The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Bibliometrics: Global gender disparities in science
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
Understanding current causes of women's underrepresentation in science
Ceci, S. J., & Williams, W. M. (2011) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1014871108 · Cited by 1,114
Cited by
Fortunato, S., Bergstrom, C. T., Börner, K., Evans, J. A., Helbing, D., Milojević, S., Petersen, A. M., Radicchi, F., Sinatra, R., Uzzi, B., et al. (2018) · Science · doi:10.1126/science.aao0185 · Cited by 1,497
“Gender inequality in science remains prevalent and problematic (34).”
Gender inequality and restrictive gender norms: Framing the challenges to health
Heise, L., Greene, M. E., Opper, N., Stavropoulou, M., Harper, C., Nascimento, M., Zewdie, D., Darmstadt, G. L., Greene, M. E., Hawkes, S., et al. (2019) · The Lancet · doi:10.1016/s0140-6736(19)30652-x · Cited by 1,163
Team size matters: Collaboration and scientific impact since 1900
Larivière, V., Gingras, Y., Sugimoto, C. R., & Tsou, A. (2015) · Journal of the Association for Information Science and Technology · doi:10.1002/asi.23266 · Cited by 484
Self-citationGender bias in scholarly peer review
Helmer, M., Schottdorf, M., Neef, A., & Battaglia, D. (2017) · eLife · doi:10.7554/elife.21718 · Cited by 380
Fanelli, D., Costas, R., & Larivière, V. (2015) · PLOS ONE · doi:10.1371/journal.pone.0127556 · Cited by 268
Self-citationMen Set Their Own Cites High: Gender and Self-citation across Fields and over Time
King, M. M., Bergstrom, C. T., Correll, S. J., Jacquet, J., & West, J. D. (2017) · Socius: Sociological Research for a Dynamic World · doi:10.1177/2378023117738903 · Cited by 275
Reale, E., Avramov, D., Canhial, K., Donovan, C., Flecha, R., Holm, P., Larkin, C., Lepori, B., Mosoni-Fried, J., Oliver, E., et al. (2018) · Research Evaluation · doi:10.1093/reseval/rvx025 · Cited by 258
Gender differences in how scientists present the importance of their research: observational study
Lerchenmueller, M. J., Sorenson, O., & Jena, A. B. (2019) · BMJ · doi:10.1136/bmj.l6573 · Cited by 211
A systematic identification and analysis of scientists on Twitter
Ke, Q., Ahn, Y.-Y., & Sugimoto, C. R. (2017) · PLOS ONE · doi:10.1371/journal.pone.0175368 · Cited by 175
Self-citationSystemic 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
The Mismeasure of Science: Citation Analysis
MacRoberts, M. H., & MacRoberts, B. R. (2018) · Journal of the Association for Information Science and Technology · doi:10.1002/asi.23970 · Cited by 101
Investigating the division of scientific labor using the Contributor Roles Taxonomy (CRediT)
Larivière, V., Pontille, D., & Sugimoto, C. R. (2021) · Quantitative Science Studies · doi:10.1162/qss_a_00097 · Cited by 97
Self-citationHomophily and the Glass Ceiling Effect in Social Networks
Avin, C., Keller, B., Lotker, Z., Mathieu, C., Peleg, D., & Pignolet, Y.-A. (2015) · Proceedings of the 2015 Conference on Innovations in Theoretical Computer Science · doi:10.1145/2688073.2688097 · Cited by 90
The landscape of biomedical research
González-Márquez, R., Schmidt, L., Schmidt, B. M., Berens, P., & Kobak, D. (2024) · Patterns · doi:10.1016/j.patter.2024.100968 · Cited by 89
The good, the bad and the rude peer-review
Mavrogenis, A. F., Quaile, A., & Scarlat, M. M. (2020) · International Orthopaedics · doi:10.1007/s00264-020-04504-1 · Cited by 85
Quantifying the use and potential benefits of artificial intelligence in scientific research
Gao, J., & Wang, D. (2024) · Nature Human Behaviour · doi:10.1038/s41562-024-02020-5 · Cited by 81
Twitter's Glass Ceiling: The Effect of Perceived Gender on Online Visibility
Nilizadeh, S., Groggel, A., Lista, P., Das, S., Ahn, Y.-Y., Kapadia, A., & Rojas, F. (2021) · Proceedings of the International AAAI Conference on Web and Social Media · doi:10.1609/icwsm.v10i1.14711 · Cited by 48
Malhotra, K., & Kempegowda, P. (2023) · Journal of Medical Internet Research · doi:10.2196/49220 · Cited by 26
AlShebli, B., Makovi, K., & Rahwan, T. (2020) · Nature Communications · doi:10.1038/s41467-020-20617-y · Cited by 23
RetractedBardolph, D. N. (2018) · California Archaeology · doi:10.1080/1947461x.2018.1535813 · Cited by 18
Metaresearch study highlights the gender gap in randomized controlled trials in dentistry
Prado, M. C., Dotto, L., Agostini, B. A., & Sarkis-Onofre, R. (2023) · Journal of Clinical Epidemiology · doi:10.1016/j.jclinepi.2023.08.005 · Cited by 10
Unveiling the ethical void: Bias in reference citations and its academic ramifications
Mattiazzi, A., & Vila-Petroff, M. (2024) · Current Research in Physiology · doi:10.1016/j.crphys.2024.100130 · Cited by 6
Metadata
- Authors
- Larivière, V., Ni, C., Gingras, Y., Cronin, B., & Sugimoto, C. R.
- Venue
- Nature
- Published
- 2013-12-11
- Volume
- 504
- Issue
- 7479
- Pages
- 211-213
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- OpenAlex
- W2050990045
- Cited by
- 1,493
- References
- 1
- FWCI
- 45.53
- Type
- journal article
- Language
- en
- Open access
- closed
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
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.
