Rapid Visual Perception of Interracial Crowds: Racial Category Learning From Emotional Segregation

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Abstract

Drawing from research on social identity and ensemble coding, we theorize that crowd perception provides a powerful mechanism for social category learning. Crowds include allegiances that may be distinguished by visual cues to shared behavior and mental states, providing perceivers with direct information about social groups and thus a basis for learning social categories. Here, emotion expressions signaled group membership: to the extent that a crowd exhibited emotional segregation (i.e., was segregated into emotional subgroups), a visible characteristic (race) that incidentally distinguished emotional subgroups was expected to support categorical distinctions. Participants were randomly assigned to view interracial crowds in which emotion differences between (black vs. white) subgroups were either small (control condition) or large (emotional segregation condition). On each trial, participants saw crowds of 12 faces (6 black, 6 white) for roughly 300 ms and were asked to estimate the average emotion of the entire crowd. After all trials, participants completed a racial categorization task and self-report measure of race essentialism. As predicted, participants exposed to emotional segregation (vs. control) exhibited stronger racial category boundaries and stronger race essentialism. Furthermore, such effects accrued via ensemble coding, a visual mechanism that summarizes perceptual information: emotional segregation strengthened participants’ racial category boundaries to the extent that segregation limited participants’ abilities to integrate emotion across racial subgroups. Together with evidence that people observe emotional segregation in natural environments, these findings suggest that crowd perception mechanisms support racial category boundaries and race essentialism.

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