Dynamic social representations of the 2009 H1N1 pandemic: Shifting patterns of sense-making and blame

We investigate dynamics of public perceptions of the 2009 H1N1 influenza pandemic to understand changing patterns of sense-making and blame regarding the outbreak of emerging infectious diseases. We draw on social representation theory combined with a dramaturgical perspective to identify changes in how various collectives are depicted over the course of the pandemic, according to three roles: heroes, villains and victims. Quantitative results based on content analysis of three cross-sectional waves of interviews show a shift from mentions of distant collectives (e.g., far-flung countries) at Wave 1 to local collectives (e.g., risk groups) as the pandemic became of more immediate concern (Wave 2) and declined (Wave 3). Semi-automated content analysis of media coverage shows similar results. Thematic analyses of the discourse associated with collectives revealed that many were consistently perceived as heroes, villains and victims.

Policy attitudes, ideological values and social representations

This article reviews research on policy attitudes and ideological values from the perspective of social representations theory. In the first part of the paper, key features of lay political thinking are presented, its pragmatic imperative, its focus on communication and the social functions of shared knowledge. Objectification transforms abstract and group-neutral ideological values into concrete and socially useful knowledge, in particular stereotypes of value-conforming and value-violating groups. Such shared understandings of intergroup relations provide citizens with common reference knowledge which provides the cognitive and cultural basis of policy attitudes. Social representations theory further suggests that lay knowledge reflects the social context in which it has been elaborated (anchoring), an aspect which allows conceptualising aggregate-level differences in policy attitudes. In the second part of the paper, a model of lay conceptions of social order is outlined which organises four shared conceptions of social order, along with the stereotype-based thinking associated with each conception: Moral order, Free Market, Social diversity and Structural inequality. We conclude by arguing that policy attitudes are symbolic devices expressed to justify or to challenge existing social arrangements.

Contexts and typologies in the analysis of welfare state legitimacy : a social psychological approach to political opinion formation

This dissertation analyses public opinion towards the welfare state across 29 European countries. Based on an interdisciplinary approach combining social psychological, sociological, and public opinion approaches to political opinion formation, it investigates how social position and shared beliefs shape perceived legitimacy of welfare institutions, and how social contexts impact on the processes of opinion formation. Drawing on social representations theory, as well as socialization and self-interest approaches, the dissertation analyses the role of social position in lay support for institutional solidarity. Normative beliefs-defined as preferred views regarding the organisation of social relations-mediate the effect of social position on welfare support. In addition, drawing on public opinion literature, the dissertation analyses opinion formation as a function of country-level structural (e.g., level of social spending, unemployment) and ideological factors (e.g., level of meritocracy). The dissertation comprises two theoretical and four empirical chapters. Three of the empirical chapters use data from the European Social Survey 2008. Using multilevel and typological approaches, the dissertation contributes to welfare attitude literature by showing that normative beliefs, such as distrust or egalitarianism, function as underlying mechanisms that link social position to policy attitudes (Chapter 3), and that characteristics of the national contexts influence the processes of political opinion formation (Chapters 3 and 4). Chapter 5 proposes and predicts a typology of the relationship between attitudes towards solidarity and attitudes towards control, reflecting the two central domains of government intervention. Finally, Chapter 6 examines welfare support in the realm of action and social protest, using data from a survey on Spanish Indigados activists. The findings of this dissertation inform contemporary debates about welfare state legitimacy and retrenchment. - Cette thèse avait pour but d'analyser l'opinion publique envers l'Etat social dans 29 pays européens. Basée sur une approche interdisciplinaire qui combine des perspectives psycho-sociales, sociologiques et d'opinion publique sur la formation d'opinion politique, la thèse étudie comment la position sociale et les croyances partagées façonnent la légitimité perçue des institutions de l'Etat social, et comment les contextes sociaux influencent les processus de formation d'opinion. Basée sur la théorie des représentations sociales, ainsi qu'une approche de socialisation et d'intérêt propre, cette thèse analyse le rôle des positions sociales dans le soutien envers la solidarité institutionnelle. Les croyances normatives-définies comme les visions préférées de l'organisation des rapports sociaux-médiatisent l'effet de la position sociale sur le soutien pour l'Etat social. De plus, s'inspirant de la littérature sur l'opinion publique, la thèse analyse la formation d'opinion en fonction des facteurs structurels (ex. le taux de dépenses sociales, le chômage) et idéologiques (ex. le degré de méritocratie). Cette thèse est composée de deux chapitres théoriques et quatre chapitres empiriques. Trois chapitres empiriques utilisent des données provenant de l'enquête European Social Survey 2008. Appliquant des approches multi-niveux et typoloqiques, la thèse contribue à la littérature sur les attitudes envers l'Etat social en montrant que les croyances normatives, telles que la méfiance ou l'égalitarisme, fonctionnent comme des mécanismes sous-jacents qui relient la position sociale aux attitudes politiques (Chapitre 3), et que les caractéristiques des contextes nationaux influencent les processus de formation d'opinion politique (Chapitres 3 et 4). Le chapitre 5 propose et prédit une typologie sur le rapport entre les attitudes envers la solidarité et celles envers le contrôle, renvoyant à deux domaines centraux de régulation étatique. Enfin, le chapitre 6 examine le soutien à l'Etat social dans le domaine de l'action protestataire, utilisant des données d'une enquête menée auprès des militants espagnols du mouvement des Indignés. Les résultats de cette thèse apportent des éléments qui éclairent les débats contemporains sur la légitimité de l'Etat social et son démantèlement.

