object through the interface of their own body as a social subject (Kucklick, 2001). Using one's own body as a way to interrogate other societies requires the development of reflexivity and awareness about how one's own emotional/physiological condition, observable body, socioeconomic position, and so on, affect the kinds of experiences one has and how one interprets those (see Kucklick, 2001;[START_REF] Jokinen | When bodies do not fit: an analysis of postgraduate fieldwork[END_REF][START_REF] Thompson | On writing notes in the field: Interrogating positionality, emotion, participation and ethics[END_REF]. Indeed, although one might assume that categories like class or education are not bodily issues, they are socialized, internalized and expressed through posture, movement, discomfort or ease, use of space, modes of physical interaction and other unconsciously acquired dispositions of the body -what sociologist Pierre Bourdieu called hexus and habitus (1972;[START_REF] Bourdieu | Distinction: A social critique of the judgement of taste[END_REF].

Anthropology and geography have also developed a large literature on the attention to emotion-both the researchers' and the interlocutors'-during fieldwork (e.g. [START_REF] Knudsen | Affective methodologies: Developing cultural research strategies for the study of affect[END_REF][START_REF] Stodulka | Affective scholarship: Doing anthropology with epistemic affects[END_REF]. Emotions can be signs that something matters-while figuring out what it means may be an issue for analytical thinking (cf. [START_REF] Despret | Responding bodies and partial affinities in human-animal worlds[END_REF]. The reverse might also be true-if an event that is represented as mattering a great deal occurs, the emotions on experiencing it (fear? relief? embarrassment?) might help to clarify what exactly it means to oneself and to others. Attention to emotion can aid empathy, and thus interpretation of social situations.

Emotions are an important aspect of cognition that cannot be ignored in analysis of the meanings and importance of situations. [START_REF] Damasio | Descartes' error: Emotion, reason, and the human brain[END_REF] demonstrated that individuals who lacked emotional affect cannot be strategic. The deficit was not cognitive as they could be taught games such as poker and accurately analyze their chances of winning any particular hand. However, they always lost because they did not care about the game. Feelings and emotions imbue knowledge with value. The anthropological literature, in showing how certain social values are expressed by certain uses of the body, also extends the understanding of embodied cognition to include not only the recognition of other's values, but the ways in which our own values cannot be divorced from our interactions in the world.

We would suggest that by thinking of each of these embodied cognition issues as being composed of thinking practices including imaging, empathizing, and body thinking, communication between different disciplines can be facilitated. For example, when talking about our ability to dance the tango or bacterial processes, to discern the flow of glacial ice underfoot, or to probe the tacit meanings of ritual, we might ask how subconscious dispositions of bodily hexis express or constrain our ability to image, empathize with, or use body thinking for creative purposes.

Conclusion: The Embodied Education of Homo Synosius

In their study of creative thinking, Root-Bernstein and Root-Bernstein (1999) came across so many artists, writers, scientists, and inventors referring to sensory imaging, emotional empathizing, and proprioceptive thinking with body and tool, as to suggest that most successful thinkers access this terrain as regularly as they can, wielding access to their embodied thinking as problem-exploring/problem-solving tool (see also [START_REF] Root-Bernstein | A review of studies demonstrating the effectiveness of integrating arts, music, performing, crafts and design into science, technology, engineering, mathematics and medical education. Part 2: Controlled studies of transdisciplinary tools-for-thinking bridges for arts-science pedagogy[END_REF]. Absent the means of communicating embodied insights and problem solutions from mind to mind, however, they must engage as well in compositional processes capable of enacting and communicating complex information. Thus, Einstein, whose creative thinking was solely of an imagistic and bodily sort, spoke of the arduous, secondary step of translating the visual, aural, kinesthetic and proprioceptive imagery and insights of his thought experiments into mathematical descriptions of reality [START_REF] Root-Bernstein | Sparks of Genius: The Thirteen Thinking Tools of the World's Most Creative People[END_REF].

