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

arXiv: https://arxiv.org/abs/2408.02948 · HTML: https://mlsanity.com/paper/2408.02948/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- Builds on 22 of its 46 references that are in the map.
- First posted on arXiv 6 Aug 2024.

## Builds on (most cited first, 22 of 22)

- [Llama 2: Open Foundation and Fine-Tuned Chat Models](https://mlsanity.com/paper/2307.09288/) (2023)
- [Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings](https://mlsanity.com/paper/1607.06520/) (2016)
- [Semantics derived automatically from language corpora contain human-like biases](https://mlsanity.com/paper/1608.07187/) (2016)
- [Stanza: A Python Natural Language Processing Toolkit for Many Human Languages](https://mlsanity.com/paper/2003.07082/) (2020)
- [Gender Bias in Coreference Resolution: Evaluation and Debiasing Methods](https://mlsanity.com/paper/1804.06876/) (2018)
- [Recipes for building an open-domain chatbot](https://mlsanity.com/paper/2004.13637/) (2020)
- [Gender Bias in Coreference Resolution](https://mlsanity.com/paper/1804.09301/) (2018)
- [The Pushshift Reddit Dataset](https://mlsanity.com/paper/2001.08435/) (2020)
- [Evaluating Gender Bias in Machine Translation](https://mlsanity.com/paper/1906.00591/) (2019)
- [Assessing Gender Bias in Machine Translation -- A Case Study with Google Translate](https://mlsanity.com/paper/1809.02208/) (2018)
- [Unmasking Contextual Stereotypes: Measuring and Mitigating BERT's Gender Bias](https://mlsanity.com/paper/2010.14534/) (2020)
- [It's a Man's Wikipedia? Assessing Gender Inequality in an Online Encyclopedia](https://mlsanity.com/paper/1501.06307/) (2015)
- [When redundancy is useful: A Bayesian approach to 'overinformative' referring expressions](https://mlsanity.com/paper/1903.08237/) (2019)
- [Unsupervised Discovery of Gendered Language through Latent-Variable Modeling](https://mlsanity.com/paper/1906.04760/) (2019)
- [Good Secretaries, Bad Truck Drivers? Occupational Gender Stereotypes in Sentiment Analysis](https://mlsanity.com/paper/1906.10256/) (2019)
- [Type B Reflexivization as an Unambiguous Testbed for Multilingual Multi-Task Gender Bias](https://mlsanity.com/paper/2009.11982/) (2020)
- [Extending Challenge Sets to Uncover Gender Bias in Machine Translation: Impact of Stereotypical Verbs and Adjectives](https://mlsanity.com/paper/2107.11584/) (2021)
- [On the Relationships Between the Grammatical Genders of Inanimate Nouns and Their Co-Occurring Adjectives and Verbs](https://mlsanity.com/paper/2005.01204/) (2020)
- [Quantifying the Semantic Core of Gender Systems](https://mlsanity.com/paper/1910.13497/) (2019)
- [Predicting Declension Class from Form and Meaning](https://mlsanity.com/paper/2005.00626/) (2020)
- [The Causal Influence of Grammatical Gender on Distributional Semantics](https://mlsanity.com/paper/2311.18567/) (2023)
- [On the Idiosyncrasies of the Mandarin Chinese Classifier System](https://mlsanity.com/paper/1902.10193/) (2019)

## Built on by (most cited first, 3 of 3)

- [Domain Regeneration: How well do LLMs match syntactic properties of text domains?](https://mlsanity.com/paper/2505.07784/) (2025)
- [On the Mutual Influence of Gender and Occupation in LLM Representations](https://mlsanity.com/paper/2503.06792/) (2025)
- [Investigating Intersectional Bias in Large Language Models using Confidence Disparities in Coreference Resolution](https://mlsanity.com/paper/2508.07111/) (2025)

## Abstract (arXiv)

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.