Abstract

Previous research shows that perceivers have distinct mental representations of ingroups and outgroups even when groups are novel and not defined by physical attributes. Here, we leverage the minimal group paradigm, the reverse correlation method, and machine learning to parse the visual ingredients of group membership. In Study 1, we found that ingroup faces are trusted more than outgroup faces and that facial stereotypes of trustworthiness resemble those of the ingroup/outgroup distinction. However, in Study 2 we showed that such facial stereotypes of group membership resembled those of competence more than trustworthiness and dominance. Together, these findings suggest that even though trustworthiness is an important visual ingredient of the ingroup/outgroup distinction, people may rely on facial cues indicating competence the most to guide their visualization of novel ingroup and outgroup members, highlighting the nuanced nature of ingroup bias in face processing.

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