Retraction Prevalence and Gender Imbalance Among Highly-Cited Authors and Among All Authors Across Scientific Disciplines

John P. A. Ioannidis,^1,2,3,4 Angelo Maria Pezzullo,^4,5 Antonio Cristiano,^4,5 Guillaume Roberge,⁶ Stefania Boccia,^5,7 Jeroen Baas⁸ <h4>Objective</h4> <i> </i>Although retractions are increasingly frequent, they remain a small fraction of publications. We have previously incorporated retraction data into Scopus-based databases of top-cited (top 2%) scientists to facilitate linkage of retractions with impact metrics at the individual scientist level.¹ Here, we explored whether gender disparities in the likelihood of having retractions exist, both among highly cited authors and among all authors with at least 5 publications. <h4>Design </h4> On August 15, 2024, we screened 55,237 Retraction Watch records, excluding nonretractions, those clearly unrelated to author error, those tied to republished papers, or those not linkable to Scopus, leaving 39,468 eligible retractions. We examined demographics of scientists with and without retractions among highly cited authors (career-long: n = 217,097) and among all authors with at least 5 publications (n = 10,361,367). We were able to assign gender using NamSor² to 186,466 and 8,267,888 authors, respectively. We stratified authors by publication age, field,³ country income level (high, other), and publication volume, identifying for all these strata and for individual countries, men and women, and with and without retractions. We computed gender-specific retraction rates and calculated the relative propensity (R) of women vs men to have at least 1 retraction. <h4>Results </h4> Authors with retractions were more common among highly cited scientists (3.3%) than among non–highly cited scientists (0.7%). Overall, gender differences were modest: among highly cited authors, retraction rates were 2.9% for women and 3.1% for men; among all authors, retraction rates were 0.7% for both genders. Men consistently showed slightly higher retraction rates than women within both income groups. Field-specific analysis among all authors revealed women’s rates were at least one-third lower than men’s (R &lt; 0.67) in biology, biomedical research, and psychology and cognitive sciences, but higher (R &gt; 1.33) in economics and business, engineering, and information and communication technology. Among highly cited scientists, the highest women to men retraction ratios were in mathematics and statistics (R = 3.06) and engineering (R = 1.78), while biomedical research (R = 0.64) and built environment and design (R = 0.65) had lower rates for women. Across publication age cohorts, gender differences in retraction rates among all authors were minimal; however, among highly cited authors, younger cohorts showed increasingly higher rates among men (4.2% of men and 3.0% of women in those starting to publish in 2002-2011; 8.7% of men and 4.9% of women in those starting to publish post-2011). Country-level data revealed particularly large gender gaps in Pakistan (men, 28.7%; women, 14.3%), Iran (12.4% vs 9.3%), and India (9.2% vs 6.6%) among highly cited authors. Among all authors, country-level gender gaps were small. <h4>Conclusions </h4> Gender differences in retraction rates were small in most settings but varied by field, country, and publication cohort. Overall, field and country were more strongly associated with retraction rates than gender. These results highlight the need to account for structural and contextual factors when interpreting gender disparities. <h4>References</h4> 1. Ioannidis JPA, Pezzullo AM, Cristiano A, Boccia S, Baas J. Linking citation and retraction data reveals the demographics of scientific retractions among highly cited authors. <i>PLoS Biol.</i> 2025;23(1):e3002999. doi:10.1371/journal.pbio.3002999 2. NamSor. Accessed July 14, 2025. <a href="https://NamSor.app"><span class="Hyperlink CharOverride-6">https://NamSor.app</span></a> 3. Archambault É, Beauchesne OH, Caruso J. Towards a multilingual, comprehensive and open scientific journal ontology. In: <i>Proceedings of the 13th International Conference of the International Society for Scientometrics and Informetrics</i>. 2011;13:66-77. ¹Department of Medicine, Stanford University, Stanford, CA, US, jioannid@stanford.edu; ²Department of Epidemiology &amp; Population Health, Stanford University, Stanford, CA, US; ³Department of Biomedical Data Science, Stanford University, Stanford, CA, US; ⁴Meta-Research Innovation Center at Stanford (METRICS), Stanford University, Stanford, CA, US; ⁵Section of Hygiene, Department of Life Sciences and Public Health, Università Cattolica del Sacro Cuore, Rome, Italy; ⁶Analytics and Data Services, Elsevier B.V., Montreal, Canada; ⁷Department of Women, Children and Public Health Sciences, Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Rome, Italy; ⁸Research Intelligence, Elsevier B.V., Amsterdam, the Netherlands. <h4>Conflict of Interest Disclosures</h4> Guillaume Roberge and Jeroen Baas are employees of Elsevier. John P. A. Ioannidis is a member of the Peer Review Congress Advisory Board but was not involved in the review or decision for this abstract. <h4>Additional Information </h4> Elsevier runs Scopus, which is the source of these data, and also runs the repository where the database of highly cited scientists is now stored.

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