The DOI matches its Crossref record; 38 of the 38 references it cites were found in a registry or an index.
Gender contributes to personal research funding success in The Netherlands
Open accessAbstract
Significance: Women remain underrepresented in academia as they continue to face a leadership gap, salary gap, and funding gap. Closing the funding gap is of particular importance, because this may directly retain women in academia and foster the closing of other gaps. In this study, we examined the grant funding rates of a national full population of early career scientists. Our results reveal gender bias favoring male applicants over female applicants in the prioritization of their “quality of researcher” (but not “quality of proposal”) evaluations and success rates, as well as in the language use in instructional and evaluation materials. This work illuminates how and when the funding gap and the subsequent underrepresentation of women in academia are perpetuated.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Women in the boardroom and their impact on governance and performance☆
Adams, R. B., & Ferreira, D. (2009) · Journal of Financial Economics · doi:10.1016/j.jfineco.2008.10.007 · Cited by 5,711
Stereotypes and prejudice: Their automatic and controlled components
Devine, P. G. (1989) · Journal of Personality and Social Psychology · doi:10.1037/0022-3514.56.1.5 · Cited by 5,673
Science faculty’s subtle gender biases favor male students
Moss-Racusin, C. A., Dovidio, J. F., Brescoll, V. L., Graham, M. J., & Handelsman, J. (2012) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1211286109 · Cited by 3,150
Expectations of brilliance underlie gender distributions across academic disciplines
Leslie, S.-J., Cimpian, A., Meyer, M., & Freeland, E. (2015) · Science · doi:10.1126/science.1261375 · Cited by 1,516
Nepotism and sexism in peer-review
Wennerås, C., & Wold, A. (1997) · Nature · doi:10.1038/387341a0 · Cited by 1,345
Gender and the effectiveness of leaders: A meta-analysis.
Eagly, A. H., Karau, S. J., & Makhijani, M. G. (1995) · Psychological Bulletin · doi:10.1037//0033-2909.117.1.125 · Cited by 1,284
Gender Similarities and Differences
Hyde, J. S. (2014) · Annual Review of Psychology · doi:10.1146/annurev-psych-010213-115057 · Cited by 1,262
Why So Slow?: The Advancement of Women
Valian, V. (1999) · doi:10.7551/mitpress/7235.001.0001 · Cited by 1,252
Nosek, B. A., Smyth, F. L., Sriram, N., Lindner, N. M., Devos, T., Ayala, A., Bar-Anan, Y., Bergh, R., Cai, H., Gonsalkorale, K., et al. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0809921106 · Cited by 1,050
Women in Academic Science: A Changing Landscape
Ceci, S. J., Ginther, D. K., Kahn, S., & Williams, W. M. (2014) · Psychological Science in the Public Interest · doi:10.1177/1529100614541236 · Cited by 1,019
Cited by
Gender Bias in Teaching Evaluations
Mengel, F., Sauermann, J., & Zölitz, U. (2019) · Journal of the European Economic Association · doi:10.1093/jeea/jvx057 · Cited by 401
Systemic racial disparities in funding rates at the National Science Foundation
Chen, C. Y., Kahanamoku, S. S., Tripati, A., Alegado, R. A., Morris, V. R., Andrade, K., & Hosbey, J. (2022) · eLife · doi:10.7554/elife.83071 · Cited by 127
Prevalence of female authors in case reports published in the medical literature
Hsiehchen, D., Hsieh, A., & Espinoza, M. (2019) · JAMA Network Open · doi:10.1001/jamanetworkopen.2019.5000 · Cited by 23
Metadata
- Authors
- van der Lee, R., & Ellemers, N.
- Venue
- Proceedings of the National Academy of Sciences
- Published
- 2015-09-21
- Volume
- 112
- Issue
- 40
- Pages
- 12349-12353
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- OpenAlex
- W2152573571
- Cited by
- 304
- References
- 38
- FWCI
- 51.50
- Type
- journal article
- Language
- en
- Open access
- bronze
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Gender contributes to personal research funding success in The Netherlands. https://app.cochat.ai/papers/10.1073/pnas.1510159112
- The paper
- van der Lee, R., & Ellemers, N. (2015). Gender contributes to personal research funding success in The Netherlands. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.1510159112
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
