Camille Debras
email: cdebras@u-paris10.fr

Stance-taking functions of multimodal constructed dialogue during spoken interaction

Keywords: multimodality, enactment, stance-taking, constructed dialogue, interaction

Based on qualitative analyses of spontaneous interactions between native speakers of British English, this paper argues that speakers' use of multimodal enactment during constructed dialogue can be motivated by stance-taking processes. Speakers use multimodal enactment (i.e. change in voice pitch, pantomime) when dis(s-)tancing themselves from a stance attributed to an absent subject. When endorsing an absent subject's stance, they don't use multimodal enactment, thereby iconically representing the outside stance as their own. Theoretically, this study re-evaluates Du Bois's (2007) Stance Triangle as a Stance Tetrad: speakers simultaneously position themselves with respect to an object and both present and absent subjects.

Introduction

As remarked by Tannen [START_REF] Tannen | Introducing Constructed Dialogue in Greek and American Conversational and Literary Narratives[END_REF], reported speech is an inaccurate term to describe direct discourse attributed to another source than the speaker here and now. There is no point, she explains (among other scholars), in assessing the truthfulness of the representation of speech by direct discourse: the original discourse can usually not be accessed and the direct discourse is nothing but a production of the speaker here and now. When using direct speech, the speaker is not so much representing somebody's speech as presenting discourse in the form of "constructed dialogue" [START_REF] Tannen | Introducing Constructed Dialogue in Greek and American Conversational and Literary Narratives[END_REF]. Constructed dialogue can be used for a much larger range of pragmatic functions than just referring to speech, just as direct speech can sometimes be used to characterize non-speaking entities, like objects, through fictive interaction [START_REF] Pascual | Fictive interaction. The conversation frame in thought, language and discourse[END_REF].

Direct speech dissociates the speaker's voice from his responsibility: almost paradoxically, the speaker uses his own voice to present speech as not being his own. This aspect of direct speech has been studied from a rich variety of approaches. Goffman's [START_REF] Goffman | Interaction Ritual: Essays on Face-to-face Behavior[END_REF] sociolinguistic description of institutional speech distinguishes author (the source of the speech), animator (the person who is voicing the speech) and principal (the person or entity that is responsible for the speech). A large body of research in French enunciative linguistics has accounted for such polyphony with a distinction between locutor -the speaking voice, and enunciator -the origin of the speech, which can be distinct from the speaker himself ( [START_REF] Authier-Revuz | Hétérogénéités(s) énonciative(s)[END_REF], [START_REF] Ducrot | Quelques raisons de distinguer "locuteurs" et "énonciateurs[END_REF], [START_REF] Celle | Tense, Modality and Commitment in Modes of Mixed Enunciation[END_REF] among others). A locutor's utterance can hence contain multiple enunciators. This distinction has a lot in common with Martin & White's appraisal theory (anchored in systemic-functional linguistics) [START_REF] Martin | The Language of Evaluation: Appraisal in English[END_REF]. Martin & White's Bakhtinian approach considers that a speaker's utterance always exists against a backdrop of other possible utterances on the same theme. Since "whenever speakers (or writers) say anything, they encode their point of view towards it" ( [START_REF] Stubbs | A matter of prolonged fieldwork: notes towards a modal grammar of English[END_REF]: 197), any utterance makes a speaker agrees or disagrees with the explicit or potential perspectives of present interlocutors and/or absent parties. From this perspective, direct speech is only a case where the inherently dialogical nature of discourse is made explicit.

In the course of spoken interaction, constructed dialogue can be supplemented by non-verbal components, such as a change in voice pitch and/or coordinated body movements: constructed dialogue can turn into multimodal enactment ([9], [START_REF] Sidnell | Coordinating gesture, talk and gaze in reenactments[END_REF], [START_REF] Streeck | Gesturecraft: The manu-facture of meaning[END_REF]). Indeed, if gestures are often used to represent objects, one of the most familiar things to represent with a talking body is another talking body ([12]: 16).

Enactment is a well-documented phenomenon in Sign Languages, under the name of role shift ([13] on ASL), personal transfer ([14] on LSF) or constructed action ([15] on Auslan), but has received less attention in spoken languages (apart from [START_REF] Sidnell | Coordinating gesture, talk and gaze in reenactments[END_REF], [START_REF] Stec | Meaningful shifts: A review of viewpoint markers in co-speech gesture and sign language[END_REF]). This paper aims to show that multimodal enactments during constructed dialogue in the course of interaction do not only fulfill representational functions but also stance-taking ones. More specifically, a speaker's use of voice change and bodily enactment can be used as a resource to take a stance simultaneously with respect to present subjects (interlocutors) and absent ones.

Stance has been studied from various approaches in corpus linguistics, and broadly corresponds to "a display of a socially recognized point of view or attitude" ( [START_REF] Ochs | Constructing Social Identity: A Language Socialization Perspective[END_REF]). When speakers take stances, they simultaneously position themselves with respect to a discourse object and an interlocutor: "stance is a public act by a social actor, achieved dialogically through overt communicative means, of simultaneously evaluating objects, positioning subjects (self and others), and aligning with other subjects, with respect to any salient dimension of the sociocultural field" ( [START_REF] Bois | The Stance Triangle[END_REF]: 163). Studying stance is hence fundamentally concerned with how propositional content is always intermingled with the expression of intersubjective, interpersonal relations. More particularly, this paper argues that agreeing or disagreeing with absent subjects is another basic dimension of stance-taking.

Based on qualitative analyses of spontaneous interactions between native speakers of British English, I analyze how speakers' use of multimodal enactment during constructed dialogue is motivated by stance-taking processes as follows. (i) Speakers use multimodal enactment (i.e. change in voice pitch and pantomime) when they distance themselves from a stance attributed to an absent third party by constructed dialogue. (ii) Speakers don't use multimodal enactment (i.e. keep their usual gesturing style and default tone of voice) when they endorse a stance attributed to an absent third party by constructed dialogue.

Corpus and Method

Corpus

The corpus under scrutiny is a collection of videotaped semi-guided discussions between pairs of friends (2 hours and 20 minutes in total), recorded in Spring 2011. All 16 speakers (7 male, 9 female) are university students (aged 18-30) who are native speakers of British English. During approximately 15 minutes, the participants pick and discuss questions bearing on environmental issues, a classical topic in applied ethics ( [START_REF] Marzano | L'éthique appliquée : De la théorie à la pratique[END_REF]) that invite them to take stances, evaluate, and position themselves with respects to norms and knowledge. All participants signed informed consents before participating in the data collection ( [START_REF] Mondada | Constitution de corpus de parole-eninteraction et respect de la vie privée des enquêtés : une démarche réflexive[END_REF]), and are anonymously identified by trigram code names. Speakers sat in the familiar setting of a college supervision room and were free to skip a question if they wished. Recording pairs of friends made the conversation spontaneous and familiar and sitting on chairs did not prevent them from moving and gesturing freely from the waist up. Although using multiple cameras allows for collecting visual information ( [START_REF] Mondada | Video Recording as the Preservation of Fundamental Features for Analysis[END_REF]) these naturalistic conversations were filmed with just one camera, which is less intrusive.

Method

The chosen approach is founded in multimodal interaction analysis ( [START_REF] Norris | Analyzing Multimodal Interaction: a methodological framework[END_REF], [START_REF] Stivers | Introduction: Multimodal Interaction[END_REF], [START_REF] Mondada | Participants' online analysis and multimodal practices: projecting the end of the turn and the closing of the sequence[END_REF]). For each occurrence of constructed dialogue in the corpus, voice pitch is analyzed in PRAAT ( [START_REF] Boersma | Praat: doing phonetics by computer[END_REF]) and the following features are coded in ELAN ( [START_REF] Sloetjes | Annotation by category -ELAN and ISO DCR[END_REF]):

-Affiliation/ disaffiliation ( [START_REF] Stivers | Stance, Alignment, and Affiliation During Storytelling: When Nodding Is a Token of Affiliation[END_REF]) with the absent subject: based on the analysis of the sequential context, does the speaker agree or disagree with the absent subject to whom the speech content is attributed?

-Affiliation/ disaffiliation with the interlocutor: based on the analysis of the sequential context, does the speaker agree or disagree with his interlocutor on the topic? -Vocal features: does the speaker keep or markedly change his or her usual voice pitch range during constructed dialogue?

-Gestures: does the speaker gesture the usual way or is there observable change in the gesture's quality (e.g. more ample, faster gestures?) -Gaze and posture: is there a shift sideways indicating the creation of an imaginary story space and multimodally expressing mixed viewpoints ( [START_REF] Stec | Managing Multiple Viewpoints[END_REF])?

The results presented here focus on the qualitative study of three sequences, which exemplify processes at work in the data as a whole. The analyzed passages are transcribed in intonation units ( [START_REF] Chafe | Discourse, Consciousness and Time: the Flow and Displacement of Conscious Experience in Speaking and Writing[END_REF], [START_REF] Stelma | Intonation units in spoken interaction: Developing transcription skills[END_REF]), in which punctuation reflects intonation, not syntax. Specific gestures are shown after each transcript in screen captures. For the sake of clarity, turns at talk are numbered and instances of constructed dialogue are transcribed in bold.

Results

Endorsing an absent subject's stance

In a previous study, we showed how absent subjects are sometimes quoted as experts to serve as warrants for the speaker's discourse ( [START_REF] Debras | Formes et fonctions du discours d'expert dans des discussions sur l'environnement entre étudiants britanniques : une étude multimodale de la prise de position en interaction[END_REF]). But endorsing an absent subject's stance can have other forms and functions. In Excerpt 1, ANT tells his interlocutor ELI a side anecdote from his adolescence, in which a homeless man who smelt bad used to regularly visit his local library. Each time he left, the librarian sprayed the library with an air freshener, perplexing some library users.

