Meta-Research: Individual-level researcher data confirm the widening gender gap in publishing rates during COVID-19

  1. Emil Bargmann Madsen
  2. Mathias Wullum Nielsen
  3. Josefine Bjørnholm
  4. Reshma Jagsi
  5. Jens Peter Andersen  Is a corresponding author
  1. Aarhus University, Denmark
  2. University of Copenhagen, Denmark
  3. University of Michigan, United States

Abstract

Publishing is part and parcel of a successful academic career, and Covid-19 has amplified gender disparities in manuscript submissions and authorships. We used longitudinal publication data on 431,207 scientists in biology, chemistry, and clinical and basic medicine to quantify the differential impact of Covid-19 on women's and men's annual publishing rates. In a difference-in-differences analysis, we estimated that the average gender difference in publication productivity increased from -0.26 in 2019 (corresponding to a 17% lower output for women than men) to -0.35 in 2020 (corresponding to a 24% lower output for women than men). An age-group comparison showed a widening gender gap for both early career and mid-career scientists. The increasing gender gap was most pronounced among highly productive authors and scientists in clinical medicine and biology. Our study demonstrates the importance of reinforcing institutional commitments to diversity through policies that support the inclusion and retention of women researchers.

Data availability

The current manuscript is a computational study, so no data have been generated for this manuscript. Source data and code will be provided on git-hub for all tables and figures.

Article and author information

Author details

  1. Emil Bargmann Madsen

    Danish Centre for Studies in Research and Research Policy, Aarhus University, Aarhus, Denmark
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-4394-5373
  2. Mathias Wullum Nielsen

    Department of Sociology, University of Copenhagen, Copenhagen, Denmark
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-8759-7150
  3. Josefine Bjørnholm

    Danish Centre for Studies in Research and Research Policy, Aarhus University, Aarhus, Denmark
    Competing interests
    No competing interests declared.
  4. Reshma Jagsi

    Department of Radiation Oncology, University of Michigan, Ann Arbor, United States
    Competing interests
    Reshma Jagsi, stock options as compensation for advisory board role at Equity Quotient, a company that evaluates culture in health care companies; has received personal fees from the National Institutes of Health (NIH) as a special government employee (in her role as a member of the Advisory Committee for Research on Women's Health), the Greenwall Foundation, and the Doris Duke Charitable Foundation; has received grants for unrelated work from the NIH, the Doris Duke Foundation, the Greenwall Foundation, the Komen Foundation, and Blue Cross Blue Shield of Michigan for the Michigan Radiation Oncology Quality Consortium; has held a contract to conduct an unrelated investigator-initiated study with Genentech; has served as an expert witness for Sherinian and Hasso, Dressman Benzinger LaVelle, and Kleinbard LLC..
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-6562-1228
  5. Jens Peter Andersen

    Danish Centre for Studies in Research and Research Policy, Aarhus University, Aarhus, Denmark
    For correspondence
    jpa@ps.au.dk
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-2444-6210

Funding

Samfund og Erhverv, Det Frie Forskningsråd (DFF-0133-00165B)

  • Emil Bargmann Madsen
  • Mathias Wullum Nielsen
  • Josefine Bjørnholm
  • Jens Peter Andersen

Aarhus Universitets Forskningsfond (AUFF-F-2018-7-5)

  • Jens Peter Andersen

Independent Research Fund Denmark (9130-00029B)

  • Mathias Wullum Nielsen

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Copyright

© 2022, Madsen et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

Metrics

  • 40
    citations

Views, downloads and citations are aggregated across all versions of this paper published by eLife.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

  1. Emil Bargmann Madsen
  2. Mathias Wullum Nielsen
  3. Josefine Bjørnholm
  4. Reshma Jagsi
  5. Jens Peter Andersen
(2022)
Meta-Research: Individual-level researcher data confirm the widening gender gap in publishing rates during COVID-19
eLife 11:e76559.
https://doi.org/10.7554/eLife.76559
  1. Further reading

Further reading

  1. Edited by Fred Atherden
    Collection

    eLife’s Executable Research Article lets authors include live code, data and interactive figures in their published paper.

    1. Computational and Systems Biology
    Masaaki Uematsu, Jeremy M Baskin
    Tools and Resources

    Plasmid construction is central to life science research, and sequence verification is arguably its costliest step. Long-read sequencing has emerged as a competitor to Sanger sequencing, with the principal benefit that whole plasmids can be sequenced in a single run. Nevertheless, the current cost of nanopore sequencing is still prohibitive for routine sequencing during plasmid construction. We develop a computational approach termed Simple Algorithm for Very Efficient Multiplexing of Oxford Nanopore Experiments for You (SAVEMONEY) that guides researchers to mix multiple plasmids and subsequently computationally de-mixes the resultant sequences. SAVEMONEY defines optimal mixtures in a pre-survey step, and following sequencing, executes a post-analysis workflow involving sequence classification, alignment, and consensus determination. By using Bayesian analysis with prior probability of expected plasmid construction error rate, high-confidence sequences can be obtained for each plasmid in the mixture. Plasmids differing by as little as two bases can be mixed as a single sample for nanopore sequencing, and routine multiplexing of even six plasmids per 180 reads can still maintain high accuracy of consensus sequencing. SAVEMONEY should further democratize whole-plasmid sequencing by nanopore and related technologies, driving down the effective cost of whole-plasmid sequencing to lower than that of a single Sanger sequencing run.