If you have any problems related to the accessibility of any content (or if you want to request that a specific publication be accessible), please contact firstname.lastname@example.org.
Explaining Asymmetric Intergroup Judgments through Differential Aggregation: Computer Simulations and Some New Evidence
AltmetricsView Usage Statistics
Outgroups are often judged to be less differentiated, more homogeneous, and more polarized than ingroups. Theoretical accounts of this outgroup homogeneity effect (OHE) emphasize impoverished knowledge of outgroups, qualitatively different memory representations, or the motivational impact of group membership. A parsimonious explanation for all these findings is proposed, based on the assumption that most operational variants of the OHE can be understood as a result of differential aggregation from unequal stimulus samples. Given that (a) ingroup-related samples are typically larger and richer than outgroup-related samples, and (b) perception in the social domain rests on multiple probabilistic cues, latent information can be extracted more efficiently for ingroups than outgroups. The processes through which differential aggregation in a noisy environment produces different measures of the OHE, the so-called outgroup co-variation effect, outgroup polarization, and other paradigmatic findings, are explicated in a series of computer simulations using the BIAS model (Fiedler, 1996). The model accounts for some notable reversals of these findings (ingroup homogeneity, ingroup co-variation) under specified conditions. In addition, some new empirical findings are reported that support distinct predictions of BIAS.