4.5 Article

People Attribute Humanness to Men and Women Differently Based on Their Facial Appearance

出版社

AMER PSYCHOLOGICAL ASSOC
DOI: 10.1037/pspi0000364

关键词

attractiveness; dehumanization; face; gender; intelligence

向作者/读者索取更多资源

The research findings suggest that individuals who appear less attractive and less intelligent are often perceived as less human, with differences in attribution based on gender. These differences seem to be rooted in gender stereotypes and result in biases in moral treatment towards more attractive women and intelligent-looking men. This sheds light on how interpersonal judgments interact with intergroup biases to promote gender-based discrimination.
Recognizing others' humanity is fundamental to how people think about and treat each other. People often ascribe greater humanness to groups that they socially value, but do they also systematically ascribe social value to different individuals? Here, we tested whether people (de)humanize individuals based on social traits inferred from their facial appearance, focusing on attractiveness and intelligence. Across five studies, less attractive and less intelligent-looking individuals seemed less human, but this varied by target gender: Attractiveness better predicted humanness attributions to women whereas perceived intelligence better predicted humanness attributions to men (Study 1). This difference seems to stem from gender stereotypes (preregistered Studies 2 and 3) and even extends to attributions of children's humanness (preregistered Study 4). Moreover, this gender difference leads to biases in moral treatment that confer more value to the lives of attractive women and intelligent-looking men (preregistered Study 5). These data help to explain how interpersonal judgments of individuals interact with intergroup biases to promote gender-based discrimination, providing greater nuance to the mechanisms and outcomes of dehumanization.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.5
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据