Excerpt 1 1 ANT: and er she'd literally just like as soon as he left she kind of like, right I'm gonna go round with the febreze now, and everybody else was like, why why is she like going round with the febreze? and she was like, well you know the smelly guy's been round again.

2 ELI: (laughs) oh god, 3 ANT: (laughs) it was quite common knowledge.

In the passage, ANT presents both the library users' incomprehension and the librarian's justification of her action in the form of constructed dialogue. His attribution of direct discourse to the library users (why is she going round with the febreze?) and to the librarian (well you know the smelly guy's been round again) is probably a reformulation rather than a quote: in the silent environment of a library, they would more likely have expressed their incomprehension by silent visual displays (e.g. raised eyebrows) rather than voiced utterances. Presenting their reaction in the form of direct discourse is hence rather a strategy to stage the anecdote and create humor. ANT represents the two points of view by relying on his usual gesture style and usual voice pitch. In none of the three occurrences of constructed dialogue (ANT, turn 1) does ANT resort to a shift of posture and/or gaze to create a visual story space. Rather, he keeps the same body orientation towards ELI and his gaze fixed on her throughout constructed dialogue, even though he embodies the mentioned absent subjects to some extent. For instance, on right I'm gonna go round with the febreze now, he keeps the same gaze and body posture orientations as when he was speaking in his own name, but combines them with an enactment of the librarian spraying febreze in the library (Fig. 1). Enacting an absent subject's actions without explicitly marking the difference between self and other, between real space and story space ( [START_REF] Stelma | Intonation units in spoken interaction: Developing transcription skills[END_REF]), is a way for the speaker to iconically express his endorsement of the absent subject's attitude. Likewise, ANT uses the upper range of his usual voice pitch to voice the library users' reaction as questioning an observable state of affairs ( [START_REF] Heritage | The limits of questioning: negative interrogatives and hostile question content[END_REF]), the way he would do to ask a question himself. He also maintains his usual pitch range during both the quotative utterance ( [START_REF] Fuchs | Les quotatifs en interaction en anglais contemporain[END_REF]) she was like and the direct discourse itself well you know the smelly guy's been round again, which iconically suggests that he puts himself in the absent subject's shoes when voicing her stance. The visual modality anticipates on the verbal content: the quotative utterance is synchronized with a small palm-up shrug (lifted shoulders, palm-up flip of the left hand, in Fig. 2) expressing shared knowledge ( [START_REF] Debras | L'expression multimodal du positionnement interactionnel (multimodal stance-taking)[END_REF]), which is later taken up verbally by the discourse marker you know in the utterance attributed to the librarian. The small amplitude of this shrug is typical of this speaker's way of gesturing.

Using his usual voice pitch range and gesturing style to represent points of view that originally did not involve speech in the form of constructed dialogue allows him to achieve several effects. Two different points of view (the library users' and the librarian's) on the same event are presented on an equal footing. By lending his own voice and gesturing style to both of them, he endorses each viewpoint in turn. More precisely, his whole talking body is mobilized to lend a voice to each of them, thereby suggesting that he could well have reacted the same way in their place. ELI aligns with ANT, empathetically laughing at the incongruous situation he has just described, and their shared laughter (turns 2 and 3) indicates their aligned stances (i.e. shared perspectives) on the story. In this passage, the main function of direct discourse cannot be truthfully quoting an absent subject: the source of the direct discourse is explicitly identified as a group of people (they were a geographic society) during a debate. DAN uses multimodal constructed dialogue to sum up a collective stance on a given topic, and makes extensive use of multimodal resources to enact it. A first striking aspect is the use of a change in voice pitch range in synchrony with the direct discourse attributed to the geographers. On and they were saying, oh it's it's either one or the other you know we can't direct our attention to both, DAN uses a markedly low voice pitch (around 100Hz, see Fig. 3) that reaches far lower than his usual pitch range. His own voice pitch (around 200 Hz) reappears when he starts speaking in his own name again, on but I definitely think we can. This contrast in voice pitch iconically marks the introduction of an outside enunciator, whose voice is perceptually different from his own. He uses his own voice as a medium to present an absent subject's stance while simultaneously reminding his interlocutor that this outside voice is distinct from his. The difference in voice pitch iconically represents the speaker's disaffiliation with the absent subject's stance. The transition from self to other is also marked on the verbal level: the direct discourse opens with the utterance-initial discourse marker oh, which usually indicates a change of state for the speaker ( [START_REF] Heritage | A change-of-state token and aspects of its sequential placement[END_REF]). Oh is highlighted by a low initial pitch, marking a shift from the speaker's viewpoint to the absent subject's viewpoint.

The visual modality reinforces the speaker's distance: DAN accompanies the constructed dialogue utterance with pantomime including exaggerated head movements and facial displays ( [START_REF] Kraut | Social and Emotional Messages of Smiling; an Ethological Approach[END_REF]), and a shift in posture and eye gaze (Fig. 5). These visual changes are timed with the vocal distanciation and all begin on the quotative utterance (and they were saying). In that respect, the non-verbal components slightly anticipate the verbal one. In contrast with his previous physical attitude (Fig. 4), the use of visual markers borders on caricature (Fig. 5), informing the interlocutor that the stance presented by the speaker has nothing to do with what he believes here and now.

Using a markedly lower voice pitch (Fig. 3) adds to the caricature, as it mimics the voice of a phlegmatic old professor. Furthermore, DAN's simultaneous shifts in gaze and trunk posture (Fig. 4) suggest that the rejected stance is positioned in another, abstract dialogue space different from the real dialogue space ( [START_REF] Stelma | Intonation units in spoken interaction: Developing transcription skills[END_REF]) of his conversation with SIM (Fig. 5). In this specific context, creating a virtual dialogue space does not only serve a narrative purpose. Locating the constructed dialogue outside the here and now is another way for the speaker to iconically represent disaffiliation with the absent subject's stance. In all, verbal strategies (direct discourse, oh) as well as vocal (marked change in voice pitch range) and visual ones (exaggerated pantomime, gaze sideways) are carefully timed and combined in the sequential unfolding of actions to multimodally construct the rejection of an absent party's stance.

gaze away, exaggerated facial expression

There is a meta-pragmatic ( [START_REF] Streeck | Gesturecraft: The manu-facture of meaning[END_REF]) quality in the speaker's use of multimodal constructed dialogue. By using a full range of verbal, vocal and visual resources, he reminds his interlocutor that this is only an enactment, i.e. that his words, voice and body are only temporarily used to display another subject's stance and in no way represent his personal beliefs. His interlocutor SIM immediately aligns with him by questioning the absent subject's stance described with a rising intonation on why not, and DAN sides with him in verbally questioning the absent subject's stance by presenting it as incomprehensible (this is what I didn't understand). DAN's multimodal enactment has allowed him to put the absent subject at a distance, while simultaneously fostering agreement with his interlocutor.

An in-between, more complex case

In Excerpt 3, AMY has just picked up the question how can we solve climate change as part of the semi-guided conversation protocol, and asks it to her interlocutor JOE. As an answer, JOE develops the following stance: nuclear power is a relevant solution to combat climate change (e.g. it replaces polluting coal stations) and it is safe technology since accidents like Fukushima remain rare. AMY's stance in response to his is two-fold. She starts with a concession that is compatible with JOE's stance, thereby partially aligning with him (anti-nuclear activists can oversimplify matters), but eventually disagrees with him (one huge nuclear accident is already one too many). 5 AMY: I think like a lot of em a lot of anti nuclear sentiment is really not informed at all, and rather kind of like, nuclear stuff's poisonous and that's bad, 6 JOE: yeah, 7 AMY: em, 8 JOE: yeah I I think it' a real shame with the with the thing in Japan, 9 AMY: mmh, 10 JOE: er from the point of view of nuclear power as well, 11 JOE: cause it's sort of the, 12 JOE: actually what happened in Japan was this really big exception, 13 AMY: mmh, (JOE argues in favor of nuclear power for 8 seconds) 14 JOE: and then sort of well actually if we if we're just careful, then then nuclear power is fine. 15 AMY: I guess like the the problem is, a lot of people understandably will say like, even if it happens once it's once too often, but,

Expressing disagreement is a sensitive phenomenon that involves face work ([3]), and agreement is usually preferred to (i.e. is more frequent than) disagreement in interaction ( [START_REF] Heritage | A change-of-state token and aspects of its sequential placement[END_REF], [START_REF] Pomerantz | Agreeing and disagreeing with assessments: some features of preferred/ dispreferred turn shapes[END_REF]). Owing to politeness mechanisms ( [START_REF] Brown | Politeness: Some Universals in Language[END_REF]), speakers tend to attenuate the potential threat posed to their interlocutor's face thanks to diverse strategies. As exemplified by Excerpt 3, agreement prefacing disagreement, in the form of concession, is one way of downplaying disagreement. AMY starts by adopting a stance that is compatible with JOE's as she criticizes the oversimplified criticisms of anti-nuclear activists. To do so, she uses constructed dialogue introduced by a quotative utterance (I think like a lot of em a lot of anti nuclear sentiment is (…) kind of like) to reject the absent subjects' stance just as she provides them with a voice. Her critical distance with respect to them is marked in the verbal modality (really not informed at all) as well as vocally. On the direct discourse attributed to the absent subjects, nuclear stuff's poisonous and that's bad, her voice pitch markedly shifts to a very high range which is not common at all in her usual way of speaking (Fig. 6). Yet when using this high-pitched voice, iconic of the scatterbrain attitude she is criticizing, she does not gesture at all. This comes out as slightly incongruous. Indeed, prosody and gesture usually work hand in hand ( [START_REF] Bolinger | Intonation and Gesture[END_REF]), with heightened intensity in the vocal modality being simultaneously expressed in some way in the visual modality, and vice versa. The larger stance-taking processes at work here are a plausible explanation for this partial (vocal not visual) enactment of a criticized absent subject's stance. This critical instance of constructed dialogue is not the core of her stance, but only a concession and preface to her real (i.e. anti-nuclear) stance. She is not using the full range of multimodal resources to caricature the absent subjects to the full, because that is not her main point and she partially agrees with them.

