Gender Biases in
Social Face Perception
People make intuitive judgments of other people’s traits (e.g., intelligence, kindness) from faces. Such intuitive judgments reveal biases people have about sexes (e.g., “men are competitive”, “women are emotional“).
Perceivers’ expectations about gender (e.g., gender stereotypes) affect social judgments of faces of different genders. Dimensionality reduction and data-driven face models found that human raters’ impressions of female faces are more simplified (e.g., higher correlations among the impressions of warmth, dominance, attractiveness, happiness, emotional stability, and so on) and are more highly tied to overall positivity-negativity than male faces (Oh, Dotsch, Porter, & Todorov, J Exp Psychol: Gen 2019). Further, raters who are more willing to endorse gender stereotypes (e.g., men are competitive, women are emotional), they show more simplified impressions of both men and women.
Perceivers’ expectations about gender (e.g., gender stereotypes) affect social judgments of faces of different genders. Dimensionality reduction and data-driven face models found that human raters’ impressions of female faces are more simplified (e.g., higher correlations among the impressions of warmth, dominance, attractiveness, happiness, emotional stability, and so on) and are more highly tied to overall positivity-negativity than male faces (Oh, Dotsch, Porter, & Todorov, J Exp Psychol: Gen 2019). Further, raters who are more willing to endorse gender stereotypes (e.g., men are competitive, women are emotional), they show more simplified impressions of both men and women.
People have more simplified and valence-laden impressions of women than of men.
Left: y = the level of correlations among impressions; each dot = the level of correlations between a pair of impression ratings).
Right: PC1 = the component representing the dependency of impressions on overall positivity-negativity in male and female impressions; PC2 = the component explaining the second largest amount of variance in male and female impressions.
Left: y = the level of correlations among impressions; each dot = the level of correlations between a pair of impression ratings).
Right: PC1 = the component representing the dependency of impressions on overall positivity-negativity in male and female impressions; PC2 = the component explaining the second largest amount of variance in male and female impressions.
Masculine facial characteristics are at the basis of people’s face-based judgments of competence. (Oh, Buck, & Todorov, Psych Sci 2018). It was revealed via data-driven models describing facial characteristics that elicit competence impressions (in the absence of attractiveness – which covaries with competence impressions under normal circumstances).
This line of research informs us about the importance of how people’s preconceptions manifests in how we form first impressions based on faces.
This line of research informs us about the importance of how people’s preconceptions manifests in how we form first impressions based on faces.
References
Oh D, Dotsch R, Porter JM, Todorov A (2019) Gender biases in impressions from faces: Empirical studies and computational models. Journal of Experimental Psychology: General.
Oh D, Buck EA, Todorov A (2018) Revealing hidden gender biases in competence impressions from faces. Psychological Science, 30, 65-79.
Oh D, Dotsch R, Porter JM, Todorov A (2019) Gender biases in impressions from faces: Empirical studies and computational models. Journal of Experimental Psychology: General.