心理学
男子气概
女性气质
社会心理学
种族(生物学)
性别图式理论
模式(遗传算法)
可信赖性
原型(UML)
性别研究
社会学
机器学习
计算机科学
精神分析
作者
Hanyong Bao,Peter Hays Gries
摘要
Abstract How are Asian and Black men and women stereotyped? Research from the gendered race and stereotype content perspectives has produced mixed empirical findings. Using BERT models pre‐trained on English language books, news articles, Wikipedia, Reddit and Twitter, with a new method for measuring propositions in natural language (the Fill‐Mask Association Test, FMAT), we explored the gender (masculinity–femininity), physical strength, warmth and competence contents of stereotypes about Asian and Black men and women. We find that Asian men (but not women) are stereotyped as less masculine and less moral/trustworthy than Black men. Compared to Black men and Black women, respectively, both Asian men and Asian women are stereotyped as less muscular/athletic and less assertive/dominant, but more sociable/friendly and more capable/intelligent. These findings suggest that Asian and Black stereotypes in natural language have multifaceted contents and gender nuances, requiring a balanced view integrating the gender schema theory and the stereotype content model. Exploring their semantic representations as propositions in large language models, this research reveals how intersectional race–gender stereotypes are naturally expressed in real life.
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