Sexist textbooks: Automated analysis of gender bias in 1,255 books from 34 countries

Abstract

Textbooks play a critical role in schooling around the world. Small sample studies show that many books continue to under-represent women and girls, and to portray men and women in stereotypical gendered roles. In this paper, we use quantitative text analysis to assess the degree of gender bias in a newly assembled corpus of 1,255 English language school textbooks from 34 countries that are publicly available online. We find consistent patterns of under-representation of female characters and portrayal of stereotypical gendered roles. Women and girls appear less frequently, are portrayed as more passive, are less likely to be associated with work or achievement, and are more likely to be associated with the home and traditionally female occupations. Comparing across countries, female representation in books is correlated with higher GDP and more legal rights for women. Under-representation and stereotypes are a particular problem in South Asia.

Cite this work

No public copy is stored for this record, so only the metadata is cited.

Stored only when both papers are in the corpus — 16 citations exist upstream.

Papers that cite the same references — the relational fallback while embeddings are still backfilling.