To formulate her disagreement with JOE (turn 15), AMY uses oblique strategies that allow her to express a divergent opinion while preserving her interlocutor's face. Her dissent is expressed by a turn-initial I guess. As Kärkkäinen ([40]) remarks, when I guess is used in second position in a sequence (i.e. in responsive actions to some other actions), it usually indicates some "degree of disagreement and disaffiliation between the participants", as "the current speaker wishes to modify, withdraw, and redefine his or her original stance at this point" ( [START_REF] Kärkkäinen | The role of I guess in conversational stancetaking[END_REF]: 197). Disagreement with the interlocutor is also marked on the vocal level: AMY uses a distinct pitch reset on I guess: this break in intonation is iconic of a break away from her interlocutor's stance ( [START_REF] Morel | Grammaire de l'intonation : L'exemple du français oral[END_REF]). Then AMY presents her discordant stance in an indirect way, resorting to constructed dialogue as an intermediate to express her opinion. She attributes a stance (even if it happens once it's once too often but) to the underdetermined, generic absent subject people and positions herself as endorsing this outside point of view by way of the stance adverb understandably in the quotative utterance (a lot of people understandably will say like). Her endorsement of this utterance is vocally and visually indicated by the continuity in her vocal pitch range and personal gesturing style. This supposedly outside voice cannot be traced to anyone in particular: more likely, it is hers in disguise. In this example, direct discourse works as a hedging technique to avoid disagreeing with the interlocutor too bluntly. AMY's cautiousness in taking an adversative stance is confirmed by a final shoulder shrug, an epistemic emblem expressing uncertainty and disengagement ( [START_REF] Debras | L'expression multimodal du positionnement interactionnel (multimodal stance-taking)[END_REF]) just before her final but.

Discussion

This qualitative study has evidenced that speakers do not use the multimodal potential of constructed dialogue only to represent interactions that have taken place or to narrate past events. Constructed dialogue can often not be traced to a speaker's original utterance at another time and place. It is also a pragmatic strategy that allows the speaker here and now to present a person or a group's stance in a more vivid, embodied way. Constructed dialogue allows speakers to articulate two levels of intersubjectivity: they position themselves with respect to both present subject (interlocutors) and absent ones (brought in by constructed dialogue). More specifically, positioning themselves with respect to absent subjects is one way of positioning themselves with respect to present ones. Many combinations are possible: the speaker enacts the absent subjects' stance to take on their perspective, and the interlocutor aligns, empathetically sharing the experience put on display by the speaker (Excerpt 1). In other cases, the speaker can mobilize his own talking body as a medium to ridicule an absent subject, thereby inviting his interlocutor to side with him on the topic at stake (Excerpt 2). The enactment of an absent subject's stance to put it at a distance can also be partial (verbal and vocal only, not visual) when the speaker caricatures this absent subject's stance to side with the interlocutor only temporarily and partially in a movement of concession, just before disagreeing with him (Excerpt 3). Constructed dialogue can be used as a hedge to downplay disaffiliation with the interlocutor, so as to ensure the politeness of the exchange: the speaker lessens her endorsement of the disagreeing stance by attributing it to an absent subject and agreeing with it (Excerpt 3).

There is a continuum in the multimodal intensity of constructed dialogue: not all instances of constructed dialogue include enactments of the absent subject's body or voice. Nonverbal resources, and most strikingly voice pitch, seem iconic of the speaker's stance with respect to the absent subject. When speakers make a distinction between they own voice and the other voice through a marked change of pitch, they distance themselves from this other voice/stance by marking it as different. Conversely, using one's usual voice pitch to present another voice can indicate the speaker's endorsement of that voice/stance. Likewise, keeping one's usual gesturing style can mark the speaker's endorsement of the absent subject's stance, while suddenly using more ample, faster gestures can express distance through pantomimic caricature. In all, constructed dialogue takes on different stancetaking functions in context, depending on the kind of multimodal resources that are mobilized.

Conclusion

On a theoretical level, this qualitative study invites to a reevaluation of Du Bois's ( [START_REF] Bois | The Stance Triangle[END_REF]) model of stance as a triangle between two subjects (the speaker and the interlocutor) and a (discourse) object. Constructed dialogue makes explicit not only the backdrop of possible perspectives ( [START_REF] Martin | The Language of Evaluation: Appraisal in English[END_REF]) on a given topic, but also the other, absent subjects who take on these stances. The Stance Triangle could be redefined as a Stance Tetrad, where speakers position themselves with respect not only to an object and a present subject but also to absent subjects. This in turn invites a redefinition of the interaction context. As the speaker positions himself with respect to absent subjects as well, the interaction context becomes indexical of the larger social context ( [START_REF] Goodwin | Rethinking Context: an introduction[END_REF]).

This qualitative study opens up further research perspectives. A larger corpus and quantitative methods could permit to operationalize "self" and "other" voice pitch and gesturing style according to a set of specific features. This in turn could help show whether changes in voice pitch range and/or in the quality of the speaker's gestures function as statistical predictors of endorsement or distance vis-à-vis an absent subject's stance presented as constructed dialogue.

Figure 1 :

 1 Figure 1: ANT (left)'s enactment of right I'm gonna go round with the febreze now.

Figure 2 :

 2 Figure 2: ANT's palm-up shrug on and she was like3.2. Dis(-s)tancing oneself from an absent subject's stanceIn the data, distance with respect to an absent subject's stance presented as constructed dialogue is largely expressed by non-verbal resources. Excerpt 2 is taken from the conversation between SIM and DAN. DAN presents the opinion of geographers about climate change in the form of constructed dialogue. He heard them speak at a debate organized by a geographical society, and was surprised by their position on combating climate change: they argued that a country should develop either renewable energies or nuclear power, while DAN thinks that both should be developed together. SIM joins him in questioning the absent subject's stance and DAN eventually confirms that he rejects it too.Excerpt 2 1 DAN: like people I went to this debate, they were a geographical society, and they were saying, oh it's it's either one or the other you know, we can't direct our attention to both. but I definitely think we can, 2 SIM: really, why not? 3 DAN: well this is what I didn't understand, none of them gave a good argument.

Figure 3 :

 3 Figure 3: DAN's change in voice pitch between constructed dialogue (and they were saying) and his own voice (but I..)

Figure 4 :

 4 Figure 4: DAN (right) gazing at SIM (left) before constructed dialogue

Excerpt 3 1

 1 AMY: ok er how can we solve climate change? 2 JOE: er pff lots of nuclear power. (small laugh) 3 AMY: mmh, (small laugh) 4 JOE: I know that's a bit controversial at the moment, but I th… I think it's still a valid point. (argues in favor of nuclear power for 21 seconds)

Figure 6 .

 6 Figure 6. AMY's shift in voice pitch range on nuclear stuff's poisonous and that's bad (turn 5)

Figure 6 :

 6 Figure 6: AMY's initial pitch reset on I guess (turn 15)


PhD Isabelle Laplace
email: isabelle.laplace@enac.fr

Dr Nathalie Lenoir

Dr Chantal Roucolle

Economic impacts of the ASEAN single aviation market: focus on Cambodia, Laos, Myanmar, The Philippines and Vietnam

Keywords: network expansion, innovation air transport, ASEAN, competition distortion, economic impact estimation, liberalization, market regulation

Her expertise concerns the economic aspects of the air transport market in terms of passenger demand, airline behaviour, airport strategies, airport capacity, air transport liberalisation, energetic transition, innovation strategies, door-to-door travel

Introduction

Air transport in South East Asia has been historically regulated on the basis of bilateral agreements which imposed restrictions on the operations of all carriers. The idea of liberalizing the air travel sector in the region goes back to the ASEAN (Association of South East Asian Nations) leaders' summit held in Bangkok in 1995. In 2004, the 10th air transport ministers' meeting in Phnom Penh decided upon an "Action Plan for ASEAN Air Transport Integration and Liberalization 2005-2015" (10th ASEAN Transport Ministers Meeting 2004). The objective was to establish a single aviation market by 2015. Since then, while not all of the countries have reached the same level of ratification, they have all made steps towards greater liberalization. The first target which has been reached was to open 3 rd , 4 th and 5 th freedom rights inside the ASEAN region for ASEAN carriers by 2015. With this first step, also named ASEAN open skies, ASEAN airlines are still only allowed to fly to and from their home country to neighbouring ASEAN countries but with greater freedom (all entry points are granted, there are no more frequency and capacity constraints). They are also granted 5 th freedom rights to extend flights beyond their home country. This work starts with a literature review of the economic impacts of previous air transport liberalization experiences. We then explain the specific econometric method developed to assess the impact of liberalization on GDP in the five considered ASEAN countries, and present the results in terms of regional GDP growth due to liberalisation. In a third part, we look at the impact of a multilateral agreements with a third country on ASEAN carriers. We highlight possible competition distortion in air transport on international markets with the example of the multilateral agreement between ASEAN and China.

