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Record W3180740175 · doi:10.1136/bmjopen-2021-051224

Gender disparity between authors in leading medical journals during the COVID-19 pandemic: a cross-sectional review

2021· review· en· W3180740175 on OpenAlexafffund
Vaidehi Misra, Frozan Safi, Kathryn A Brewerton, Wei Wu, Robín Masón, An‐Wen Chan, Paula A. Rochon, Iliana C. Lega, Husam Abdel‐Qadir

Bibliographic record

VenueBMJ Open · 2021
Typereview
Languageen
FieldSocial Sciences
TopicDiversity and Career in Medicine
Canadian institutionsUniversity Health NetworkInstitute for Clinical Evaluative SciencesPublic Health OntarioUniversity of TorontoWomen's College Hospital
FundersHeart and Stroke Foundation of Canada
KeywordsMedicineCoronavirus disease 2019 (COVID-19)Cross-sectional studyLogistic regressionPandemicOdds ratioOddsFamily medicineDemographyMEDLINEGerontologyInternal medicineDiseasePathology

Abstract

fetched live from OpenAlex

OBJECTIVES: Evaluate gender differences in authorship of COVID-19 articles in high-impact medical journals compared with other topics. DESIGN: Cross-sectional review. DATA SOURCES: Medline database. ELIGIBILITY CRITERIA: Articles published from 1 January to 31 December 2020 in the seven leading general medical journals by impact factor. Article types included primary research, reviews, editorials and commentaries. DATA EXTRACTION: Key data elements were whether the study topic was related to COVID-19 and names of the principal and the senior authors. A hierarchical approach was used to determine the likely gender of authors. Logistic regression assessed the association of study characteristics, including COVID-19 status, with authors' likely gender; this was quantified using adjusted ORs (aORs). RESULTS: We included 2252 articles, of which 748 (33.2%) were COVID-19-related and 1504 (66.8%) covered other topics. A likely gender was determined for 2138 (94.9%) principal authors and 1890 (83.9%) senior authors. Men were significantly more likely to be both principal (1364 men; 63.8%) and senior (1332 men; 70.5%) authors. COVID-19-related articles were not associated with the odds of men being principal (aOR 0.99; 95% CI 0.81 to 1.21; p=0.89) or senior authors (aOR 0.96; 95% CI 0.78 to 1.19; p=0.71) relative to other topics. Articles with men as senior authors were more likely to have men as principal authors (aOR 1.49; 95% CI 1.21 to 1.83; p<0.001). Men were more likely to author articles reporting original research and those with corresponding authors based outside the USA and Europe. CONCLUSIONS: Women were substantially under-represented as authors among articles in leading medical journals; this was not significantly different for COVID-19-related articles. Study limitations include potential for misclassification bias due to the name-based analysis. Results suggest that barriers to women's authorship in high-impact journals during COVID-19 are not significantly larger than barriers that preceded the pandemic and that are likely to continue beyond it. PROSPERO REGISTRATION NUMBER: CRD42020186702.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.013
metaresearch head score (Gemma)0.059
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Incentives · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.987
Threshold uncertainty score0.068

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.059
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0110.013
Science and technology studies0.0010.001
Scholarly communication0.0020.003
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.644
GPT teacher head0.617
Teacher spread0.028 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designObservational
DomainIncentives
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations42
Published2021
Admission routes2
Has abstractyes

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