2021
DOI: 10.1353/lan.0.0256
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Gender bias in linguistics textbooks: Has anything changed since Macaulay & Brice 1997?

Abstract: Macaulay and Brice (1997:798) surveyed example sentences in eleven syntax textbooks published from 1969-1994 and found that virtually all of the authors 'favor male-gendered NPs as subjects and agents, and regularly stereotype both genders'. In this article, we address the question of whether constructed example sentences in more recent textbooks show similar gender bias. We present an analysis of six syntax textbooks published from 2005-2017, from which we randomly sampled 200 example sentences each. We find… Show more

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Cited by 5 publications
(9 citation statements)
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“…Little has improved in the decades since Macaulay & Brice's 1997survey. Pabst et al (2018 -findings later published in Cépeda et al (2021) -found that textbooks published between 2005 and 2017 continued the same trends of privileging male arguments and promoting gender stereotypes. In the six textbooks surveyed, male arguments were almost twice as frequent as female ones and were much more likely to appear as subjects, agents, and experiencers.…”
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confidence: 95%
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“…Little has improved in the decades since Macaulay & Brice's 1997survey. Pabst et al (2018 -findings later published in Cépeda et al (2021) -found that textbooks published between 2005 and 2017 continued the same trends of privileging male arguments and promoting gender stereotypes. In the six textbooks surveyed, male arguments were almost twice as frequent as female ones and were much more likely to appear as subjects, agents, and experiencers.…”
mentioning
confidence: 95%
“…
It has been well established that example sentences in linguistics use a remarkably non-diverse set of proper names in terms of gender, culture, and ethnicity (e.g., Macaulay & Brice 1997, Cépeda et al 2021). Here, we introduce a new resource, the Diverse Names Generator (DNG), which provides randomly selected proper names with IPA transcriptions from a user-contributed, linguist-curated database of names from a wide range of languages and cultures.
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confidence: 99%
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