Considering those results, we conclude with some recommendations in order to anticipate future traffic growth and potential competition unbalances. The work presented here has been undertaken in the scope of the ASEAN Air Transport Integration Project (AATIP), supporting the making of the ASEAN Single Aviation Market [START_REF] Laplace | Provision for Consultancy Study on the Economic Impact of the ASEAN Single Aviation Market[END_REF]. The objective of AATIP was to facilitate the development of ASEAN frameworks to strengthen institutional capacities in order to achieve a safe, secure and sustainable ASEAN Single Aviation Market (ASAM). AATIP made some recommendations in terms of harmonisation of regulations in the ASEAN area with high regulatory standards.

Literature review on previous air transport liberalisation experiences

In previous liberalisation experiences (e.g. USA [START_REF] Goetz | The Good, the Bad, and the Ugly: 30 Years of US Airline Deregulation[END_REF], EU-Africa [START_REF] Njoya | Understanding the Impact of Liberalisation in the EU-Africa Aviation Market[END_REF], US-Carribean (Warnock-Smith and Morrell 2008), EU-Morocco [START_REF] Dobruszkes | Aviation Liberalization as a Means to Promote International Tourism: The EU-Morocco Case[END_REF], it has been observed that air transport liberalization led to higher air traffic volumes. In a deregulated environment, airlines have to adapt their strategies in response to new possibilities and a stronger competition illustrated by an increased number of operating carriers at the route level (Warnock-Smith and Morrell 2008; [START_REF] Burghouwt | In the Wake of Liberalisation: Long-Term Developments in the EU Air Transport Market[END_REF][START_REF] Olariaga | Influence of the Liberalization of the Air Transport Industry on Configuration of the Traffic in the Airport Network[END_REF]. They can compete within their existing network by operating more frequencies [START_REF] Njoya | Understanding the Impact of Liberalisation in the EU-Africa Aviation Market[END_REF][START_REF] Njoya | Understanding the Impact of Liberalisation in the EU-Africa Aviation Market[END_REF] or expand and optimise their network [START_REF] Fu | Air Transport Liberalization and Its Impacts on Airline Competition and Air Passenger Traffic[END_REF][START_REF] Jankiewicz | The Air Transport Market in Central and Eastern Europe after a Decade of Liberalisation -Different Paths of Growth[END_REF] and offer more destinations. They strive to reduce ticket prices and increase the quality of their services [START_REF] Abate | Economic Effects of Air Transport Market Liberalization in Africa[END_REF][START_REF] Goetz | The Good, the Bad, and the Ugly: 30 Years of US Airline Deregulation[END_REF][START_REF] Njoya | Understanding the Impact of Liberalisation in the EU-Africa Aviation Market[END_REF]. Deregulation is hence a recognized driver of traffic and network growth [START_REF] Jankiewicz | The Air Transport Market in Central and Eastern Europe after a Decade of Liberalisation -Different Paths of Growth[END_REF] and is recognised as bringing positive impacts on countries' economies [START_REF] Fu | Air Transport Liberalization and Its Impacts on Airline Competition and Air Passenger Traffic[END_REF]. For instance, INterVISTAS (InterVISTAS-ga 2006) models the liberalisation effects and shows that the air traffic increase in air traffic generates significant employment benefits. In a 2016 working paper, ICAO also concludes that liberalization leads positive externalities to the overall economy including GDP growth and employment opportunities.

These positive impacts, however, can be less than expected if airlines face barriers to entry at airports. When studying the impacts of air transport liberalization on airline competition in Europe, [START_REF] Dobruszkes | Does Liberalisation of Air Transport Imply Increasing Competition? Lessons from the European Case[END_REF] stresses that "the saturation of a number of European airports is a strong barrier to the entry of new carriers or to the extension of existing ones". [START_REF] Oliveira | Network Concentration and Airport Congestion in a Post De-Regulation Context: A Case Study of Brazil 2000-2010[END_REF] also highlight the combined role of airline activity concentration and airport congestion in generating entry barriers for airlines. Other limitations to the expected positive economic impacts can come from possible competition distortion between airlines if the completion level of the liberalization process is different according to countries. Multilateral liberalisation agreements are likely to have more positive economic implications than bilateral agreements (IATA 2007). IATA explains that if airlines do not have the full commercial freedom to restructure capacity in response, this restricts their ability to achieve a sustainable level of return on investment and cost to all stakeholders in the aviation industry at a long-term and as a consequence limit the expected positive economic impacts. So far, there are only few studies that estimate the economic impact of air transport liberalization for the ASEAN countries. ECORYS (2012) only addresses economic impacts of the ASEAN air transport liberalisation (in terms of contribution to GDP, employment growth or tourism growth) due to expected air traffic increase between ASEAN member states but not consider the traffic with non-ASEAN member states. InterVISTAS-ga (2006) focused on the impacts of air transport liberalization at a worldwide level but was not able to provide reliable results for developing countries such as ASEAN member states, due to missing data. The impacts of the air liberalization agreements both on the economic development inside ASEAN and on the organisation of air transport have not yet been studied. Our paper aims to fill this gap in the literature by first estimating, by local and regional GDP impacts of liberalization for five ASEAN countries: Cambodia, Lao PDR, Myanmar, the Philippines and Vietnam. Then, we study impacts of a multilateral agreement with third country on the air transport organisation, by considering the ASEAN-China multilateral agreement and by analysing the existence of barriers to entry.

Quantifying the economic impacts of the ASEAN liberalization

Methodology

We develop an econometric model to quantify the economic impacts of the air transport liberalization up to the 5 th freedom right in the ASEAN countries. The analysis focuses on five countries, Cambodia, Lao PDR, Myanmar, the Philippines and Vietnam, and is conducted independently for each of them. We implement a two-stage methodology.

(1) First, we estimate a model which expresses, for each country, the relationship between economic development and air traffic, in terms of number of passengers. The level of regional GDP is used as a proxy for economic development in airport areas. The number of air passengers is the measure of air transport performance.

The model is estimated based on observation during the period 2004-2013.

(2) Then, based on air passenger growth scenarios, between 2014 and 2020, we use this econometric model to forecast the potential impact on GDP growth up to 2020.

We conduct the analysis at the regional level, focusing on regions that include at least one airport. In order to isolate the GDP growth due to the increase in passengers from its growth due to other characteristics of the region, or to socio-economic chocks which impact independently all the regions, we include in the estimated model different controls variables. In particular, the period of observation includes the world financial crisis, which has drastically affected the performance of air transport worldwide. ASEAN air transport market, as others markets, suffered from this crisis. Thus, we introduce in the model some controls for this specific chock. We give measures of GDP growth by region and by country, as a consequence of the expected increase in air transport passengers. Regional GDP should always be preferred as the improvement in economic performances should be better appreciated locally, in area where air traffic is concentrated. Nonetheless, we will provide impacts at the national level after some aggregation of regional effects. Additionally, the sense of causality between air transport performances and economic growth is uncertain. This issue is taken into consideration with the use of an instrumental variable estimation method that requires two stages.

Data

We use data collected directly from the states under consideration, complemented by other aviation and non aviation public data. The data provided by the states are yearly data for the period 2004-2020. They are related to air transport performances and socioeconomic indicators for the period 2004-2013 and forecast of some of the above measures for the period 2014-2020.

Air transport data provided by national civil aviation authorities includes yearly domestic and international passengers per airport. We use the number of passengers as a proxy for air transport performances. The total number of passengers at airport level is a relevant indicator to address the question of impact of air traffic on regional economic performances. The existence of uncertainty regarding the sense of causality between air transport performance and economic activity leads to the use of instrumental variables to correct the potential endogeneity. In addition, the relative importance of international and domestic passengers is considered as a proxy for air transport structure. We argue that air transport structure affects the level of airports' performance. We use the air transport structure, as explained later on, as an instrumental variable in the estimated model. Wen turning to the forecast up to 2020, we assume that air transport structure will remain constant over the period 2014-2020. Although restrictive, this assumption is necessary to produce consistent air transport forecast up to 2020, in the absence of information on the evolution of individual airport traffic structure beyond the period of observation.

National ministries of tourism provided yearly tourism activity index and yearly forecasts until 2020 of international number of tourists. We use this information for two different purposes. Firstly, in the estimation process, the yearly index is an instrumental variable for the treatment of air passenger endogeneity. This choice is justified by the low level of tourism contribution to GDP in ASEAN countries. The contribution of tourism activity to GDP is in 2013, quite close and low for Lao PDR, the Philippines and Vietnam (between 4 and 4.6%). It is even lower for Myanmar, accounting for 1.6% of GDP only. Thus, we consider that tourism does not affect GDP but should influence the number of passengers. Secondly, during the forecast process, we use the forecasted number of tourists to recover the expected number of passengers.

In addition, we use GDP and population as socio-economic indicators. GDP comes from the World Bank database where the information is delivered at a national level. Our objective is to estimate the impact of the air traffic development at the regional level. GDP is the variable to explain and this implies to observe it at the regional level. The regional GDP information is unavailable and we make the strong assumption that regional GDP is proportional to the number of inhabitants in the region.

For all countries but Cambodia, we were able to collect population information, at city or regional level, on the cities websites. Cambodian population is collected at the national level. No historic evolution is available for the population data: the information is collected for a unique year. We assume stability of the regional level of population over the full period of analysis. This is a strong assumption as between 2003 and 2020 we should expect some regions, in particular the highest economic developed areas, to see their number of inhabitants to increase more than other less dynamic regions. Moreover, the overall number of inhabitants is increasing. The assumption of stability should lead to underestimate the effects.

First stage results: estimation of the impact of air traffic on GDP

We express a linear relationship between the yearly regional GDP and the yearly number of passengers at airports. The regional impacts of liberalization depend on the socioeconomic characteristics of the region at stake. We argue that any change in the number of passengers might have different impacts on economic growth depending on the airport characteristics. Socio-economic differences between regional areas are controlled for thanks to airport fixed effects. Moreover, whether the airport is domestic or international might be of particular importance. We introduce a dummy variable to distinguish between international and domestic airports. Yearly fixed effects are included when necessary to take into account the non-measurable economic shocks linked with the world financial crisis. However, the relevant yearly fixed effects vary according to the country, as we will see in the forthcoming estimations.

