Sexist Textbooks ABSTRACT

9 We validate this process manually with a sample of 5 books across a range of subjects (English, Mathematics, Social Studies, Political Science, and Biology) and countries (Afghanistan, Bangladesh, Guyana, India and Pakistan), to calculate both the rate of precision - the proportion of identified ’names’ which are in fact names in context - and recall - the proportion of names in the text which w. [...] In our case, we are interested in the distance between male and female words on the one hand, and words relating to work, family, achievement, and appearance on the other. [...] Male bias is calculated as the difference between the average cosine similarity of the theme word with the set of male gender terms, and the average similarity of the theme word with the set of female gender terms. [...] A 1 standard deviation increase in the gender parity in secondary schooling index, or in the share of female members of parliament, is associated with a 2 percentage point increase in the share of female words in books. [...] All of these correlations are estimated in regressions in which the outcome is the share of gendered words in a specific textbook that are female, estimated as a function of country-level attitudes, outcomes, and laws, whilst controlling for (log) GDP per capita, and characteristics of the textbook itself (its grade, subject, and word length) (Table 4).