Quantifying Gender Stereotypes in Japan between 1900 and 1999 with Word Embeddings
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| Format: | Preprint |
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2025
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| _version_ | 1866915533639647232 |
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| author | Sakai, Shintaro Kwak, Haewoon An, Jisun Matsui, Akira |
| author_facet | Sakai, Shintaro Kwak, Haewoon An, Jisun Matsui, Akira |
| contents | We quantify the evolution of gender stereotypes in Japan from 1900 to 1999 using a series of 100 word embeddings, each trained on a corpus from a specific year. We define the gender stereotype value to measure the strength of a word's gender association by computing the difference in cosine similarity of the word to female- versus male-related attribute words. We examine trajectories of gender stereotype across three traditionally gendered domains: Home, Work, and Politics, as well as occupations. The results indicate that language-based gender stereotypes partially evolved to reflect women's increasing participation in the workplace and politics: Work and Politics domains become more strongly female-stereotyped over the years. Yet, Home also became more female-stereotyped, suggesting that women were increasingly viewed as fulfilling multiple roles such as homemakers, workers, and politicians, rather than having one role replace another. Furthermore, the strength of female stereotype for occupations positively correlate with the proportion of women in each occupation, indicating that word-embedding-based measures of gender stereotype mirrored demographic shifts to a considerable extent. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2510_03905 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Quantifying Gender Stereotypes in Japan between 1900 and 1999 with Word Embeddings Sakai, Shintaro Kwak, Haewoon An, Jisun Matsui, Akira Computers and Society We quantify the evolution of gender stereotypes in Japan from 1900 to 1999 using a series of 100 word embeddings, each trained on a corpus from a specific year. We define the gender stereotype value to measure the strength of a word's gender association by computing the difference in cosine similarity of the word to female- versus male-related attribute words. We examine trajectories of gender stereotype across three traditionally gendered domains: Home, Work, and Politics, as well as occupations. The results indicate that language-based gender stereotypes partially evolved to reflect women's increasing participation in the workplace and politics: Work and Politics domains become more strongly female-stereotyped over the years. Yet, Home also became more female-stereotyped, suggesting that women were increasingly viewed as fulfilling multiple roles such as homemakers, workers, and politicians, rather than having one role replace another. Furthermore, the strength of female stereotype for occupations positively correlate with the proportion of women in each occupation, indicating that word-embedding-based measures of gender stereotype mirrored demographic shifts to a considerable extent. |
| title | Quantifying Gender Stereotypes in Japan between 1900 and 1999 with Word Embeddings |
| topic | Computers and Society |
| url | https://arxiv.org/abs/2510.03905 |