The relationship between regional GDP and the number of passengers arriving or departing in the region is expressed as:

𝐺𝐷𝑃 𝑜𝑓 𝑐𝑖𝑡𝑦 ( 𝑟𝑒𝑔𝑖𝑜𝑛)
= 𝛼 𝑃𝑎𝑠𝑠𝑒𝑛𝑔𝑒𝑟 𝑛𝑢𝑚𝑏𝑒𝑟 𝑖𝑛 𝑐𝑖𝑡𝑦 (𝑟𝑒𝑔𝑖𝑜𝑛) + 𝛽 airport fixed effect

+ 𝜎 𝑑𝑜𝑚𝑒𝑠𝑡𝑖𝑐 𝑎𝑖𝑟𝑝𝑜𝑟𝑡 + 𝛾 𝑦𝑒𝑎𝑟𝑙𝑦 𝑓𝑖𝑥𝑒𝑑 𝑒𝑓𝑓𝑒𝑐𝑡 + 𝜇 Equation 1
where , ,  and  are the parameters to be estimated and  is the error of the model.  includes all the factors also affecting the level of GDP but which cannot be observed. In order to control for the temporal effect, the estimation is performed using the differenceby-difference methodology. The variables included in the model are therefore expressed as yearly changes.

There is uncertainty regarding the sense of causality between the GDP and the number of passengers. To control for the sense of causality and the consequent endogeneity issue, we use the usual instrumental variable method. As explained previously, we use the percentage of international air passengers as a first instrument for the number of passengers. This percentage interprets as the structure of air transport activity. For international airports, we set the share of international passengers equal to its yearly level over the period 2004-2013. For domestic airports, the share of international passengers equals zero. We argue that air transport structure has no direct link with GDP, although its relationship with the number of passengers at airport level is non-ambiguous: we observe that the number of passengers in international airport is always higher than the number of passengers in domestic airport. This justify the use of this variable as an instrument.

The second instrument is the number of tourists, used as a proxy for tourism activity. This information is available at the national level. As explained in the data section, the low level of tourism contribution to GDP in the different countries justify the choice of this variable as an instrument. The number of tourists directly impacts the number of passengers, but does have a direct effect on GDP.

The estimation using instrumental variables does not generally require the specification of the relationship between the endogenous variable and it instruments. However, in our particular case, the finale objective is to provide forecast of DGP growth following traffic growth up to 2020. No forecast of air passengers is available, but the States provided tourists forecasts. Thus, we need to use the forecasted number of tourists to recover the forecasted number of passengers. This necessitates to specify and to estimate the relationship between the number of passengers and the number of tourists. The preliminary step in our estimation process consists in estimating the regional number of passengers on the above-defined instruments. The instruments have to be correlated with the number of passengers, but uncorrelated with the error of the first model in Equation 1. The instruments are the yearly number of tourists, the percentage of international air passengers into the corresponding region, and all the other exogenous variables of the model in Equation 1, regional (or airport) and yearly fixed effects, domestic or international airport.

Then we can express the regional number of passengers as:

𝑃𝑎𝑠𝑠𝑒𝑛𝑔𝑒𝑟 𝑛𝑢𝑚𝑏𝑒𝑟 𝑖𝑛 𝑐𝑖𝑡𝑦 (𝑟𝑒𝑔𝑖𝑜𝑛)
= 𝛿 tourist number +  percentage of international passengers +  domestic airport +  regional fixed effect +  yearly fixed effect +  Equation 2

where , , ,  and  are the parameters to estimate, and  is the error of the model. As in the previous estimation, the model is estimated using difference by difference estimation.

The two equations 1 and 2 are estimated using the model procedure in SAS where we specified the 3SLS method which takes into account both endogeneity of some of the regressors and cross-equation correlation of the errors. This methodology is applied independently for four countries: Lao PDR, Myanmar, The Philippines, and Vietnam. For the fifth one, Cambodia, due to data constraints, the model is adapted. We estimate it, still using a 3SLS method for the Equation 1 and 2, but at airport level rather than regional level.1 Thanks to the estimated parameters, we can measure GDP growth for the period 2014-2020 linked with airport traffic forecasts, thanks to tourism development forecasts on the same period. The process is the following: we use the tourist forecast on the period 2014-2020 and, first, use Equation 2to calculate the increase in passenger number. Then we use Equation 1to measure the impact on GDP.

The main limitation of the above described method lies in the lack of information regarding drivers of GDP other than passenger numbers. This could lead to marginally overestimating the impacts even though the instrumental variable method partially fixes this issue of missing variables. However, the relative impact on the different regions and the comparison of impacts between countries remain relevant since the methodology respects the regional specificities of each country. Additionally, the provided forecasts by country (regarding the growth of the number of tourists or the number of passengers to 2020) intensify the marginal overestimation phenomenon as the rate of growth before and after 2013 increases a lot.

Second stage results: Forecasts of the impact of air traffic on GDP

Forecasting the impact of air traffic on GDP up to 2020 requires including forecasts of the number of air passengers in Equation 1. Based on tourist predictions up to 2020, a preliminary step consists in using the relationship between passengers and the number of tourists (Equation 2) to assess the impact of the increase in the number of tourists on the number of air passengers. Then, the impacts on GDP are estimated by introducing the air passenger forecasts in Equation 1.

The forecasts are implemented under the assumption that the share of international passengers remains constant for the period of prediction. This amounts to assuming that the structure of air traffic remains constant over the period of prediction. For international airport and from 2014 to 2020, we set the share of international passengers equal to its average level on the observed period 2004-2013. For domestic airport, we keep the share of international passengers equal to zero, assuming here that these airports will remain domestic airport up to 2020. This is one of the main limits of the model, as the deregulation should enhance international traffic share at international airports. Finally, for robustness imperatives, we use the Monte Carlo technique of simulation available in the SAS model procedure. It consists in assessing the different potential economic impacts when the values of the estimated parameters of the econometric model are modified inside their respective confident intervals. Therefore, we obtain some distributions of the regional impacts rather than single values. The results reported in Table 1 are the means of these distributions. The forecasted GDP growth at a country level, between 2014 and 2020, differs a lot between countries. The Philippines will benefit from the highest effect with an annual expected increase of 6.1% of its GDP. The effect is expected to be around 2-3% yearly for Lao PDR and Vietnam. Finally, the impact on GDP should be the lowest, but still positive for Myanmar and Vietnam: +1.2% and +1% respectively. At a regional level, it is particularly interesting to observe that for all countries, except Myanmar, the highest GDP growth should be in regions with domestic airports only. In other words, despite the fact that the air transport liberalization only concerns international airports, domestic airports should also benefit from traffic increase at international airports, which will play the role of national hubs. However, the strongest expected GDP growth in regions where only domestic airports are located does not mean that these regions will bring the highest contribution to the national GDP. The GDP levels in these regions are generally lower than in regions with international airports where we observe, in general, the largest industrial and/or tourism development.

The expected increase in national GDP strongly relates to two main effects: the current contribution of the tourism activity on national GDP and the forecasted tourism activity growth expected by each country up to 2020. 2 Countries with an important tourism activity such as the Philippines and Vietnam should benefit from the higher yearly GDP growth over the period (+6.1% and +2.9% respectively). The expected economic growth due to the ASEAN air transport liberalization is particularly important for the Philippines already which welcomed 5% of the total tourists in the ASEAN region in 2013 (Source: Philippines Statistics Authority) and forecasts a tourism yearly growth of 6.75% by 2020.

The expected GDP growth of Vietnam following the liberalization should also be mainly due to its tourism activity. Vietnam is ranked 5 th in ASEAN in terms of number of yearly tourists, with an expected yearly growth of 6% by 2020 (source Vietnam Tourism Ministry). Moreover, the direct contribution of travel and tourism to the country's GDP represents 4.6% in 2013 which is slightly higher than the average tourism contribution to GDP in ASEAN (4.2%).

The explanation of the moderate expected economic growth for Lao PDR (+2.1% yearly increase up to 2020) is related to the moderate tourism activity growth expected by 2020 (+3% yearly increase in numbers of tourists) combined with the low tourism activity in 2013 (Source Myanmar tourism Ministry). In Cambodia, the economic impact of the air transport liberalization in terms of GDP should be five times higher in Siem Reap than in Phnom Penh. The explanation of this large difference comes from the very important tourist activity in the Siem Reap region.

In 2013, the number of tourist in the Siem Reap province represented 53.1% of the total number of tourists in the country. Air passengers at Siem Reap airport are, for most of them, tourists who stay for several days in the region and spend money visiting the Angkor monuments and staying at hotels, restaurants, shops. An increase in activity at Siem Reap airport promises important economic impacts for the region.

We show the positive impact of liberalization on regional economies. The expected passenger increase will boost the economic development in ASEAN market. We show that the impact is heterogeneous among and within ASEAN countries. However, capacity constraints at some airports could mitigate these traffic forecasts and the expected positive economic impacts. [START_REF] Laplace | Air Traffic Development in ASEAN: An Airport Capacity Analysis[END_REF] illustrate this problem by considering Soekarno-Hatta airport in Indonesia. Their analysis shows that the saturation of the main international airports in Indonesia will lead to a potential loss of air traffic in this country. Soekarno-Hatta airport will lose 49 million passengers by 2020 if the traffic is not diverted to other places. These figures are computed using Indonesian traffic forecast up to 2020. Authors obtain that 82 Million passengers more are expected at Soekarno-Hatta by 2020. Thirty-three million out of these 82 million passengers could be diverted to other Indonesian international airports which have some spare capacity. However, all the expected traffic will not be handled.

