Are Female Carpenters like Blue Bananas? A Corpus Investigation of Occupation Gender Typicality

Da Ju, Karen Ullrich, Adina Williams


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:
Bibkey:
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)
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PDF:
https://aclanthology.org/2024.findings-acl.253.pdf