@article{ddac4a04811f4b11a1b92a0642b7438e,
title = "Women are credited less in science than men",
abstract = "There is a well-documented gap between the observed number of works produced by women and by men in science, with clear consequences for the retention and promotion of women1. The gap might be a result of productivity differences2–5, or it might be owing to women{\textquoteright}s contributions not being acknowledged6,7. Here we find that at least part of this gap is the result of unacknowledged contributions: women in research teams are significantly less likely than men to be credited with authorship. The findings are consistent across three very different sources of data. Analysis of the first source—large-scale administrative data on research teams, team scientific output and attribution of credit—show that women are significantly less likely to be named on a given article or patent produced by their team relative to their male peers. The gender gap in attribution is present across most scientific fields and almost all career stages. The second source—an extensive survey of authors—similarly shows that women{\textquoteright}s scientific contributions are systematically less likely to be recognized. The third source—qualitative responses—suggests that the reason that women are less likely to be credited is because their work is often not known, is not appreciated or is ignored. At least some of the observed gender gap in scientific output may be owing not to differences in scientific contribution, but rather to differences in attribution.",
author = "Ross, {Matthew B.} and Glennon, {Britta M.} and Raviv Murciano-Goroff and Berkes, {Enrico G.} and Weinberg, {Bruce A.} and Lane, {Julia I.}",
note = "Funding Information: For each pay period, the FHR system at each university records the details of charges to each sponsored project, including for each person paid on each grant and reports the information to the Institute for Research on Innovation and Science. These administrative data are different from the level-of-effort data that are submitted by PIs as part of their annual and final report to an agency in at least three ways. First, they represent actual payroll data, drawn from the FHR system every pay period, rather than the estimate provided by the PI or the team administrator once a year. An intensive hand-curated effort that compared the results from an early effort found that the FHR reports are more granular and comprehensive than the PI or team administrator reports. For example, all personnel names (including co-PIs) are recorded in the FHR reports, but many names are not recorded in the former. Second, the UMETRICS data capture all sources of funding, and are much more comprehensive than data from a single agency. The UMETRICS data include federal funding sources as well as funding from philanthropic foundations, state and local governments, industry, and international organizations. Third, the data reflect actual expenditures in every accounting time period, not just funds that are obligated at the beginning of a grant. So if, as often happens, there is a no-cost extension, or more funds are spent earlier in the project, that spending and the work of the relevant team members is captured in the data. There are limitations. If personnel do not charge time to the grant, their effort is not captured in the data; we are unaware of any source that would capture unpaid work. If there are gender differences in unpaid research work, the analysis would not be able to capture such differences. , Publisher Copyright: {\textcopyright} 2022, The Author(s).",
year = "2022",
month = aug,
day = "4",
doi = "10.1038/s41586-022-04966-w",
language = "English (US)",
volume = "608",
pages = "135--145",
journal = "Nature Cell Biology",
issn = "1465-7392",
publisher = "Nature Publishing Group",
number = "7921",
}