Gender stereotypes have endured despite substantial change in gender roles. Previous work has assessed how gender stereotypes affect language production in particular interactional contexts. Here, we assessed communication biases where context was less specified: written texts to diffuse audiences. We used Latent Semantic Analysis (LSA) to computationally quantify the similarity in meaning between gendered names and stereotype-linked terms in these communications. This revealed that female names were more similar in meaning to the proscriptive (undesirable) masculine terms, such as emotional.

中文翻译：

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语言使用中嵌入的性别刻板印象的内容

尽管性别角色发生了重大变化，但性别陈规定型观念仍然存在。以前的工作评估了性别刻板印象如何影响特定交互环境中的语言生成。在这里，我们评估了上下文不太明确的交流偏见：分散受众的书面文本。我们使用潜在语义分析 (LSA) 来计算量化这些通信中性别名称和刻板印象相关术语之间含义的相似性。这表明女性名字在含义上与禁止性（不受欢迎的）男性化术语更相似，例如情绪化。