Liberalization with a third party: the ASEAN-China multilateral agreement

The organisation and development of air transport inside ASEAN and its impact on the economies of the region also depends on relationships with other countries. In this respect, the case of the agreement between ASEAN and China gives some hints as to what those impacts could be in the future, and about the risks involved. The EU-ASEAN Comprehensive Air Transport Agreement (CATA) which is currently under negotiation will also give new opportunities to ASEAN and non-ASEAN air carriers.

The air service agreement with China

At The first protocol appears to give ASEAN airlines some immediate benefits, by opening up any point in China (except the three excluded points). The protocol also opened the ASEAN market to Chinese airlines. It is to be remarked that slot restrictions at major airports can limit access on both sides: difficulties for ASEAN airlines to reach main cities in China (Beijing, Shanghai and others), and problems for Chinese airlines to reach main cities in ASEAN where some capital airports are congested. These protocols lead to unbalances in traffic rights, given the fact that Chinese carriers can start from anywhere in China to go to anywhere in ASEAN, and have thus access to a larger market than ASEAN carriers. Those can only start from their ASEAN country of origin, because the process of liberalization inside ASEAN is not yet complete. This could lead to an unbalance in market shares between Chinese and ASEAN Airlines, and this is what we investigate thereafter.

Methodology : Analysis of seats and market shares between ASEAN and China

We analyse here the evolution of traffic between ASEAN and China in order to assess the impact of the multilateral treaty.

i) Global overview

The international traffic to and from ASEAN has developed strongly in the last decade with 80% more seats supplied in 2015 than in 2006. 3 The strongest growth was between 2010 and 2015 with 49% more seats supplied. This growth is quite homogenous over the years between ASEAN and non-ASEAN airlines, which supply a balanced total number of seats each year, as shown in Fig 1. The situation is, however, significantly different on the air transport market between ASEAN and China. Firstly, this market is more dynamic: the total number of seats supplied was multiplied by 2.7 between 2006 and 2015 to reach 14.9 million seats. The growth was particularly high between 2010 and 2015 with 124% more seats supplied over the period. Secondly, the market shares have evolved in favour of Chinese carriers: While the market shares of ASEAN airlines (in number of seats) on all international routes remained around 50% between 2006 and 2015, they have decreased from 59% to 48% on routes between China and ASEAN during the same period (Figure 7). This loss of market share has been to the benefit of Chinese airlines for which the market share grew from 35% in 2006 to 51% in 2015.

ii) Routes and networks

The strategy chosen by Chinese airlines to reach this strong growth of market shares was mainly to develop a more extended network than ASEAN airlines. As an illustration, let us look at two airlines that developed their network during the period. We can see that China Southern Airlines opened routes from several cities in China to practically all countries in ASEAN, even if the effort was particularly concentrated in Guangzhou (China Southern is based there). On the other hand, the Thai airlines "Thai Air Asia" which is a low-cost airline (subsidiary of Air Asia) opened routes to several Chinese cities, especially in the southern and central part of China, but it is limited to start from Thailand (Bangkok, Chiang Mai, Krabi).

iii) Market entry and airlines

Market attractiveness is strong: 16 new airlines have entered the ASEAN-China market between 2010 and 2015. It is interesting to stress that Chinese airlines were particularly attracted, since eight new Chinese airlines decided to operate in this market between 2010 Thai Air Asia and Silk Air are the only ASEAN airlines belonging to the top 15 which increased their market share between 2010 and 2015 (Figure 17). Thai Air Asia is a lowcost carrier, while Silk Air is the regional subsidiary of Singapore Airlines on short and medium-haul markets. The loss of market share was particularly strong for Singapore Airlines that dropped from a 14% market share to a 7% market share over the period, which did not compensate for the increase of Silk Air by far.

There was an opposite trend for the Chinese airlines in the top 15 that generally tended to increase their market share. Only Air China and Shanghai airlines faced a market share reduction.

Summary of Findings

Our analysis shows that the traffic between ASEAN and China has grown tremendously since 2006, and even more since 2010. It appears that the market shares of airlines, in terms of available seats, have changed in favor of the Chinese airlines from 35% in 2006 to 51% in 2015.

The case is especially clear on the markets from the six countries who signed the air service agreement with China during the period under consideration, liberalizing the 3rd and 4th freedom traffic between China and each country. This unbalance is significant in terms of seats offered, but even more in terms of routes opened and network development.

The Chinese airlines operated nearly 200 routes in 2015 (from 120 in 2010), compared to 126 for ASEAN carriers.

One could argue that this evolution is due to the greater dynamism of Chinese carriers, but it is likely that the conditions of competition are also to blame: Chinese carriers can develop their networks from anywhere in China to anywhere in ASEAN, while the ASEAN carriers can only start from their country of origin. Each individual Chinese carrier has therefore more opportunities for network growth on profitable routes, and can benefit from economies of scope over the network. This particular agreement therefore highlights the need for ASEAN to exercise caution when liberalizing new markets while the internal ASEAN market is still not liberalized.

Discussion

Following liberalization, air traffic demand in ASEAN will increase. We show in our analysis that as a consequence of traffic increase, national GDP is expected to grow yearly depending on the country, from 1% (Cambodia) to 6.1% (The Philippines). The magnitude of the impact depends on the tourism development expectation as well as on the contribution of tourism to GDP. The expected impacts will not be homogenous over the different countries: they depend on the socio-economic characteristics of the region where the airport is located. The analysis indicates that the economic benefits of air transport liberalization are non-negligible for the ASEAN countries. However, these positive economic impacts could be narrowed due to saturation problems at some airports, leading to losses in potential air traffic in some countries. To benefit fully from air transport liberalization, ASEAN countries should carefully consider their issues with airport congestion.

In addition to that, ASEAN airlines also face possible competition distortion due to multilateral agreements with third countries, as is shown by the case of the ASEAN-China agreement. In particular, two elements are missing in ASEAN: there is no real possibility today of having ASEAN carriers with traffic rights all over the region, and the existing national carriers do not have such extended traffic rights either. Impatience to sign agreements now with outside partners can place national airlines at a disadvantage as long as traffic rights are not liberalized inside ASEAN.

If we look closely at the case of the six ASEAN countries concerned so far with the horizontal agreement with China, we see contrasted situations, but globally the Chinese airlines benefit much more from the agreement, which is again very clear in terms of network development (50% of routes in 2015 operated by Chinese carriers only). By doing so, they gain a first mover advantage that may give them a competitive edge, and it is likely that the unbalance observed will only worsen over time, as long as the ASEAN carriers are limited in their development. While the traffic increase is so far beneficial to the passengers on both sides, the potential reduction in competition between carriers may be a bad thing in the long run, especially if the situation endures.

Implications and recommendations

Considering this situation, it would be advisable to move forward with the liberalization process, including in it the concept of ASEAN carriers, able to operate anywhere in the area. This would indeed set the balance right between ASEAN and partner states carriers before the latter become too powerful in the region, and it would enable ASEAN carriers to consolidate and to develop by accessing new markets. Some ASEAN airlines may be able to benefit more from this than others, but it would be better for them than having foreign carriers take the lead in the region. From a competitive point of view, and from the point of view of the passenger, it would also be preferable to have more competition between carriers of several countries than to have only a few carriers on most markets. So far, final steps, leading to an ASEAN Single Aviation Market (ASAM) similar to the Single European Aviation Market, still need to be taken, but are slow to come, partly because some countries are reluctant to move forward. The date at which the freedoms up to the ninth freedom right will be liberalized is hence not yet defined. Opening all the freedoms to other ASEAN Member States has two main consequences: the first is that ASEAN airlines will be able to operate traffic from any airport of any other ASEAN country, to any destination of ASEAN. The second consequence is that ASEAN airlines will be able to directly target international airports in ASEAN (other than the airports concerned by the MAAS and MALFPAS agreements), which have now reached the safety and technical standards required after the 5th freedom is liberalized.

Beyond the possibility to fly everywhere inside ASEAN, ASAM would include the liberalisation of ownership, control of airlines, and advances on the concept of ASEAN Community Carrier. If ASAM were completed, it would ultimately lead to an ASEAN airspace open to all ASEAN carriers, with unified competition rules.

To help ASEAN member states prepare for the future, some recommendations can be made:

• Robust and reliable air traffic data are required in order to evaluate more precisely the impact of the ASAM on economic variables such as economic growth, employment or trade, and to formulate forecasts. A sufficient granularity is essential: the segmentation of the traffic into domestic, intra-ASEAN and extra-ASEAN traffic is needed to reach a better understanding of the influence of the liberalization at the State and regional levels. Historical data is also needed in order to perform consistent and relevant economic analysis. • Institutional design and standardization: the air traffic management systems are different across the countries. Certain air traffic management systems have reached sufficient standards but others are still improving. Moreover, the slot allocation process is different and (especially for the congested airports) needs to be clarified and stated in order to allow entry for other airlines at congested airports. • Design of a coherent competition policy. Liberalization will benefit the air transport market provided that conditions are in place to allow fair competition.

The main issue will be to make sure that the conditions are satisfied to allow entry and to prevent any incumbent behaviour against competition development (abuse of dominant position).

Conclusions

Our analysis shows that the regional air transport liberalization should benefit the ASEAN airlines and the ASEAN countries, but not in a homogeneous way, depending on the socio-economic conditions of each region and the contribution of tourism to its economy, Economic impacts of the ASEAN single aviation market without forgetting that airport saturation can be a limiting factor to traffic growth.

