Abstract
People tend to use language to mention surprising properties of events: for example, when a banana is blue, we are more likely to mention color than when it is yellow. This fact is taken to suggest that yellowness is somehow a typical feature of bananas, and blueness is exceptional. Similar to how a yellow color is typical of bananas, there may also be genders that are typical of occupations. In this work, we explore this question using information theoretic techniques coupled with corpus statistic analysis. In two distinct large corpora, we do not find strong evidence that occupations and gender display the same patterns of mentioning as do bananas and color. Instead, we find that gender mentioning is correlated with femaleness of occupation in particular, suggesting perhaps that woman-dominated occupations are seen as somehow “more gendered” than male-dominated ones, and thereby they encourage more gender mentioning overall.- Anthology ID:
- 2024.findings-acl.253
- Volume:
- Findings of the Association for Computational Linguistics ACL 2024
- Month:
- August
- Year:
- 2024
- Address:
- Bangkok, Thailand and virtual meeting
- Editors:
- Lun-Wei Ku, Andre Martins, Vivek Srikumar
- Venue:
- Findings
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 4254–4274
- Language:
- URL:
- https://aclanthology.org/2024.findings-acl.253
- DOI:
- Cite (ACL):
- Da Ju, Karen Ullrich, and Adina Williams. 2024. Are Female Carpenters like Blue Bananas? A Corpus Investigation of Occupation Gender Typicality. In Findings of the Association for Computational Linguistics ACL 2024, pages 4254–4274, Bangkok, Thailand and virtual meeting. Association for Computational Linguistics.
- Cite (Informal):
- Are Female Carpenters like Blue Bananas? A Corpus Investigation of Occupation Gender Typicality (Ju et al., Findings 2024)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-4/2024.findings-acl.253.pdf