How life history and demography promote or inhibit the evolution of helping behaviours.

In natural populations, dispersal tends to be limited so that individuals are in local competition with their neighbours. As a consequence, most behaviours tend to have a social component, e.g. they can be selfish, spiteful, cooperative or altruistic as usually considered in social evolutionary theory. How social behaviours translate into fitness costs and benefits depends considerably on life-history features, as well as on local demographic and ecological conditions. Over the last four decades, evolutionists have been able to explore many of the consequences of these factors for the evolution of social behaviours. In this paper, we first recall the main theoretical concepts required to understand social evolution. We then discuss how life history, demography and ecology promote or inhibit the evolution of helping behaviours, but the arguments developed for helping can be extended to essentially any social trait. The analysis suggests that, on a theoretical level, it is possible to contrast three critical benefit-to-cost ratios beyond which costly helping is selected for (three quantitative rules for the evolution of altruism). But comparison between theoretical results and empirical data has always been difficult in the literature, partly because of the perennial question of the scale at which relatedness should be measured under localized dispersal. We then provide three answers to this question.

Christians, Muslims, Jews, and their religions

Depending on the context, Christians, Muslims and Jews have constructed their own religion, perceived the religions of others, and articulated relations between religions in different ways. This paper examines the rise in history of the three communities, which came to identify themselves through their religions and have been highly sensitive to differences. It indicates common features and parallels of which adherents may have been more or less conscious. The central question in such research is what persons and groups mean in particular situations when they call themselves Christian, Muslim or Jewish. The variety of personal and group identities in the three religious communities has been concealed partly by religious leaderships concerned with the survival of their flocks, and partly by the use of the general concepts of Christianity, Islam and Judaism with which believers have been called to identify. These concepts have shut people into separate religious pigeonholes and could thus be used to support ethnic, social and other rivalries. This pigeonholing has also confronted more spiritually-oriented people with problems of social identity, religious belonging and spiritual authenticity.

Wolves in sheep's clothing: SDO asymmetrically predicts perceived ethnic victimization among White and Latino students across three years

Dominant groups have claimed to be the targets of discrimination on several historical occasions during violent intergroup conflict and genocide.The authors argue that perceptions of ethnic victimization among members of dominant groups express social dominance motives and thus may be recruited for the enforcement of group hierarchy. They examine the antecedents of perceived ethnic victimization among dominants, following 561 college students over 3 years from freshman year to graduation year. Using longitudinal, cross-lagged structural equation modeling, the authors show that social dominance orientation (SDO) positively predicts perceived ethnic victimization among Whites but not among Latinos, whereas victimization does not predict SDO over time. In contrast, ethnic identity and victimization reciprocally predicted each other longitudinally with equal strength among White and Latino students. SDO is not merely a reflection of contextualized social identity concerns but a psychological, relational motivation that undergirds intergroup attitudes across extended periods of time and interacts with the context of group dominance.

