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Publication . Article . Preprint . 2019

Gender and collaboration patterns in a temporal scientific authorship network

Gecia Bravo-Hermsdorff; Valkyrie Felso; Ray Emily A; Lee Gunderson; Mary E. Helander; Joana Maria; Yael Niv;
Open Access
One can point to a variety of historical milestones for gender equality in STEM (science, technology, engineering, and mathematics), however, practical effects are incremental and ongoing. It is important to quantify gender differences in subdomains of scientific work in order to detect potential biases and monitor progress. In this work, we study the relevance of gender in scientific collaboration patterns in the Institute for Operations Research and the Management Sciences (INFORMS), a professional society with sixteen peer-reviewed journals. Using their publication data from 1952 to 2016, we constructed a large temporal bipartite network between authors and publications, and augmented the author nodes with gender labels. We characterized differences in several basic statistics of this network over time, highlighting how they have changed with respect to relevant historical events. We find a steady increase in participation by women (e.g., fraction of authorships by women and of new women authors) starting around 1980. However, women still comprise less than 25% of the INFORMS society and an even smaller fraction of authors with many publications. Moreover, we describe a methodology for quantifying the structural role of an authorship with respect to the overall connectivity of the network, using it to measure subtle differences between authorships by women and by men. Specifically, as measures of structural importance of an authorship, we use effective resistance and contraction importance, two measures related to diffusion throughout a network. As a null model, we propose a degree-preserving temporal and geometric network model with emergent communities. Our results suggest the presence of systematic differences between the collaboration patterns of men and women that cannot be explained by only local statistics.
Published in Applied Network Science, November 2019
Subjects by Vocabulary

Library of Congress Subject Headings: lcsh:Applied mathematics. Quantitative methods lcsh:T57-57.97

Microsoft Academic Graph classification: Data science Professional association Publication data Gender equality History Local statistics Null model


Physics - Physics and Society, Computer Science - Social and Information Networks, Authorship network, Collaboration patterns, Temporal network, Gender in STEM, Physics and Society (physics.soc-ph), Social and Information Networks (cs.SI), FOS: Physical sciences, FOS: Computer and information sciences, Computational Mathematics, Computer Networks and Communications, Multidisciplinary

62 references, page 1 of 7

1. Raymond, J.: Most of us are biased. Nature 495(7439), 33{34 (2013). doi:10.1038/495033a

2. Schrou , J., Pischedda, D., Genon, S., Fryns, G., Pinho, A.L., Vassena, E., Liuzzi, A.G., Ferreira, F.S.: Gender bias in (neuro) science: facts, consequences and solutions. European Journal of Neuroscience (2019) [OpenAIRE]

3. Moss-Racusin, C.A., Dovidio, J.F., Brescoll, V.L., Graham, M.J., Handelsman, J.: Science faculty's subtle gender biases favor male students. Proceedings of the National Academy of Sciences 109(41), 16474{16479 (2012). doi:10.1073/pnas.1211286109. [OpenAIRE]

4. Witteman, H.O., Hendricks, M., Straus, S., Tannenbaum, C.: Are gender gaps due to evaluations of the applicant or the science? A natural experiment at a national funding agency. The Lancet 393(10171), 531{540 (2019). doi:10.1016/S0140-6736(18)32611-4

5. Helmer, M., Schottdorf, M., Neef, A., Battaglia, D.: Gender bias in scholarly peer review. eLife 6 (2017). doi:10.7554/elife.21718

6. Nittrouer, C.L., Hebl, M.R., Ashburn-Nardo, L., Trump-Steele, R.C.E., Lane, D.M., Valian, V.: Gender disparities in colloquium speakers at top universities. Proceedings of the National Academy of Sciences 115(1), 104{108 (2017). doi:10.1073/pnas.1708414115

7. Araujo, E.B., Araujo, N.A.M., Moreira, A.A., Herrmann, H.J., Andrade, J.S.: Gender di erences in scienti c collaborations: Women are more egalitarian than men. PLOS ONE 12(5), 0176791 (2017). doi:10.1371/journal.pone.0176791

8. Karimi, F., Mayr, P., Momeni, F.: Analyzing the network structure and gender di erences among the members of the Networked Knowledge Organization Systems (NKOS) community. International Journal on Digital Libraries (2018). doi:10.1007/s00799-018-0243-0

9. Jadidi, M., Karimi, F., Lietz, H., Wagner, C.: Gender disparities in science? dropout, productivity, collaborations and success of male and female computer scientists. Advances in Complex Systems 21(03n04), 1750011 (2018)

10. West, J.D., Jacquet, J., King, M.M., Correll, S.J., Bergstrom, C.T.: The role of gender in scholarly authorship. PLoS ONE 8(7), 66212 (2013). doi:10.1371/journal.pone.0066212

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  • Funder: Canadian Institutes of Health Research (CIHR)
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