基于社会群体的身份相交。“女人”的含义是通过增加“富婆”或“穷婆”中的社会阶层来调节的。\“这种交叉性如何在日常语言中大规模运作?哪个交叉性占主导地位(最常见)?什么品质(积极性,能力,温暖)归因于每个十字路口?在这项研究中,我们有可能通过制定一个逐步的程序来解决这些问题,灵活的交叉刻板印象提取(FISE),应用于对数十亿个英语互联网文本单词进行培训的单词嵌入(GloVe;BERT),揭示对交叉刻板印象的见解。首先,将FISE应用于跨性别交叉点的职业刻板印象,种族,班级显示与职业人口统计数据的真实数据一致,提供初始验证。第二,将FISE应用于特质形容词在主导日常英语语言方面表现出强烈的男性中心主义(男性)和种族中心主义(白人)(例如白人男性与59%的特质相关;黑人女性与5%)。相关性状也揭示了交叉差异:优势交叉组,尤其是涉及Rich的交叉路口,有更常见的,积极的,温暖,主管,和显性特征联想。一起,FISE的经验见解说明了其在透明和有效地量化现有大型文本语料库中的交叉刻板印象方面的效用,具有在前所未有的时间和地点扩展交叉性研究的潜力。该项目进一步建立了必要的基础设施,以对交叉身份的新兴特性进行新的研究。
Social group-based identities intersect. The meaning of \"woman\" is modulated by adding social class as in \"rich woman\" or \"poor woman.\" How does such intersectionality operate at-scale in everyday language? Which intersections dominate (are most frequent)? What qualities (positivity, competence, warmth) are ascribed to each intersection? In this study, we make it possible to address such questions by developing a stepwise procedure, Flexible Intersectional Stereotype Extraction (FISE), applied to word embeddings (GloVe; BERT) trained on billions of words of English Internet text, revealing insights into intersectional stereotypes. First, applying FISE to occupation stereotypes across intersections of gender, race, and class showed alignment with ground-truth data on occupation demographics, providing initial validation. Second, applying FISE to trait adjectives showed strong androcentrism (Men) and ethnocentrism (White) in dominating everyday English language (e.g. White + Men are associated with 59% of traits; Black + Women with 5%). Associated traits also revealed intersectional differences: advantaged intersectional groups, especially intersections involving Rich, had more common, positive, warm, competent, and dominant trait associates. Together, the empirical insights from FISE illustrate its utility for transparently and efficiently quantifying intersectional stereotypes in existing large text corpora, with potential to expand intersectionality research across unprecedented time and place. This project further sets up the infrastructure necessary to pursue new research on the emergent properties of intersectional identities.