2022
DOI: 10.1038/s41386-022-01288-3
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Neuropsychopharmacology (NPP) 2020 report on gender balance among corresponding authors and reviewers: before and during the COVID-19 pandemic

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Cited by 3 publications
(4 citation statements)
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“…Our dataset enabled us to look at both invitations and responses to these same invitations, and we found that women were not only less frequently invited to review but also agreed less often than men, compounding this gender inequality. Although some gender inequality in peer review activity has been reported in the early pandemic period,23 other studies found no difference in overall patterns of review activity and women’s peer review activity 153233. To the best of our knowledge, our study was the first to look at invitations and responses to invitations by gender in the later stages of the pandemic compared with pre-pandemic.…”
Section: Discussionmentioning
confidence: 67%
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“…Our dataset enabled us to look at both invitations and responses to these same invitations, and we found that women were not only less frequently invited to review but also agreed less often than men, compounding this gender inequality. Although some gender inequality in peer review activity has been reported in the early pandemic period,23 other studies found no difference in overall patterns of review activity and women’s peer review activity 153233. To the best of our knowledge, our study was the first to look at invitations and responses to invitations by gender in the later stages of the pandemic compared with pre-pandemic.…”
Section: Discussionmentioning
confidence: 67%
“…This is the first study to explore gender and geographical diversity in invitations to review and responses to these invitations and to consider factors associated with this agreement at several levels (journals, manuscripts, reviewers, and editors). We included all review invitations at multiple journals, whereas other studies have been limited to online peer review reports of published manuscripts, focused on a single journal, or used aggregated metadata 1415161718192023323335. We explored geographical diversity by using multivariable analyses with both geographical affiliation and the income level of the country, which increases the understanding of the identified associations.…”
Section: Discussionmentioning
confidence: 99%
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“…Gender representation among the content creators was determined using the Gender Application Programming Interface (API) (https://gender-api.com/), a leading gender inference service. Leveraging a large database of names, social media insights, and sociolinguistics, Gender API predicts sex based on a person's name—a methodology that has been tested, validated, and commonly used in representation studies across various fields 8,9 . However, it is important to note that this tool is restricted to binary gender classification and lacks the capability to accurately infer nonbinary genders.…”
Section: Methodsmentioning
confidence: 99%