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      Historical comparison of gender inequality in scientific careers across countries and disciplines

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          Significance

          Empirical evidence suggests significant gender differences in the total productivity and impact of academic careers across science, technology, engineering, and mathematics (STEM) fields. Paradoxically, the increase in the number of women academics over the past 60 years has increased these gender differences. Yet, we find that men and women publish a comparable number of papers per year and have equivalent career-wise impact for the same total number of publications. This suggests the productivity and impact of gender differences are explained by different publishing career lengths and dropout rates. This comprehensive picture of gender inequality in academic publishing can help rephrase the conversation around the sustainability of women’s careers in academia, with important consequences for institutions and policy makers.

          Abstract

          There is extensive, yet fragmented, evidence of gender differences in academia suggesting that women are underrepresented in most scientific disciplines and publish fewer articles throughout a career, and their work acquires fewer citations. Here, we offer a comprehensive picture of longitudinal gender differences in performance through a bibliometric analysis of academic publishing careers by reconstructing the complete publication history of over 1.5 million gender-identified authors whose publishing career ended between 1955 and 2010, covering 83 countries and 13 disciplines. We find that, paradoxically, the increase of participation of women in science over the past 60 years was accompanied by an increase of gender differences in both productivity and impact. Most surprisingly, though, we uncover two gender invariants, finding that men and women publish at a comparable annual rate and have equivalent career-wise impact for the same size body of work. Finally, we demonstrate that differences in publishing career lengths and dropout rates explain a large portion of the reported career-wise differences in productivity and impact, although productivity differences still remain. This comprehensive picture of gender inequality in academia can help rephrase the conversation around the sustainability of women’s careers in academia, with important consequences for institutions and policy makers.

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          Most cited references48

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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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            The Gender Citation Gap in International Relations

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              Quantifying the evolution of individual scientific impact.

              Despite the frequent use of numerous quantitative indicators to gauge the professional impact of a scientist, little is known about how scientific impact emerges and evolves in time. Here, we quantify the changes in impact and productivity throughout a career in science, finding that impact, as measured by influential publications, is distributed randomly within a scientist's sequence of publications. This random-impact rule allows us to formulate a stochastic model that uncouples the effects of productivity, individual ability, and luck and unveils the existence of universal patterns governing the emergence of scientific success. The model assigns a unique individual parameter Q to each scientist, which is stable during a career, and it accurately predicts the evolution of a scientist's impact, from the h-index to cumulative citations, and independent recognitions, such as prizes.
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                Author and article information

                Journal
                Proc Natl Acad Sci U S A
                Proc. Natl. Acad. Sci. U.S.A
                pnas
                pnas
                PNAS
                Proceedings of the National Academy of Sciences of the United States of America
                National Academy of Sciences
                0027-8424
                1091-6490
                3 March 2020
                18 February 2020
                18 February 2020
                : 117
                : 9
                : 4609-4616
                Affiliations
                [1] aNetwork Science Institute and Department of Physics, Northeastern University , Boston, MA 02115;
                [2] bCompleX Lab, School of Computer Science and Engineering, University of Electronic Science and Technology of China , Chengdu 611731, China;
                [3] cPaul and Marcia Wythes Center on Contemporary China, Princeton University , Princeton, NJ 08540;
                [4] dDepartment of Computer Science, IT University of Copenhagen , 2300 Copenhagen, Denmark;
                [5] eISI Foundation , 10126 Turin, Italy;
                [6] fChanning Division of Network Medicine, Brigham and Women’s Hospital, Harvard Medical School , Boston, MA 02115;
                [7] gDepartment of Medicine, Brigham and Women’s Hospital, Harvard Medical School , Boston, MA 02115;
                [8] hDepartment of Network and Data Science, Central European University , 1051 Budapest, Hungary
                Author notes
                2To whom correspondence may be addressed. Email: A.Barabasi@ 123456northeastern.edu .

                Edited by Susan T. Fiske, Princeton University, Princeton, NJ, and approved January 22, 2020 (received for review August 15, 2019)

                Author contributions: J.H., A.J.G., R.S., and A.-L.B. designed research; J.H. and A.J.G. performed research; J.H. and A.J.G. analyzed data; and J.H., A.J.G., R.S., and A.-L.B. wrote the paper.

                1J.H. and A.J.G. contributed equally to this work.

                Author information
                http://orcid.org/0000-0002-7558-1028
                http://orcid.org/0000-0002-4028-3522
                Article
                201914221
                10.1073/pnas.1914221117
                7060730
                32071248
                cbf5b081-9345-4683-ad53-bbaa0cf90769
                Copyright © 2020 the Author(s). Published by PNAS.

                This open access article is distributed under Creative Commons Attribution License 4.0 (CC BY).

                History
                Page count
                Pages: 000
                Funding
                Funded by: John Templeton Foundation (JTF) 100000925
                Award ID: 61066
                Award Recipient : Alexander J Gates Award Recipient : Albert-László Barabási
                Funded by: DOD | USAF | AFMC | Air Force Office of Scientific Research (AFOSR) 100000181
                Award ID: FA9550-19-1-0354
                Award Recipient : Alexander J Gates Award Recipient : Roberta Sinatra Award Recipient : Albert-László Barabási
                Funded by: DOD | Defense Advanced Research Projects Agency (DARPA) 100000185
                Award ID: DARPA- 428 BAA-15-39
                Award Recipient : Junming Huang Award Recipient : Albert-László Barabási
                Funded by: DOD | USAF | AFMC | Air Force Office of Scientific Research (AFOSR) 100000181
                Award ID: FA9550-15-1-0077
                Award Recipient : Alexander J Gates Award Recipient : Roberta Sinatra Award Recipient : Albert-László Barabási
                Funded by: DOD | USAF | AFMC | Air Force Office of Scientific Research (AFOSR) 100000181
                Award ID: FA9550-15-1-0364
                Award Recipient : Alexander J Gates Award Recipient : Roberta Sinatra Award Recipient : Albert-László Barabási
                Categories
                Social Sciences
                Social Sciences
                From the Cover

                gender inequality,science of science,stem,scientific careers

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