«Où, quand, et comment ?» : Évolution des conduites agressives en football et en hockey sur glace

RésuméCette étude a pour objectif d'observer l'évolution des actes agressifs dans deux sports d'équipes en fonction de facteurs situationnels (périodes de jeu, lieu de la faute, état du score) et du type d'agressions (instrumentales, hostile). 60 matchs professionnels de football et de hockey sur glace ont été filmés puis analysés à l'aide de grilles d'observation différenciant les deux types d'agressions. Les résultats révèlent que dans ces deux sports, les agressions instrumentales sont plus fréquentes dans les zones importantes du terrain (milieu ou défense) ou lorsque le score est serré. En revanche, les agressions hostiles ne varient pas (ou peu) selon ces facteurs. Les résultats sont discutés au regard de la théorie de l'apprentissage social et de l'hypothèse frustration-agression.AbstractThis study aims at examining observed aggression in two team sports as a function of situational triggers (periods, zones of field, games score) and of type of aggression (instrumental, hostile). 60 soccer and ice hockey games were recorded and analyzed using a grid that differentiates the two types of aggression. The results revealed that theses two sports, instrumental aggressions were more frequent in important zones of field (neutral or defensive ones) and in tied score situations. However, no difference was found for hostile aggression according to these factors. The discussion focused on the social learning theory and frustration-aggression hypothesis.

Man Made Black Holes and Big Bangs: Diffusion and Integration of Scientific Information into Everyday Thinking

Drawing on Social Representations Theory, this study investigates focalisation and anchoring during the diffusion of information concerning the Large Hadron Collider (LHC), the particle accelerator at the European Organisation for Nuclear Research (CERN). We hypothesised that people focus on striking elements of the message, abandoning others, that the nature of the initial information affects diffusion of information, and that information is anchored in prior attitudes toward CERN and science. A serial reproduction experiment with two generations and four chains of reproduction diffusing controversial versus descriptive information about the LHC shows a reduction of information through generations, the persistence of terminology regarding the controversy and a decrease of other elements for participants exposed to polemical information. Concerning anchoring, positive attitudes toward CERN and science increase the use of expert terminology unrelated to the controversy. This research highlights the relevance of a social representational approach in the public understanding of science.

Discovery of the faithfulness gene: a model of transmission and transformation of scientific information.

The purpose of this paper is to study the diffusion and transformation of scientific information in everyday discussions. Based on rumour models and social representations theory, the impact of interpersonal communication and pre-existing beliefs on transmission of the content of a scientific discovery was analysed. In three experiments, a communication chain was simulated to investigate how laypeople make sense of a genetic discovery first published in a scientific outlet, then reported in a mainstream newspaper and finally discussed in groups. Study 1 (N=40) demonstrated a transformation of information when the scientific discovery moved along the communication chain. During successive narratives, scientific expert terminology disappeared while scientific information associated with lay terminology persisted. Moreover, the idea of a discovery of a faithfulness gene emerged. Study 2 (N=70) revealed that transmission of the scientific message varied as a function of attitudes towards genetic explanations of behaviour (pro-genetics vs. anti-genetics). Pro-genetics employed more scientific terminology than anti-genetics. Study 3 (N=75) showed that endorsement of genetic explanations was related to descriptive accounts of the scientific information, whereas rejection of genetic explanations was related to evaluative accounts of the information.

