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Author or just ‘acknowledged’? How women are not gaining full credit for research

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Nature, Published online: 11 November 2026; doi:10.1038/d41586-026-03448-7 An analysis of who is more likely to get authorship than acknowledgement highlights the influence of a researcher’s gender and status.

Original text(via Nature)
Conceptual image of colourful paper cutouts of male and female silhouettes standing divided by dotted line.
Conceptual image of colourful paper cutouts of male and female silhouettes standing divided by dotted line.

The number of men with high citation counts exceeds that of women.Credit: FotografiaBasica/iStock via Getty

Women are more frequently mentioned in the acknowledgements section of papers than credited as co-authors, especially for research and analytical work, a study has found. But status seems to trump gender.

An analysis of more than 20,000 authors and 60,000 acknowledged contributors on papers published in seven PLOS journals between 2016 and 2021 highlighted persistent disparities between women and men in who gets authorship over an acknowledgement.

The study, published in Scientometrics1, also found that highly cited researchers — used by the authors as a proxy for higher status — were more likely to receive authorship over acknowledgement than were their less-cited collaborators, irrespective of gender. When a highly cited woman collaborated with a less-cited man, for example, the woman was more likely to be credited as an author.

Authorship is one of the most important metrics in research evaluation, grant reviews and promotion decisions, whereas acknowledgements aren’t typically factored in. The difference between getting authorship credit versus an acknowledgement can make or break a researcher’s career. One famous example is chemist Rosalind Franklin, a key contributor to the discovery of the DNA double helix. Franklin was mentioned in the acknowledgements section of the 1953 paper describing the finding, which went on to win the 1962 Nobel Prize in Physiology or Medicine, rather than being named a co-author with James Watson and Francis Crick.

The Scientometrics study highlights the importance of status in determining who gets credit, and the uphill battle that many women in research have to face — especially in their early and mid-careers. The number of highly cited men exceeded that of women, suggesting that even if women benefit from high status once they have attained it, fewer women attain higher status in the first place.

“We realized that the issue is double. One linked with gender bias, but another surprisingly due to hierarchy bias,” says Yukie Sano, a computational scientist at the University of Tsukuba in Japan, who co-authored the paper.

Tracking credit

The impact of a researcher’s status and gender on academic credit is well-documented, but Sano and her co-authors point to the Contributor Role Taxonomy (CRediT) — a standardized system describing specific roles that individual scientists often take on during research — as a game-changer by providing high-quality data to track this metric across journals and disciplines.

Sano and her colleagues used CRediT data from open-access PLOS journals (which implemented the system in 2016) to track the contributions of authors and devised a separate system to track contributions in the acknowledgements section. Author gender was determined using Gender API, an artificial-intelligence-powered service that infers a person’s gender on the basis of their name.

The team found that men were generally more likely than women to receive authorship credit — particularly in investigation roles (performing the experiments) and analysis roles (analysing or synthesizing the study data). Around 70% of men were credited as authors, compared with about 65% of women.

The size of the gender gap varied between disciplines, but was particularly evident in medicine, biology and computer science, whereas environmental science showed little evidence of a gender difference in authorship versus acknowledgement rates.

Status effect

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doi: https://doi.org/10.1038/d41586-026-03448-7

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References

  • Kusumegi, K., Acuña, D. E. & Sano, Y. Scientometrics 131, 5781–5801 (2026).Article Google Scholar

Kusumegi, K., Acuña, D. E. & Sano, Y. Scientometrics 131, 5781–5801 (2026).

Article Google Scholar

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