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Ambient belonging: how stereotypical cues impact gender participation in computer science
Abstract
People can make decisions to join a group based solely on exposure to that group's physical environment. Four studies demonstrate that the gender difference in interest in computer science is influenced by exposure to environments associated with computer scientists. In Study 1, simply changing the objects in a computer science classroom from those considered stereotypical of computer science (e.g., Star Trek poster, video games) to objects not considered stereotypical of computer science (e.g., nature poster, phone books) was sufficient to boost female undergraduates' interest in computer science to the level of their male peers. Further investigation revealed that the stereotypical broadcast a masculine stereotype that discouraged women's sense of ambient belonging and subsequent interest in the environment (Studies 2, 3, and 4) but had no similar effect on men (Studies 3, 4). This masculine stereotype prevented women's interest from developing even in environments entirely populated by other women (Study 2). Objects can thus come to broadcast stereotypes of a group, which in turn can deter people who do not identify with these stereotypes from joining that group.
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“One study, for instance, found that the presence of cues aligned with the stereotype of male computer scientists-geeky posters and video games-in a computer science classroom had a negative effect on women's performance (Cheryan, Plaut, Davies, & Steele, 2009).”
From Tackling Educational Inequalities with Social Psychology: Identities, Contexts, and Interventions (2021) · cites this paper as Cheryan, Plaut, Davies, & Steele, 2009
In the citing paper
“Stereotype threat can also undermine women's sense of belonging in a field and their motivation and desire to pursue success within the field (Cheryan, Plaut, Davies, & Steele, 2009).”
From Managing to clear the air: Stereotype threat, women, and leadership (2016) · cites this paper as Cheryan, Plaut, Davies, & Steele, 2009
In the citing paper
“For example, women who were exposed to stereotypically masculine items in their environment, including a Star Trek poster and video games, reported less interest in pursuing computer science than those not exposed to the gendered environment (Cheryan, Plaut, Davies, & Steele, 2009).”
From Managing to clear the air: Stereotype threat, women, and leadership (2016) · cites this paper as Cheryan, Plaut, Davies, & Steele, 2009
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Metadata
- Authors
- Cheryan, S., Plaut, V. C., Davies, P. G., & Steele, C. M.
- Affiliations
- University of Washington (US)
- University of British Columbia (CA)
- Stanford University (US)
- Venue
- Journal of Personality and Social Psychology
- Published
- 2009
- Volume
- 97
- Issue
- 6
- Pages
- 1045-1060
- ISSN
- 0022-3514 (ISSN-L)
- 1939-1315
- OpenAlex
- W2056648275
- Cited by
- 1,372
- References
- 70
- Citations by year
- 2026: 71 · 2025: 105 · 2024: 137 · 2023: 106 · 2022: 98 · 2021: 117 · 2020: 182 · 2019: 131 · 2018: 91 · 2017: 66 · 2016: 56 · 2015: 66 · 2014: 50 · 2013: 41 · 2012: 21
- FWCI
- 47.09
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Personality and Social Psychology (publishedVersion)
- PubMed (publishedVersion)
- Berkley Law Scholarship Repository (University of California, Berkeley) (submittedVersion)
- Topics
- Social Sciences › Psychology › Applied Psychology › Career Development and Diversity
- Social Sciences › Gender Studies › Gender and Technology in Education
- Social Sciences › Psychology › Developmental and Educational Psychology › Science Education and Perceptions
- Keywords
- gender stereotypes, gender gap in computing, stereotype threat, women in technology, gendered objects, female undergraduates
- MeSH terms
- Analysis of Variance, Computers, Cues, Environment, Female, Gender Identity, Georgia, Group Processes, Humans, Male, Social Identification, Social Perception, Stereotyped Behavior, Stereotyping, Students, Organizational Culture, Informatics
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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