Global Meta-Analysis Finds Consistent Preference for Women’s Faces Over Men’s Across Cultures

A meta-analysis of 1.5 million facial ratings drawn from 52 previously published studies identified a robust “gender attractiveness gap” (GAP). Across 76 countries and a pooled sample of roughly 28,500 participants, women’s faces were rated, on average, more attractive than men’s. Women rated other women’s faces substantially higher than men’s faces, while men’s faces received similarly low scores from both sexes. The GAP narrowed for images of elderly individuals and for people of African descent, and it disappeared when participants evaluated their own attractiveness.

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The notion that women are the “fairer sex” has long been anecdotal, dating back to Charles Darwin’s observations of sexual dimorphism in non-human species. Prior to this work, researchers assumed a human exception without empirical verification. The present study was designed explicitly to test whether a measurable sex difference in facial attractiveness exists across diverse populations.

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• Eugen Wassiliwizky, psychologist, Max Planck Institute for Empirical Aesthetics (study co-author).

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• Karel Kleisner, evolutionary biologist, Charles University in Prague (independent commentator).

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• An international consortium of researchers who compiled the underlying datasets.

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• Participants: ~28,500 individuals worldwide.

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• Ratings: >1.5 million face evaluations.

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• Studies Included: 52 peer-reviewed investigations.

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• Geographic Scope: 76 nations spanning North America, Europe, and Asia.

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• Key Metrics: Women’s faces received higher mean attractiveness scores; the GAP attenuated for older and African-descent faces.

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The findings suggest that human facial attractiveness may retain a universal bias toward feminine features, challenging the view that male ornamentation predominates in mate selection. The cross-cultural consistency supports a potential evolutionary basis, while the observed moderation for specific age and ethnic groups highlights the role of cultural standards in shaping aesthetic judgments.

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Wassiliwizky emphasized that facial structure accounts for part of the GAP but not its entirety, noting that women may “appreciate each other’s beauty more.” He also acknowledged that the study’s reliance on existing datasets limits direct control over aesthetic variables. Kleisner praised the confirmation of the GAP yet warned that the analysis lacks sensitivity to African beauty norms, calling this a major limitation.

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• Dataset Design: The original studies were not intended to examine sex differences, potentially introducing uncontrolled confounds.

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• Self-Rating Discrepancy: The absence of a GAP in self-attractiveness ratings suggests a contextual bias not captured by the meta-analysis.

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• Cultural Specificity: Critics highlight insufficient representation of African aesthetic criteria, which may affect the generalizability of the results.

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• “took it for granted that women are the fairer sex and theorized about what evolutionary principle could have led to this phenomenon, but the existence of the gap itself was never actually tested,” — Eugen Wassiliwizky, Psychologist, Max Planck Institute for Empirical Aesthetics

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• “can be partly explained by differences in facial structure, but not entirely,” — Eugen Wassiliwizky, statement

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• “Women might find other women’s faces more attractive than men’s because they’re appreciating “each other’s beauty more,” Wassiliwizky told New Scientist’s Michael Le Page last year, after the study was posted to the preprint server bioRxiv.” — Eugen Wassiliwizky, interview with *New Scientist*

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• “A major limitation of the study is its lack of sensitivity to the specific aesthetics of African beauty,” — Karel Kleisner, Evolutionary Biologist, Charles University

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• “Additionally, the GAP narrowed when raters viewed faces of elderly individuals and those of people of African descent.” — Study authors, Max Planck Institute for Empirical Aesthetics

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Researchers plan targeted experiments that manipulate facial masculinity and femininity while controlling for age and ethnicity, aiming to isolate causal mechanisms behind the GAP. Additional work will seek culturally specific datasets, particularly from African contexts, to address the noted limitation and to explore why self-rating does not replicate the observed bias.

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