Graduate Student Research Symposium 2025

Research on visual judgments suggests that social evaluations of faces are influenced by gendered associations with adjectives. This study examines whether similar patterns hold at the linguistic level across 57 countries and languages using a multilevel modeling approach. We analyze cosine similarity scores between gendered words (male and female) and adjectives to test whether language-based associations mirror biases observed in visual perception. Building on prior work in social perception, we assess whether adjectives that predict male or female face evaluations in visual tasks systematically align with gendered language representations across diverse linguistic and cultural contexts. By modeling adjective-gender associations as nested within languages, we evaluate the robustness of these effects globally. Our findings contribute to understanding whether visual gender biases emerge from or are reinforced by linguistic structures, with implications for theories of social perception, gender stereotyping, and the interplay between language and cognition.