The same two-step process from imaging to communicating characterizes creative work in other fields. For the poet Stanley Kunitz, a poem began deep in the ocean of images, "even before it is ready to change into language…" (cited in Campbell, 2000, p. 16). Poets and writers spend years learning to communicate what they have imaged to others, to say in words "what cannot be said in words," as the novelist Ursula LeGuin put it (1976, introduction). The need for translation from image to word also goes the other way, from word to image. For the teachers in Bamberger's study, abstract verbal or mathematical understanding of mobiles faltered unless and until it could be instantiated. As novelist Vladimir Nabokov observed, the "hand" supports "the thought" (1973, p. 311). Le Guin's paradox is one that creative individuals wrestle with every day-how to mesh the embodied thinking of sensory imagination and intuition with rational modes of composition and discourse. Education must also come to grips with the conundrum if it aspires to nurture creative practice. This means imaginatively expanding curricula. Build mobiles as an introductory ground for learning how to understand and express relevant physical principles.

Hunt for signs of animal life before symbolizing their ecological relationships. Pose the what-ifs of speculative worlds-as must attend, for instance, the imaginative inhabitation of a different body-as a spur for exploring what is known about the one at hand. Words and mathematics are only useful in so far as they communicate how embodied experience links to accumulated knowledge. Equally, an embodied competence without access to some symbolic form of articulation is also incomplete because it cannot be distilled into actionable principles. A full and active understanding requires the linkage of signs or symbols with sensory inputs by means of actions (Aristotle, 345 BCE;[START_REF] Anderson | Embodied cognition: A field guide[END_REF]. Active understanding emerges only when mind and body are fully integrated through performance-embodied, embedded, enacted and extended [START_REF] Malinin | How radical is embodied creativity? Implications of 4E approaches for creativity research and teaching front[END_REF]. We have complete understanding of things only when our sensations, feelings, desires, wants and actions are fully integrated with our knowledge of what is possible and our analysis of what is necessary or desirable.

In conclusion, we offer a revision of our potential as a species. As creative problemraising and problem-solving creatures, we are neither Homo sapiens ("rational human") or Homo faber ("the maker"), but a synthesis of both: Homo synosius. We derive the word synosius from

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it, human sensory and functional capabilities [START_REF] Thrift | Non-representational theory: Space| politics| affect[END_REF]-the book as memory, the tool as augmented hand, the x-ray as extended vision. Rather than seeing technologies and crafts as prostheses of the human body, [START_REF] Ingold | Making: Anthropology, archaeology, art and architecture[END_REF] sees them as separate entities with which, through attention, empathy, and skill, we come to collaborate. Whether as prosthesis or collaboration, it is certainly the case that surgeons "feel" with the scalpel as if with their own fingers; the same projection of human sensory capabilities holds true for surgical tools manipulated at a distance, as in robotic surgery.

Why this should be so has much to do, from a neurocognitive perspective, with the way the brain uses both proprioceptive feedback and visual cues to form a "body image," which can incorporate things like clothes, tools, and prosthetic limbs [START_REF] Holmes | Beyond the body schema: Visual, prosthetic, and technological contributions to bodily perception and awareness[END_REF]. Things that are permanently or semi-permanently attached to our bodies can become cognitively incorporated into the body. [START_REF] Holmes | Beyond the body schema: Visual, prosthetic, and technological contributions to bodily perception and awareness[END_REF] describe a case in which a woman, after a stroke, did not recognize her left hand as her own. She also could see and describe a ring on her left hand but did not recognize or associate biographical memories with the ring, until it was moved onto her right hand. The ring had suffered the same cognitive dissociation as the hand.

Research on macaques has also shown that the visual and sensorimotor neural representations of tools "extend" to cover the extent of the tool [START_REF] Iriki | Self-images in the video monitor coded by monkey intraparietal neurons[END_REF]. This has been described as a multisensorial integration of the representation of the space around the body [START_REF] Martel | Tool-use: An open window into body representation and its plasticity[END_REF]. When tools are used regularly, as with the probing cane of a person who is blind, the extension of the peripersonal space to incorporate it is permanent [START_REF] Martel | Tool-use: An open window into body representation and its plasticity[END_REF].

The neurocognitive literature does not focus on using tools that require skill, or on the control of semi-autonomous and dynamic processes like flying kites and making a pot on a pottery wheel. We know even less about the neurocognitive issues around how two collaborating synosia, a neologism introduced in Sparks of Genius. Built from the words synaesthesia (combining of all senses) and gnosis (knowledge), synosia refers to the integration of the body's sensorium with the mind's multiple ways of knowing. Homo synosius is both a rational being and a maker simultaneously, but more importantly, a creator whose sensually and emotionally embodied knowledge yields actionable understanding.