The DOI matches its Crossref record; 10 of the 10 references it cites were found in a registry or an index.
Quantitative evaluation of gender bias in astronomical publications from citation counts
Open accessAbstract
Numerous studies across different research fields have shown that both male and female referees consistently give higher scores to work done by men than to identical work done by women1,2,3. In addition, women are under-represented in prestigious publications and authorship positions4,5 and women receive ~10% fewer citations6,7. In astronomy, similar biases have been measured in conference participation8,9 and success rates for telescope proposals10,11. Even though the number of doctorate degrees awarded to women is constantly increasing, women still tend to be under-represented in faculty positions12. Spurred by these findings, we measure the role of gender in the number of citations that papers receive in astronomy. To account for the fact that the properties of papers written by men and women differ intrinsically, we use a random forest algorithm to control for the non-gender-specific properties of these papers. Here we show that papers authored by women receive 10.4 ± 0.9% fewer citations than would be expected if the papers with the same non-gender-specific properties were written by men. Gender discrimination is very much an issue in academia generally and in astronomy specifically. Through machine learning techniques, astronomy papers authored by women are shown to have 10% systematically fewer citations than those authored by men.
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Cites
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Matplotlib: a 2D graphics environment
Hunter, J. D. (2007) · Computing in Science & Engineering · doi:10.1109/mcse.2007.55 · Cited by 39,249
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
Groups of diverse problem solvers can outperform groups of high-ability problem solvers
Hong, L., & Page, S. E. (2004) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0403723101 · Cited by 2,103
Bibliometrics: Global gender disparities in science
Larivière, V., Ni, C., Gingras, Y., Cronin, B., & Sugimoto, C. R. (2013) · Nature · doi:10.1038/504211a · Cited by 1,493
Nepotism and sexism in peer-review
Wennerås, C., & Wold, A. (1997) · Nature · doi:10.1038/387341a0 · Cited by 1,345
The Role of Gender in Scholarly Authorship
West, J. D., Jacquet, J., King, M. M., Correll, S. J., & Bergstrom, C. T. (2013) · PLoS ONE · doi:10.1371/journal.pone.0066212 · Cited by 892
Double-blind review favours increased representation of female authors
BUDDEN, A., TREGENZA, T., AARSSEN, L., KORICHEVA, J., LEIMU, R., & LORTIE, C. (2008) · Trends in Ecology & Evolution · doi:10.1016/j.tree.2007.07.008 · Cited by 552
On the Compliance of Women Engineers with a Gendered Scientific System
Ghiasi, G., Larivière, V., & Sugimoto, C. R. (2015) · PLoS ONE · doi:10.1371/journal.pone.0145931 · Cited by 145
Pritchard, J. R., Masters, K. L., Allen, J. D. V., Contenta, F., Huckvale, L., Wilkins, S. M., & Zocchi, A. (2014) · Astronomy & Geophysics · doi:10.1093/astrogeo/atu245 · Cited by 23
Cited by
The gender gap in science: How long until women are equally represented?
Holman, L., Stuart-Fox, D., & Hauser, C. E. (2018) · PLOS Biology · doi:10.1371/journal.pbio.2004956 · Cited by 769
Environmental influences on the pace of brain development
Tooley, U. A., Bassett, D. S., & Mackey, A. P. (2021) · Nature reviews. Neuroscience · doi:10.1038/s41583-021-00457-5 · Cited by 488
Gender bias in scholarly peer review
Helmer, M., Schottdorf, M., Neef, A., & Battaglia, D. (2017) · eLife · doi:10.7554/elife.21718 · Cited by 380
Socioeconomic roots of academic faculty
Morgan, A. C., LaBerge, N., Larremore, D. B., Galesic, M., Brand, J. E., & Clauset, A. (2022) · Nature Human Behaviour · doi:10.1038/s41562-022-01425-4 · Cited by 269
A review on application of artificial intelligence in teaching and learning in educational contexts
Fahimirad, M., & Kotamjani, S. S. (2018) · International Journal of Learning and Development · doi:10.5296/ijld.v8i4.14057 · Cited by 240
Metadata
- Authors
- Caplar, N., Tacchella, S., & Birrer, S.
- Venue
- Nature Astronomy
- Published
- 2017-05-26
- Volume
- 1
- Issue
- 6
- ISSN
- 2397-3366 (ISSN-L)
- OpenAlex
- W2541604517
- Cited by
- 308
- References
- 10
- FWCI
- 14.92
- Type
- journal article
- Language
- en
- Open access
- bronze
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- Caplar, N., Tacchella, S., & Birrer, S. (2017). Quantitative evaluation of gender bias in astronomical publications from citation counts. Nature Astronomy. https://doi.org/10.1038/s41550-017-0141
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.