Voir le monde à travers les lunettes du métacontraste : un modèle mathématique inspiré de la psychologie sociale

Résumé La théorie de l'autocatégorisation est une théorie de psychologie sociale qui porte sur la relation entre l'individu et le groupe. Elle explique le comportement de groupe par la conception de soi et des autres en tant que membres de catégories sociales, et par l'attribution aux individus des caractéristiques prototypiques de ces catégories. Il s'agit donc d'une théorie de l'individu qui est censée expliquer des phénomènes collectifs. Les situations dans lesquelles un grand nombre d'individus interagissent de manière non triviale génèrent typiquement des comportements collectifs complexes qui sont difficiles à prévoir sur la base des comportements individuels. La simulation informatique de tels systèmes est un moyen fiable d'explorer de manière systématique la dynamique du comportement collectif en fonction des spécifications individuelles. Dans cette thèse, nous présentons un modèle formel d'une partie de la théorie de l'autocatégorisation appelée principe du métacontraste. À partir de la distribution d'un ensemble d'individus sur une ou plusieurs dimensions comparatives, le modèle génère les catégories et les prototypes associés. Nous montrons que le modèle se comporte de manière cohérente par rapport à la théorie et est capable de répliquer des données expérimentales concernant divers phénomènes de groupe, dont par exemple la polarisation. De plus, il permet de décrire systématiquement les prédictions de la théorie dont il dérive, notamment dans des situations nouvelles. Au niveau collectif, plusieurs dynamiques peuvent être observées, dont la convergence vers le consensus, vers une fragmentation ou vers l'émergence d'attitudes extrêmes. Nous étudions également l'effet du réseau social sur la dynamique et montrons qu'à l'exception de la vitesse de convergence, qui augmente lorsque les distances moyennes du réseau diminuent, les types de convergences dépendent peu du réseau choisi. Nous constatons d'autre part que les individus qui se situent à la frontière des groupes (dans le réseau social ou spatialement) ont une influence déterminante sur l'issue de la dynamique. Le modèle peut par ailleurs être utilisé comme un algorithme de classification automatique. Il identifie des prototypes autour desquels sont construits des groupes. Les prototypes sont positionnés de sorte à accentuer les caractéristiques typiques des groupes, et ne sont pas forcément centraux. Enfin, si l'on considère l'ensemble des pixels d'une image comme des individus dans un espace de couleur tridimensionnel, le modèle fournit un filtre qui permet d'atténuer du bruit, d'aider à la détection d'objets et de simuler des biais de perception comme l'induction chromatique. Abstract Self-categorization theory is a social psychology theory dealing with the relation between the individual and the group. It explains group behaviour through self- and others' conception as members of social categories, and through the attribution of the proto-typical categories' characteristics to the individuals. Hence, it is a theory of the individual that intends to explain collective phenomena. Situations involving a large number of non-trivially interacting individuals typically generate complex collective behaviours, which are difficult to anticipate on the basis of individual behaviour. Computer simulation of such systems is a reliable way of systematically exploring the dynamics of the collective behaviour depending on individual specifications. In this thesis, we present a formal model of a part of self-categorization theory named metacontrast principle. Given the distribution of a set of individuals on one or several comparison dimensions, the model generates categories and their associated prototypes. We show that the model behaves coherently with respect to the theory and is able to replicate experimental data concerning various group phenomena, for example polarization. Moreover, it allows to systematically describe the predictions of the theory from which it is derived, specially in unencountered situations. At the collective level, several dynamics can be observed, among which convergence towards consensus, towards frag-mentation or towards the emergence of extreme attitudes. We also study the effect of the social network on the dynamics and show that, except for the convergence speed which raises as the mean distances on the network decrease, the observed convergence types do not depend much on the chosen network. We further note that individuals located at the border of the groups (whether in the social network or spatially) have a decisive influence on the dynamics' issue. In addition, the model can be used as an automatic classification algorithm. It identifies prototypes around which groups are built. Prototypes are positioned such as to accentuate groups' typical characteristics and are not necessarily central. Finally, if we consider the set of pixels of an image as individuals in a three-dimensional color space, the model provides a filter that allows to lessen noise, to help detecting objects and to simulate perception biases such as chromatic induction.