Nevertheless, with the signature of external liberalizing treaties with partner states, ASEAN airlines are likely to face competition distortion, as is shown by the case of the ASEAN-China agreement, because of traffic rights unbalances between ASEAN airlines and Chinese airlines, in favor of the later.

The implications are that ASEAN countries should proceed with the liberalization process, in order to obtain the full benefits or liberalization and give their own airlines the best chances in the competitive markets to and from ASEAN.

Annexes

Annex 1: Lao PDR Database building Air passengers per airport are provided by the Civil Aviation of Lao PDR for the period 2004-2013. The number of international tourists is provided for the whole period 2004-2013 by the Lao PDR Ministry of tourism. The data related to GDP and to the population are collected for the period 2004-2013 on the World Bank statistics website. No regional GDP has been provided or found on the publicly available data.

Annex 3: The Philippines

Database building Air passengers per airport are provided by Filipino Civil Aviation for the period 2004-2013. The number of international tourists is provided by the Filipino Statistics Authority for the period 2004-2013. The data related to GDP and to the population are collected for the period 2004-2013 on the World Bank statistics website. No regional GDP has been provided or found on the publicly available data. Economic impacts of the ASEAN single aviation market Annex 5: Cambodia

Database building

Air passengers per airport are provided by Civil Aviation of Cambodia for the period 2004-2013. The number of international tourists is provided by Cambodian government for the whole period of analysis 2004-2013. The data related to GDP and to the population are collected for the period 2004-2013 on the World Bank statistics website.

No regional GDP has been provided or found on the publicly available data.

Fig 1

 1 Fig 1 Yearly seats supplied by ASEAN and non-ASEAN airlines on international routes to and from ASEAN (data source from OAG database)

  If both ASEAN and Chinese airlines have increased their number of routes operated between 2006 and 2015, the network operated by Chinese airlines has far more developed during the period considered (Fig 3). Moreover, while there are around twice more ASEAN airlines than Chinese airlines operating on routes between China and ASEAN (Fig 5), the average number of routes operated per airline is dramatically higher for Chinese airlines than for ASEAN airlines (Fig 4). In 2015, 27 ASEAN airlines operated around 250 routes, while 15 Chinese airlines operate more than 370 routes. Another element of interest is the proportion of routes operated by carriers from only one country, or by ASEAN and Chinese carriers: in 2015 routes operated only by Chinese carriers represent 52% of the total routes between China and ASEAN, routes operated only by ASEAN carriers represent 27%, and routes operated by both represent 21%. This is another indication of the dominance of Chinese carriers over the networks.

Fig 2

 2 Fig 2 Number of seats by airline origin on routes between ASEAN and China (Source: OAG database)

Fig. 1 :Fig 7

 17 Fig. 1: Thai Air Asia route network in 2010 (data source from OAG database, map with http://www.gcmap.com/)

Fig 11

 11 Fig 11 Market share (in number of seats) of Chinese and ASEAN airlines in the TOP 15 airlines on the ASEAN-China market (Source: OAG database)

Fig 12

 12 Fig 12 Market share (seats) of individual airlines in the TOP 15 on the ASEAN-China market (data source from OAG database)

  Table 1 presents air traffic impact on GDP forecasted up to 2020. Figures represent the average yearly GDP growth over the period 2014 and 2020.

	Table 1 ASEAN Single Aviation Market impact on GDP. Estimated yearly GDP growth
	for the period 2014 to 2020.
		Regions with domestic airports only	Region with international airports only	Regions with airports domestic and international	Country
	Lao PDR	+13.5%	+6.2%		+2.1%
	Myanmar	+1.5%	+2.5%	+1.0%	+1.2%
	The Philippines	+7.2%	+6.2%	+5.6%	+6.1%
	Vietnam	+6.2%	+6.1%	+3.2%	+2.9%

Table 2 ASEAN

 2 Single Aviation Market impact on Cambodian GDP. Estimated yearly regional GDP growth for Cambodian regions for the period 2014 and 2020.

		Phnom Penh regional GDP	Siem regional GDP Reap	Country
	Cambodia	+4.9%	+18.4%	+1.0%

  the beginning of 2010, ASEAN and China established the ASEAN-China Free Trade Area (ACFTA). At the end of the same year, ASEAN signed an air service agreement with China. The reason behind the first initiative lies mainly in the importance of commercial links between China and the countries of ASEAN. Trade between them grew at an average annual rate of 46% during the period2000[START_REF] Fu | Air Transport Liberalization and Its Impacts on Airline Competition and Air Passenger Traffic[END_REF] (IMF 2018)). In 2008, ASEAN represented 9% of all imports and exports of China in value (US$ billions, (Ministry of commerce, People's Republic of China 2018)). It was even more in 2013, with 10.66%. On the ASEAN side, trade (imports and exports) with China (including Hong Kong) represented 18.5% of all ASEAN external trade in 2010 (US$ billions, (IMF 2018)). The strength and growth of commercial links between ASEAN and China are therefore an important factor in explaining the willingness to open the markets to trade and lower the trade barriers. A major determinant of growing air transport between ASEAN and China appears to be tourism: tourism arrivals from China grew by 86% from 3.93 million in 2007 to7.32 million in 20117.32 million in (ASEAN 2018)). Even before signing the agreement, the traffic of ASEAN with China (including Hong Kong) already represented 23,9% of all international seats into/out ofASEAN ('OAG Analyser' 2008). The importance of this traffic flow has pushed the authorities to alleviate the constraints and give more freedom to the airlines of both regions: less capacity constraints and more possibilities to open new routes. What is the nature of this new air service agreement? In the first protocol of this agreement, 3rd and 4th freedom rights are liberalized on both sides, with the exception of Hong Kong, Macao and Taiwan (points excluded by China). This enables ASEAN carriers to go from their own country to anywhere in China, as long as the airport is not saturated. Chinese carriers are allowed to go from anywhere in China to any point in ASEAN. The first protocol had now been ratified by China and all ASEAN countries (ASEAN 2017) and is already in force. A second protocol, concerning the 5th freedom has been signed in November 2014, but it is not expected to lead to any significant result because only secondary cities are concerned on both sides, with a capacity limit. It has been ratified by China and all ASEAN countries except Indonesia and Brunei (ASEAN 2017). It came into force in September 2015.

Table 3

 3 Regression of GDP on Passenger number -Result of estimations for Lao PDRA Pr > |t| lower than 0.1 indicates that the estimated coefficient can be considered as non-zero. Regression of Passenger numbers on the number of tourists and percentage of international passengers -Result of estimations for Lao PDR A Pr > |t| lower than 0.1 indicates that the estimated coefficient can be considered as non-zero.Database buildingAir passengers per airport are provided by the Civil Aviation of Myanmar for the period 2004-2013. The number of international tourists has been provided by the Myanmar Ministry of Tourism for the period 2002-2013. Regional GDP has been provided by the Myanmar Ministry of Economy for the period 2004-2013. The data related to the population are collected for the period 2003-2013 on the World Bank statistics website.

	Estimation results of equation 1
	Regional	GDP	=			Passenger	number	+			regional	fixed	effect	+			yearly	fixed	effect	+	
																Equation 1
	Variable										Parameter Estimates			t Value	Approx Pr > |t|
	Passengers ()							0.193673						8.06	<.0001
	Yearly fixed effects
	2010 Fixed effect (τ)						85.19865						2.37	0.0234
	Estimation results of equation 2
	Passenger	number	=			tourist	number		+			percentage	of	internatio	nal	passengers
									+			regional	fixed	effect	+			yearly	fixed	effect	+	
																Equation 2
	Parameter											Parameter Estimates	t Value	Approx Pr > |t|
	Tourist number ()											0.162301	4.21	0.0002
	Percentage of international
	passengers ()												60.22238	2.11	0.0423
	Table 4

Table 7

 7 Regression of GDP on Passenger number -Result of estimations for the PhilippinesA Pr > |t| lower than 0.1 indicates that the estimated coefficient can be considered as non-zero.

	Estimation results of equation 1
	Regional	GDP	=			Passenger	number	+			C ity	fixed	effect	+			yearly	fixed	effect	+	
							Equation 1
	Variable						Parameter Estimates t Value Approx Pr > |t|
	Passengers ()					0.15634		1.97		0.0510
	Yearly fixed effect ()
	2009 fixed effect				-1876.86		-6.59		<.0001
	City fixed effects ()
	Ilocos region						1120.809		3.40		0.0009
	Cagayan Valley				812.1294		2.46		0.0152
	Central Luzon region		2188.348		6.63		<.0001
	Calabarzon						2654.926		8.05		<.0001
	Mimaropa						555.7136		1.63		0.1056
	Caraga						614.0461		1.86		0.0658
	Bicol region						1167.504		3.51		0.0006
	Westen Visayas				850.4839		1.72		0.0882
	Central Visayas				1383.844		4.11		<.0001
	Eastern Visayas				957.8738		2.90		0.0044
	Zamboanga peninsula		744.2647		2.22		0.0280
	Northern Mindanao			745.8222		2.07		0.0403
	Davao Region					REFERENT REGION
	Metro Manila					-547.647		-0.35		0.7302

Table 8

 8 Regression of Passenger numbers on the number of tourists and percentage of international passengers -Result of estimations for the PhilippinesA Pr > |t| lower than 0.1 indicates that the estimated coefficient can be considered as non-zero.Air passengers per airport are provided by the Civil Aviation of Vietnam for the period 2009-2013. The number of international tourists is collected into the ASEAN statistics for the period 2009-2012. This number for 2013 is provided by the Ministry of Tourism of Vietnam. The data related to GDP and to the population are collected for the period 2009-2013 on the World Bank statistics website. No regional GDP has been provided or found on the publicly available data.

