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      Gender disparities in high-quality research revealed by Nature Index journals

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          Abstract

          Background

          The present study aims to elucidate the state of gender equality in high-quality research by analyzing the representation of female authorships in the last decade (from 2008 to 2016).

          Methods

          Based on the Gendermetrics platform, 293,557 research articles from 54 journals listed in the Nature Index were considered covering the categories Life Science, Multidisciplinary, Earth & Environmental and Chemistry. The core method was the combined analysis of the proportion of female authorships and the female-to-male odds ratio for first, co- and last authorships. The distribution of prestigious authorships was measured by the Prestige Index.

          Results

          29.8% of all authorships and 33.1% of the first, 31.8% of the co- and 18.1% of the last authorships were held by women. The corresponding female-to-male odds ratio is 1.19 (CI: 1.18–1.20) for first, 1.35 (CI: 1.34–1.36) for co- and 0.47 (CI: 0.46–0.48) for last authorships. Women are underrepresented at prestigious authorships compared to men (Prestige Index = -0.42). The underrepresentation accentuates in highly competitive articles attracting the highest citation rates, namely, articles with many authors and articles that were published in highest-impact journals. More specifically, a large negative correlation between the 5-Year-Impact-Factor of a journal and the female representation at prestigious authorships was revealed (r(52) = -.63, P < .001). Women publish fewer articles compared to men (39.0% female authors are responsible for 29.8% of all authorships) and are underrepresented at productivity levels of more than 2 articles per author. Articles with female key authors are less frequently cited than articles with male key authors. The gender-specific differences in citation rates increase the more authors contribute to an article. Distinct differences at the journal, journal category, continent and country level were revealed. The prognosis for the next decades forecast a very slow harmonization of authorships odds between the two genders.

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          Most cited references54

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          Science faculty's subtle gender biases favor male students.

          Despite efforts to recruit and retain more women, a stark gender disparity persists within academic science. Abundant research has demonstrated gender bias in many demographic groups, but has yet to experimentally investigate whether science faculty exhibit a bias against female students that could contribute to the gender disparity in academic science. In a randomized double-blind study (n = 127), science faculty from research-intensive universities rated the application materials of a student-who was randomly assigned either a male or female name-for a laboratory manager position. Faculty participants rated the male applicant as significantly more competent and hireable than the (identical) female applicant. These participants also selected a higher starting salary and offered more career mentoring to the male applicant. The gender of the faculty participants did not affect responses, such that female and male faculty were equally likely to exhibit bias against the female student. Mediation analyses indicated that the female student was less likely to be hired because she was viewed as less competent. We also assessed faculty participants' preexisting subtle bias against women using a standard instrument and found that preexisting subtle bias against women played a moderating role, such that subtle bias against women was associated with less support for the female student, but was unrelated to reactions to the male student. These results suggest that interventions addressing faculty gender bias might advance the goal of increasing the participation of women in science.
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            Understanding current causes of women's underrepresentation in science

            Explanations for women's underrepresentation in math-intensive fields of science often focus on sex discrimination in grant and manuscript reviewing, interviewing, and hiring. Claims that women scientists suffer discrimination in these arenas rest on a set of studies undergirding policies and programs aimed at remediation. More recent and robust empiricism, however, fails to support assertions of discrimination in these domains. To better understand women's underrepresentation in math-intensive fields and its causes, we reprise claims of discrimination and their evidentiary bases. Based on a review of the past 20 y of data, we suggest that some of these claims are no longer valid and, if uncritically accepted as current causes of women's lack of progress, can delay or prevent understanding of contemporary determinants of women's underrepresentation. We conclude that differential gendered outcomes in the real world result from differences in resources attributable to choices, whether free or constrained, and that such choices could be influenced and better informed through education if resources were so directed. Thus, the ongoing focus on sex discrimination in reviewing, interviewing, and hiring represents costly, misplaced effort: Society is engaged in the present in solving problems of the past, rather than in addressing meaningful limitations deterring women's participation in science, technology, engineering, and mathematics careers today. Addressing today's causes of underrepresentation requires focusing on education and policy changes that will make institutions responsive to differing biological realities of the sexes. Finally, we suggest potential avenues of intervention to increase gender fairness that accord with current, as opposed to historical, findings.
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              Do Women Shy Away From Competition? Do Men Compete Too Much?

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                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: Project administrationRole: SoftwareRole: SupervisionRole: ValidationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: SupervisionRole: Validation
                Role: SupervisionRole: Validation
                Role: ConceptualizationRole: Project administrationRole: ResourcesRole: SupervisionRole: Validation
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                2 January 2018
                2018
                : 13
                : 1
                : e0189136
                Affiliations
                [001]Division of Computational Medicine, Institute of Occupational, Social, and Environmental Medicine, Goethe University Frankfurt, Theodor-Stern-Kai 7, Frankfurt, Germany
                Institut Català de Paleoecologia Humana i Evolució Social (IPHES), SPAIN
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Author information
                http://orcid.org/0000-0002-4931-6466
                Article
                PONE-D-17-05970
                10.1371/journal.pone.0189136
                5749692
                29293499
                127074f3-51db-4d1d-a337-b2aaf710aaf2
                © 2018 Bendels et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 14 February 2017
                : 20 November 2017
                Page count
                Figures: 6, Tables: 6, Pages: 21
                Funding
                The authors received no specific funding for this work.
                Categories
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                Citation Analysis
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                The underlying data is public and was retrieved from the Web of Science Core Collection.

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