Firm's network capability and innovation performance: evidences from China hi-tech industry

ABSTRACT : A firm's competitive advantage can arise from internal resources as well as from an interfirm network. -This dissertation investigates the competitive advantage of a firm involved in an innovation network by integrating strategic management theory and social network theory. It develops theory and provides empirical evidence that illustrates how a networked firm enables the network value and appropriates this value in an optimal way according to its strategic purpose. The four inter-related essays in this dissertation provide a framework that sheds light on the extraction of value from an innovation network by managing and designing the network in a proactive manner. The first essay reviews research in social network theory and knowledge transfer management, and identifies the crucial factors of innovation network configuration for a firm's learning performance or innovation output. The findings suggest that network structure, network relationship, and network position all impact on a firm's performance. Although the previous literature indicates that there are disagreements about the impact of dense or spare structure, as well as strong or weak ties, case evidence from Chinese software companies reveals that dense and strong connections with partners are positively associated with firms' performance. The second essay is a theoretical essay that illustrates the limitations of social network theory for explaining the source of network value and offers a new theoretical model that applies resource-based view to network environments. It suggests that network configurations, such as network structure, network relationship and network position, can be considered important network resources. In addition, this essay introduces the concept of network capability, and suggests that four types of network capabilities play an important role in unlocking the potential value of network resources and determining the distribution of network rents between partners. This essay also highlights the contingent effects of network capability on a firm's innovation output, and explains how the different impacts of network capability depend on a firm's strategic choices. This new theoretical model has been pre-tested with a case study of China software industry, which enhances the internal validity of this theory. The third essay addresses the questions of what impact network capability has on firm innovation performance and what are the antecedent factors of network capability. This essay employs a structural equation modelling methodology that uses a sample of 211 Chinese Hi-tech firms. It develops a measurement of network capability and reveals that networked firms deal with cooperation between, and coordination with partners on different levels according to their levels of network capability. The empirical results also suggests that IT maturity, the openness of culture, management system involved, and experience with network activities are antecedents of network capabilities. Furthermore, the two-group analysis of the role of international partner(s) shows that when there is a culture and norm gap between foreign partners, a firm must mobilize more resources and effort to improve its performance with respect to its innovation network. The fourth essay addresses the way in which network capabilities influence firm innovation performance. By using hierarchical multiple regression with data from Chinese Hi-tech firms, the findings suggest that there is a significant partial mediating effect of knowledge transfer on the relationships between network capabilities and innovation performance. The findings also reveal that the impacts of network capabilities divert with the environment and strategic decision the firm has made: exploration or exploitation. Network constructing capability provides a greater positive impact on and yields more contributions to innovation performance than does network operating capability in an exploration network. Network operating capability is more important than network constructing capability for innovative firms in an exploitation network. Therefore, these findings highlight that the firm can shape the innovation network proactively for better benefits, but when it does so, it should adjust its focus and change its efforts in accordance with its innovation purposes or strategic orientation.

On the evolution of harming and recognition in finite panmictic and infinite structured populations.

Natural selection may favor two very different types of social behaviors that have costs in vital rates (fecundity and/or survival) to the actor: helping behaviors, which increase the vital rates of recipients, and harming behaviors, which reduce the vital rates of recipients. Although social evolutionary theory has mainly dealt with helping behaviors, competition for limited resources creates ecological conditions in which an actor may benefit from expressing behaviors that reduce the vital rates of neighbors. This may occur if the reduction in vital rates decreases the intensity of competition experienced by the actor or that experienced by its offspring. Here, we explore the joint evolution of neutral recognition markers and marker-based costly conditional harming whereby actors express harming, conditional on actor and recipient bearing different conspicuous markers. We do so for two complementary demographic scenarios: finite panmictic and infinite structured populations. We find that marker-based conditional harming can evolve under a large range of recombination rates and group sizes under both finite panmictic and infinite structured populations. A direct comparison with results for the evolution of marker-based conditional helping reveals that, if everything else is equal, marker-based conditional harming is often more likely to evolve than marker-based conditional helping.

