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  4. Quality of evidence revealing subtle gender biases in science is in the eye of the beholder
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Quality of evidence revealing subtle gender biases in science is in the eye of the beholder

Publication type
journal article
Publication date
2015
Author(s)
Handley, Ian M.
Brown, Elizabeth R.
Moss-Racusin, Corinne A.
Smith, Jessi L.
Language
English
Keywords

Sexism

Gender bias

Diversity

Science education

Science workforce

Discipline(s)

Engineering

Mathematics

STEM

Abstract
Scientists are trained to evaluate and interpret evidence without bias or subjectivity. Thus, growing evidence revealing a gender bias against women—or favoring men—within science, technology, engineering, and mathematics (STEM) settings is provocative and raises questions about the extent to which gender bias may contribute to women’s underrepresentation within STEM fields. To the extent that research illustrating gender bias in STEM is viewed as convincing, the culture of science can begin to address the bias. However, are men and women equally receptive to this type of experimental evidence? This question was tested with three randomized, double-blind experiments—two involving samples from the general public (n = 205 and 303, respectively) and one involving a sample of university STEM and non-STEM faculty (n = 205). In all experiments, participants read an actual journal abstract reporting gender bias in a STEM context (or an altered abstract reporting no gender bias in experiment 3) and evaluated the overall quality of the research. Results across experiments showed that men evaluate the gender-bias research less favorably than women, and, of concern, this gender difference was especially prominent among STEM faculty (experiment 2). These results suggest a relative reluctance among men, especially faculty men within STEM, to accept evidence of gender biases in STEM. This finding is problematic because broadening the participation of underrepresented people in STEM, including women, necessarily requires a widespread willingness (particularly by those in the majority) to acknowledge that bias exists before transformation is possible.
Journal
Proceedings of the National Academy of Sciences
ISSN
1091-6490
DOI
10.1073/pnas.1510649112
Volume
112
Issue
43
Pagination
13201-13206
URL
https://www.pnas.org/doi/full/10.1073/pnas.1510649112
https://libkey.io/libraries/2561/articles/56634837/full-text-file?utm_source=api_2667&allow_speedbump=true
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