Social identity and self-categorization processes in organizational contexts

Although aspects of social identity theory are familiar to organizational psychologists, its elaboration, through self-categorization theory, of how social categorization and prototype-based depersonalization actually produce social identity effects is less well known. We describe these processes, relate self-categorization theory to social identity theory, describe new theoretical developments in detail, and show how these developments can address a: range of organizational phenomena. We discuss cohesion and deviance, leadership, subgroup and sociodemographic structure, and mergers and acquisitions.

Why does dissimilarity matter? Exploring self-categorization, self-enhancement, and uncertainty reduction

Although relational demographers have based their arguments on self-categorization theory, they have paid little attention to the underlying processes associated with this theory. The authors examined whether demographic dissimilarity affects individuals' identification with groups by affecting the group's prototype valence and clarity and the individual's perceptions of self-prototypicality. The data showed that the proportion of women and non-Australians in 34 work groups negatively influenced prototype valence, prototype clarity, and self-prototypicality for all members of the group. These results provide support for the continued use of self-categorization theory by relational demographers.

A self-categorization explanation for the third-person effect

Three studies tested a self-categorization theory explanation for the third-person effect. In Study 1 (N = 49) undergraduate students judged the influence of the National Enquirer, Wall Street Journal, and TV show Friends on themselves, relative to low- and high-status outgroup members, and other undergraduate students. The profile of first- and third-person perceptions was largely consistent with predictions, and the size of the third-person effect decreased as perceived similarity to target others increased-but only for media that were normative for comparison others. Study 2 (N = 49) provided evidence for this process with different media and showed that the profile of first- and third-person perceptions matched closely with perceived norms of media consumption-but not the social desirability of those media. Study 3 (N = 64) showed that the third-person effect for the same media and target other shifts with the frame of reference in which the judgment is made. Taken together, the findings are consistent with self-categorization theory and difficult to reconcile with other explanations.

Social identity, self-categorization, and the communication of group norms

We articulate the role of norms within the social identity perspective as a basis for theorizing a number of manifestly communicative phenomena. We describe how group norms are cognitively represented as context-dependent prototypes that capture the distinctive properties of groups. The same process that governs the psychological salience of different prototypes, and thus generates group normative behavior, can be used to understand the formation, perception, and diffusion of norms, and also how some group members, for example, leaders, have more normative influence than others. life illustrate this process across a number of phenomena and make suggestions for future interfaces between the social identity perspective and communication research. We believe that the social identity approach represents a truly integrative force for the communication discipline.

Racioethnic differences in job satisfaction: A test of orthogonal cultural identification theory and self -categorization theory

The theories of orthogonal cultural identification and self-categorization are offered as links in examining the possible racioethnic differences in job satisfaction. It is posited that racioethnicity (Cox & Blake, 1991) is multidimensional with at least three conceptually distinct dimensions. Since there is a need for consistent terminology with respect to these distinct dimensions, the following new terms are offered to differentiate among them: "physioethnicity" refers to the physiological dimension of racioethnicity; "socioethnicity" refers to the sociocultural dimension; and "psychoethnicity" refers to the psychological dimension.^ Results showed that for the dominant group (Hispanics in this case) (1) bicultural and multicultural individuals were more satisfied with coworkers than acultural and monocultural individuals and (2) individuals with higher strength of psychoethnicity were more satisfied with coworkers, the work itself, and supervision than those with lower strength of psychoethnicity. The findings suggest racioethnic differences within the dominant group and between groups beyond race. ^

A social identity theory of leadership

A social identity theory of leadership is described that views leadership as a group process generated by social categorization and prototype-based depersonalization processes associated with social identity. Group identification, as self-categorization, constructs an intragroup prototypicality gradient that invests the most prototypical member with the appearance of having influence; the appearance arises because members cognitively and behaviorally conform to the prototype. The appearance of influence becomes a reality through depersonalized social attraction processes that make followers agree and comply with the leader's ideas and suggestions. Consensual social attraction also imbues the leader with apparent status and creates a status-based structural differentiation within the group into leader(s) and followers, which has characteristics of unequal status intergroup relations. In addition, a fundamental attribution process constructs a charismatic leadership personality for the leader, which further empowers the leader and sharpens the leader-follower status differential. Empirical support for the theory is reviewed and a range of implications discussed, including intergroup dimensions, uncertainty reduction and extremism, power, and pitfalls of prototype-based leadership.

Improving attitude-behavior correspondence through exposure to normative support from a salient ingroup

Two experiments were conducted to test predictions derived from social identity/self-categorization theory concerning the role of group norms in attitude-behavior consistency. In Experiment 1, 160 students who could be classified as having a more or less certain target attitude were exposed to attitude congruent versus incongruent normative support from a relevant reference group (own university) under conditions of low versus high group salience. Experiment 2 was very similar in design and methodology (N=180), but a different correlate of attitude accessibility was used (an experimental manipulation of repeated expression), the target attitude was changed, and the reference group was gender. Across the 2 experiments there was consistent support for the hypothesis that participants would behave more in accordance with their attitudes when they received normative support for, rather than opposition to, their original attitude from a relevant reference group (i.e., their ingroup, not an outgroup). There was slightly weaker support for the second hypothesis that this effect would be stronger under high-than low-salience conditions. The third hypothesis (see Fazio, 1986), that attitude certainty and repeated expression of the attitude would strengthen attitude-behavior consistency, was well supported, as was the expectation that accessibility effects would be independent of reference group norm effects on attitude-behavior consistency.

Relations between high and low power groups: The importance of legitimacy

Using a social identity perspective, two experiments examined the effects of power and the legitimacy of power differentials on intergroup bias. In Experiment 1, 125 math-science students were led to believe that they had high or low representation in a university decision-making body relative to social-science students and that this power position was either legitimate or illegitimate. Power did not have an independent effect on bias; rather, members of both high and low power groups showed more bias when the power hierarchy was illegitimate than when it was legitimate. This effect was replicated in Experiment 2 (N =105). In addition, Experiment 2 showed that groups located within an unfair power hierarchy expected the superordinate power body to be more discriminatory than did those who had legitimately high or low power. The results are discussed in terms of their implications for group relations.

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.

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.