Voir le monde à travers les lunettes du métacontraste: un modèle mathématique inspiré de la psychologie sociale

La théorie de l'autocatégorisation est une théorie de psychologie sociale qui porte sur la relation entre l'individu et le groupe. Elle explique le comportement de groupe par la conception de soi et des autres en tant que membres de catégories sociales, et par l'attribution aux individus des caractéristiques prototypiques de ces catégories. Il s'agit donc d'une théorie de l'individu qui est censée expliquer des phénomènes collectifs. Les situations dans lesquelles un grand nombre d'individus interagissent de manière non triviale génèrent typiquement des comportements collectifs complexes qui sont difficiles à prévoir sur la base des comportements individuels. La simulation informatique de tels systèmes est un moyen fiable d'explorer de manière systématique la dynamique du comportement collectif en fonction des spécifications individuelles. Dans cette thèse, nous présentons un modèle formel d'une partie de la théorie de l'autocatégorisation appelée principe du métacontraste. À partir de la distribution d'un ensemble d'individus sur une ou plusieurs dimensions comparatives, le modèle génère les catégories et les prototypes associés. Nous montrons que le modèle se comporte de manière cohérente par rapport à la théorie et est capable de répliquer des données expérimentales concernant divers phénomènes de groupe, dont par exemple la polarisation. De plus, il permet de décrire systématiquement les prédictions de la théorie dont il dérive, notamment dans des situations nouvelles. Au niveau collectif, plusieurs dynamiques peuvent être observées, dont la convergence vers le consensus, vers une fragmentation ou vers l'émergence d'attitudes extrêmes. Nous étudions également l'effet du réseau social sur la dynamique et montrons qu'à l'exception de la vitesse de convergence, qui augmente lorsque les distances moyennes du réseau diminuent, les types de convergences dépendent peu du réseau choisi. Nous constatons d'autre part que les individus qui se situent à la frontière des groupes (dans le réseau social ou spatialement) ont une influence déterminante sur l'issue de la dynamique. Le modèle peut par ailleurs être utilisé comme un algorithme de classification automatique. Il identifie des prototypes autour desquels sont construits des groupes. Les prototypes sont positionnés de sorte à accentuer les caractéristiques typiques des groupes, et ne sont pas forcément centraux. Enfin, si l'on considère l'ensemble des pixels d'une image comme des individus dans un espace de couleur tridimensionnel, le modèle fournit un filtre qui permet d'atténuer du bruit, d'aider à la détection d'objets et de simuler des biais de perception comme l'induction chromatique. Abstract Self-categorization theory is a social psychology theory dealing with the relation between the individual and the group. It explains group behaviour through self- and others' conception as members of social categories, and through the attribution of the proto-typical categories' characteristics to the individuals. Hence, it is a theory of the individual that intends to explain collective phenomena. Situations involving a large number of non-trivially interacting individuals typically generate complex collective behaviours, which are difficult to anticipate on the basis of individual behaviour. Computer simulation of such systems is a reliable way of systematically exploring the dynamics of the collective behaviour depending on individual specifications. In this thesis, we present a formal model of a part of self-categorization theory named metacontrast principle. Given the distribution of a set of individuals on one or several comparison dimensions, the model generates categories and their associated prototypes. We show that the model behaves coherently with respect to the theory and is able to replicate experimental data concerning various group phenomena, for example polarization. Moreover, it allows to systematically describe the predictions of the theory from which it is derived, specially in unencountered situations. At the collective level, several dynamics can be observed, among which convergence towards consensus, towards frag-mentation or towards the emergence of extreme attitudes. We also study the effect of the social network on the dynamics and show that, except for the convergence speed which raises as the mean distances on the network decrease, the observed convergence types do not depend much on the chosen network. We further note that individuals located at the border of the groups (whether in the social network or spatially) have a decisive influence on the dynamics' issue. In addition, the model can be used as an automatic classification algorithm. It identifies prototypes around which groups are built. Prototypes are positioned such as to accentuate groups' typical characteristics and are not necessarily central. Finally, if we consider the set of pixels of an image as individuals in a three-dimensional color space, the model provides a filter that allows to lessen noise, to help detecting objects and to simulate perception biases such as chromatic induction.