Evidence that gendered wording in job advertisements exists and sustains gender inequality.

By Danielle Gaucher, Justin P Friesen, Aaron C. Kay. Journal of Personality and Social Psychology, 2011

606 citations recorded by the source corpus.

Subfields: Gender Studies, Sociology and Political Science

View Paper: https://www.semanticscholar.org/paper/5aa3da510315c53778d79ca94af039b4b1ac21bf

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Gender Studies

In Sociology and Political Science

Citations in the corpus

Gender stereotypes and workplace bias (2012, background): “Efforts to broaden conceptions of what it takes to do these jobs – much of which concerns stereotypically female people skills – have been shown to alleviate some negative consequences (Gaucher et al., 2011).”
Messages about brilliance undermine women's interest in educational and professional opportunities (2018, neutral): “In addition, per- haps both the malleable- and the xed-brilliance advertisements evokedfi a masculine work environment (e.g., Gaucher et al., 2011; Mundy, 2017).”
Can Gender-Fair Language Reduce Gender Stereotyping and Discrimination? (2016, background): “In another study, adult speakers as well envisaged more men in an occupation when job advertisements includedmore masculine than feminine forms (Gaucher et al., 2011).”
Reducing women’s lack of fit with leadership positions? Effects of the wording of job advertisements (2015, background): “, 2012), and considering that women’s perceived lack of fit with a position is more pronounced the more male-typed the position is deemed to be (Bem & Bem, 1973; Gaucher et al., 2011; Heilman, 2012), we conclude that word pairs counteracted the “maleness” of the high-status position.”
Combatting gender discrimination: A lack of fit framework (2018, background): “affects both women’s willingness to apply (Gaucher et al., 2011) and their likelihood of being selected (Horvath & Sczesny, 2015) for positions depicted as highly male gender-typed.”
Multi-Dimensional Gender Bias Classification (2020, result): “For example, adjectives which describe women have been shown to differ from those used to describe men in numerous situations (Trix and Psenka, 2003; Gaucher et al., 2011; Moon, 2014; Hoyle et al., 2019), as do verbs that take nouns referring to men”
Gender Stereotypes in Natural Language: Word Embeddings Show Robust Consistency Across Child and Adult Language Corpora of More Than 65 Million Words (2021, positive): “When consistently expressed in spoken and written language, such perceptions can become collective “truths” that shape how children and adults think about and interact with the social world (e.g., Gaucher, Friesen, & Kay, 2011; Rhodes, Leslie, Yee, & Saunders, 2019).”
Adhering, Steering, and Queering: Treatment of Gender in Natural Language Generation (2020, background): “This is already a common strategy when seeking to hire more women in male-dominated disciplines or professions (where job descriptions commonly employ male-biased language [25]).”
Raising Doubt in Letters of Recommendation for Academia: Gender Differences and Their Impact (2018, background): “…are tools that screen candidates in the selection process (Guion, 1998; Morgan, Elder, & King, 2013) because they verify information provided by applicants and offer information about applicants’ past performance (Aamodt, Nagy, & Thompson, 1998; Gatewood & Feild, 2001; McCarthy & Goffin, 2001).”