						Economic impacts of the ASEAN single aviation market
	Annex 4: Vietnam
	Database building
	Estimation results of equation 1
	Regional	GDP	=			Passenger	number	+			P rovince	fixed	effect	+			yearly	fixed	effect	+	
							Equation 1
	Variable					Parameter Estimates	t Value		Approx Pr > |t|
	Passengers ()					0.021558				1.64		0.1070
	Yearly fixed effect ()
	2012 fixed effect				138.8078				3.30		0.0017
	Province fixed effects ()
	ba ria vung tau					130.8839				1.64		0.1075
	binh dinh					201.8583				2.52		0.0147
	ca mau						164.4651				2.06		0.0441
	can tho						159.5311				2.00		0.0509
	da nang						9.170871				0.08		0.9330
	dak lak						245.9613				3.05		0.0035
	dien bien phu					51.14737				0.64		0.5244
	gia lai						175.1495				2.18		0.0334
	haiphong					referent province
	hanoi						825.5103				4.48		<.0001
	ho chi minh					847.4863				3.35		0.0015
	khanh hoa					118.4319				1.41		0.1650
	kien giang					229.4856				2.84		0.0063

Table 9

 9 Regression of GDP on Passenger number -Result of estimations for VietnamA Pr > |t| lower than 0.1 indicates that the estimated coefficient can be considered as non-zero.Table 101 Regression of Passenger numbers on the number of tourists and percentage of international passengers -Result of estimations for VietnamA Pr > |t| lower than 0.1 indicates that the estimated coefficient can be considered as non-zero.

	Estimation results of equation 2
	Passenger	number	=			tourist	number	+			percentage	of	internatio	nal	passengers
						+			province	fixed	effect	+			yearly	fixed	effect	+	
										Equation 2
													Parameter		Approx
	Parameter												Estimates		t Value	Pr > |t|
	Tourist number ()											0.096908		1.29	0.2009
	Percentage of international passengers ()			-2433.05		-5.97	<.0001
	Yearly fixed effect ( )
	2012 fixed effect											-233.215		-0.45	0.6532
	Province fixed effects ()
	ba ria vung tau											-591.06		-0.48	0.6305
	binh dinh												-426.987		-0.35	0.7281
	ca mau												-886.642		-0.73	0.4712
	can tho												-638.887		-0.52	0.6032
	da nang												7523.722
	dak lak												-75.3996		-0.06	0.9510
	dien bien phu											-861.55		-0.71	0.4837
	gia lai												-324.812		-0.27	0.7914

  Table11Regression of GDP on Passenger number -Result of estimations for Cambodia A Pr > |t| lower than 0.1 indicates that the estimated coefficient can be considered as non-zero.Table 12 Regression of Passenger numbers on the number of tourists and percentage of internationalpassengers -Result of estimations for Cambodia A Pr > |t| lower than 0.1 indicates that the estimated coefficient can be considered as non-zero.

	Estimation results of equation 1
	Regional	GDP	=			Passenger	number	+			Urban	area	fixed	effect	+			yearly	fixed	effect	+	
														Equation 1
												Parameter								Approx
	Variable									Estimates						t Value	Pr > |t|
	Passengers									0.048007						3.54	0.0030
	Yearly fixed effect
	2009 fixed effect						142.6412						1.76	0.0983
	Siem Reap fixed effect					-108.073						-2.32	0.0347
	Phnom Penh								Referent airport
	Estimation results of equation 2
	Passenger	number	=			tourist	number	+			percentage	of	internatio	nal	passengers
								+			urban	area	fixed	effect	+			yearly	fixed	effect	+	
														Equation 2
																	Parameter		Approx
	Parameter														Estimates		t Value	Pr > |t|
	Constant														451.7519		0.47	0.6443
	Tourist number ()											0.451947		2.30	0.0387
	Percentage of international passengers () -107.59		-0.80	0.4386
	Yearly fixed effect ()
	2009 fixed effect											-2699.37		-2.15	0.0510
	Siem Reap fixed effect ()								564.0629		0.87	0.3986
	Phnom Pen														Referent airport

The results of the estimation are available in the end notes.

We argue that Tourism has not direct impact on GDP but affect it through air passengers' number. However, we analyze the effect on GDP thanks the observation and forecasts on tourist numbers

The evolution of seats supplied being a proxy for measuring traffic evolution in terms of passengers transported


Delphine Lecomte Dumont

Dinu Stefan

Samia Chaouni

François Sichel

Jean-Louis Habrand

Victor Barraux

Carine Laurent

Use of genotoxicity, oxidative stress and inflammation blood biomarkers to predict the occurence of late cutaneous side effects after radiotherapy in Merkel cell carcinomas patients

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Use of genotoxicity, oxidative stress and inflammation blood biomarkers to predict the occurence of late cutaneous side effects after radiotherapy in Merkel cell carcinomas patients Delphine LECOMTE DUMONT 1,2 , Dinu STEFAN 1 , Samia CHAOUNI 2 , François SICHEL 2 , Jean-Louis HABRAND 1 , Victor BARRAUX 3 , Carine LAURENT 2,4 1: Radiotherapy Department, Cancer Centre François Baclesse, Caen; 2: ABTE-EA4651, ToxEMAC, Cancer Centre François Baclesse, Université de Caen Normandie; 3: Physics Department, Cancer Centre François Baclesse, Caen; 4: ARCHADE (Advanced Resource Centre for HADrontherapy in Europe)/SAPHYN, Cancer Centre François Baclesse, Caen.

Despite the technical advances in radiotherapy, toxicity to healthy tissues remains the limiting factor of treatment. The aim of this work is to highlight one or more blood markers whose ex vivo variations after irradiation (IR) could predict the occurrence of late cutaneous side effects. For this preliminary study, we selected patients with Merkel cell carcinoma (MCC) because, although rare, their treatment only includes radiotherapy and the dosimetry data are accurate to the skin. Two groups of patients were established according to the grade of late cutaneous toxicity after adjuvant IR for MCC: (i) no or little toxicity (grade 0, 1 or 2 of the RTOG), (ii) marked toxicity (grade 3 or 4 of the RTOG). In order to try to discriminate these 2 groups, markers of interest were selected and measured on the different compartments of ex vivo irradiated blood. At the lymphocyte level, cell cycle and apoptosis (flow cytometry) and genotoxicity (micronuclei) were quantified.

Oxidative stress was evaluated by the determination of the erythrocyte activity of the main antioxidant enzymes (SOD, CAT, GPx) as well as the generated degradation products (carbonyls and LPO in erythrocytes, secretion of 8-oxodG in plasma). The inflammatory phenomena were measured in the plasma by flow cytometry using LEGENDplex kits: IL-1β, IFN-α2, IFN-γ, TNF-α, MCP-1 (CCL2), IL-6, IL-8 (CXCL8), IL-10, IL-12p70, IL-17A, IL-18, IL-23, and IL-33. Since February 2017, 18 patients treated for a MCC at Cancer Center François Baclesse (Caen, France) were included in the study. Trends, but also some significant differences in blood markers tested after ex vivo irradiation were observed, most often after a dose of 10 Gy. The originality of this preliminary study is based on the pool of markers used on a homogeneous population of patients. The results will then be confirmed in a prospective framework.

Materials and Methods

Two groups of patients (n=10) were constituted among the patients treated by radiotherapy for a MCC (Merkel Cell Carcinoma) at the Cancer Centre François Baclesse (Caen, France). One of these groups presented extensive skin lesions (≥ grade 3 RTOG) called « Tox ≥ 3 ». The other group presented no or few skin side effects, it was called « Tox ≤ 2 ». MCC is a rare pathology but was chosen because its treatment is only radiotherapy (no hormone therapy, no chemotherapy) and dosimetry to the skin is well defined in technical records. For the protocol, see Figure 1.

Results

Eighteen patients were included since February 2017: 9 in the group « Tox ≥ 3 » (mean age = 74.4 years) and 9 in the group « Tox ≤ 2 » (mean age = 73.7 years). No significant differences were observed between patients in terms of age, received irradiation dose etc. At 2 Gy, there is a decrease in lymphocyte apoptosis (sub-G1 peak) in the group of patients « Tox ≥ 3 » compared to the group « Tox ≤ 2 » (Fig. 2). Micronucleus frequency is also decreased in the same manner but at the irradiation dose of 10 Gy (Fig. 3). At 10 Gy, there is also a decrease in SOD activity in the group « Tox ≥ 3 » (Fig. 4). In th same way, a decrease was observed in the level of reduced and oxidized glutathione (Fig. 5). There is no significant decrease but only a trend concerning IL-8 (Fig. 6) and other inflammatory cytokines, as well as degradation products as carbonyls, lipid peroxides (data not shown).

Figure 1 .

 1 Figure 1. Experimental protocol of PAESCART study.

Figure 2 .

 2 Figure 2. Lymphocyte apoptosis in both groups of patients.

Figure 3 .

 3 Figure 3. Micronucleus frequency per 1000 binucleated lymphocytes in both groups of patients.

Figure 4 .

 4 Figure 4. Superoxide dismutase activity in erythrocytes in both groups of patients. Mean value in unirradiated samples is 6.8 UI/mg of proteins.

Figure 5 .

 5 Figure 5. Reduced (left) and oxidized (right) glutathione in erythrocytes in both groups of patients.Orange is group « Tox ≤ 2 » and blue is group « Tox ≥ 3 ».

Acknowledgements

French blood establishment, Alain Batalla & Cédric Loiseau (Physics Department, Cancer Centre François Baclesse), Clinic Research Department (Cancer Centre François Baclesse), Maryline Guillamin (flow cytometry facility, University of Caen -Normandy)