Sexist textbooks? Review of over 1200 English-language textbooks from 34 countries reveals persistent pattern of stereotypical gender roles and under-representation of female characters across countri

(Press-News.org) Gender biases around male and female roles and under-representation of female characters appeared in textbooks from around the world, with male-coded words appearing twice as often as female-coded words on average, according to a study published October 9, 2024 in the open-access journal PLOS ONE by Lee Crawfurd from the Center for Global Development, United Kingdom, and colleagues.

School textbooks play an important role in shaping norms and attitudes in students—one reason why controversy over textbook content is high in many countries today. In this study, Crawfurd and colleagues investigated how gender norms are depicted in textbooks around the world.

The authors used a particularly large corpus of textbooks to conduct their analysis: 1,255 publicly available online English-language school textbooks spanning subjects and grade levels from grades 4-13 from 34 countries downloaded over 2020-2022. They compared textbook content with predefined lists of gendered nouns and pronouns (e.g. “Auntie/she/her/woman”) and investigated how often these gendered words were associated with key words used in previous studies relating to achievement, appearance, family, home, and work (e.g. “powerful/gorgeous/household/executive”) within the textbook. Finally, the authors compared their text analysis results with other measures of gender equality at the country level.

They found that on average across the full sample of textbooks, there were more than twice as many occurrences of male words (178,142) as female words (82,113), though there was considerable variation between countries. After adjusting for book length, grade, and subject, the countries with the lowest representation of women and girls were Afghanistan, Pakistan, Sri Lanka, and South Sudan, where fewer than 1 in 3 gendered words were female.

Across all countries, the adjectives most likely to describe only female and not male characters included “married”, “beautiful”, “aged”, and “quiet”. Verbs for only female characters included “bake”, “cook,” and “sang”. The adjectives most likely to describe male and not female characters included “powerful”, “rich”, “wise”, “certain”, and “unable”. Verbs for only male characters included “rule”, “guide”, “sign”, and “order”. Almost all of the individual achievement- and work-themed words showed a stronger association with male words than female words, and the individual appearance- and home-themed words showed a stronger association with female words than male words. The authors note that countries with textbooks containing a greater number of female characters also had stronger GDPs and more legal rights for women compared to countries with less female representation, though this is only correlation and cannot speak to causation.

The authors also note there are several limitations to this work—their tool was not able to assess non-text items (such as images) and was not always correct at parsing names (though the authors used manual validation where possible), and the analysis reflects a binary view of gender illustrated in the textbooks. Furthermore, this analysis is restricted to English language literature and therefore may not be generalizable to languages beyond English. However, the results suggest that combating gender biases in textbooks could potentially lead to real-world effects.

The authors add: “Our findings reveal a troubling reality: school books are perpetuating outdated gender stereotypes. Schools should broaden horizons not limit children's potential. It's crucial for policymakers and educators to address these disparities.”

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Author Interview: https://plos.io/4dybR17

In your coverage please use this URL to provide access to the freely available article in PLOS ONE: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0310366

Citation: Crawfurd L, Saintis-Miller C, Todd R (2024) Sexist textbooks: Automated analysis of gender bias in 1,255 books from 34 countries. PLoS ONE 19(10): e0310366. https://doi.org/10.1371/journal.pone.0310366

Author Countries: U.K., U.S.A.

Funding: This research was supported by funding from the Bill and Melinda Gates Foundation and Echidna Giving. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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