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Visualizing Gendered Representations of Male and Female Teachers Using a Reverse Correlation Paradigm
Stereotypically, men are expected to outperform women in science, technology, engineering, and mathematics (STEM) domains, and women to outperform men in language. We conceptually replicated this association using reverse correlation tasks. Without available gender information, participants generate...
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Published in: | Social psychology (Göttingen, Germany) Germany), 2019-07, Vol.50 (4), p.233-251 |
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Main Authors: | , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | Stereotypically, men are expected to outperform women in
science, technology, engineering, and mathematics (STEM) domains, and women to
outperform men in language. We conceptually replicated this association using
reverse correlation tasks. Without available gender information, participants
generated male images of physics teachers and female images of language teachers
(Studies 1 and 3). Personal endorsement of respective ability stereotypes
inconsistently predicted these effects (Studies 1 and 3). With unambiguous
gender information (Study 2), participants generated feminized images of female
language teachers and masculinized images of female physics teachers, whereas
images of male teachers were unaffected by academic domain. Stereotype
endorsement affected perceptions of female but not male teachers, suggesting
that appearing feminine in STEM domains still signals professional mismatch. |
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ISSN: | 1864-9335 2151-2590 |
DOI: | 10.1027/1864-9335/a000382 |