Over the last ten years, Oosterhof and Todorov's valence-dominance model has emerged as the most prominent account of how people evaluate faces on social dimensions. In this model, two dimensions (valence and dominance) underpin social judgments of faces. Because this model has primarily been developed and tested in Western regions, it is unclear whether these findings apply to other regions. We addressed this question by replicating Oosterhof and Todorov's methodology across 11 world regions, 41 countries, and 11,570 participants. When we used Oosterhof and Todorov's original analysis strategy, the valence-dominance model generalized across regions. When we used an alternative methodology to allow for correlated dimensions we observed much less generalization. Collectively, these results suggest that, while the valence-dominance model generalizes very well across regions when dimensions are forced to be orthogonal, regional differences are revealed when we use different extraction methods, correlate and rotate the dimension reduction solution.

Trustworthiness and dominance impressions summarize trait judgments from faces. Judgments on these key traits are negatively correlated to each other in impressions of female faces, implying less differentiated impressions of female faces. Here we test whether this is true across many trait judgments and whether less differentiated impressions of female faces originate in different facial information used for male and female impressions or different evaluation of the same information. Using multidimensional rating datasets and data-driven modeling, we show that (1) impressions of women are less differentiated and more valence-laden than impressions of men, and find that (2) these impressions are based on similar visual information across face genders. Female face impressions were more highly intercorrelated and were better explained by valence (Study 1). These intercorrelations were higher when raters more strongly endorsed gender stereotypes. Despite the gender difference, male and female impression models-derived from separate trustworthiness and dominance ratings of male and female faces-were similar to each other (Study 2). Further, both male and female models could manipulate impressions of faces of both genders (Study 3). The results highlight the high-level, evaluative effect of face gender in impression formation-women are judged negatively to the extent their looks do not conform to expectations, not because people use different facial information across genders, but because people evaluate the information differently across genders.

Competence impressions from faces affect important decisions, such as hiring and voting. Here, using data-driven computational models, we identified the components of the competence stereotype. Faces manipulated by a competence model varied in attractiveness (Experiment 1a). However, faces could be manipulated on perceived competence controlling for attractiveness (Experiment 1b); moreover, faces perceived as more competent but not attractive were also perceived as more confident and masculine, suggesting a bias to perceive male faces as more competent than female faces (Experiment 2). Correspondingly, faces manipulated to appear competent but not attractive were more likely to be classified as male (Experiment 3). When masculinity cues that induced competence impressions were applied to real-life images, these cues were more effective on male faces (Experiment 4). These findings suggest that the main components of competence impressions are attractiveness, confidence, and masculinity, and they reveal gender biases in how we form important impressions of other people.

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This paper was accepted for publication in Nature Human Behaviour. This is a non-final and non-copy-edited version of the paper.