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Language provides an ever-present context for our cognitions and has the ability to shape them. Languages across the world can be gendered (language in which the form of noun, verb, or pronoun is presented as female or male) versus genderless. In an ongoing debate, one stream of research suggests that gendered languages are more likely to display gender prejudice than genderless languages. However, another stream of research suggests that language does not have the ability to shape gender prejudice. In this research, we contribute to the debate by using a Natural Language Processing (NLP) method which captures the meaning of a word from the context in which it occurs. Using text data from Wikipedia and the Common Crawl project (that contains text from billions of publicly facing websites) across 45 world languages, covering the majority of the world’s population, we test for gender prejudice in gendered and genderless languages. We find that gender prejudice occurs more in gendered rather than genderless languages. Moreover, we examine whether genderedness of language influences the stereotypic dimensions of warmth and competence utilizing the same NLP method.

Language is the ever-present context of our cognitions and provides an insight into our cognition (i.e., thoughts, attitudes, and beliefs; Carnaghi & Maass, 2007; Collins & Clément, 2012). It is considered both a vessel for holding cognitions as well as a lens that can direct (or distort) those cognitions (Sutton, 2010). Differences in how concepts and objects are defined across languages, therefore, leads to differences in how they are perceived by respective speakers (Casasanto, 2008). One dimension where languages differ is gender. World languages can be categorized as gendered (a language in which the form of noun, verb, or pronoun is presented as female or male) versus genderless languages. This raises the...