Geographical and Gender Diversity in Cochrane and non-Cochrane Reviews Authorship: A Meta-Research Study
Notice bibliographique
Résumé
Abstract Background Cochrane is a recognized source of quality evidence that informs health-related decisions. As an organization, it represents a global network of diverse stakeholders. Cochrane’s key organizational values include diversity and inclusion, to enable wide participation and promote access. However, the diversity of Cochrane review authorship has not been well summarized. Objective The aim of this study was to examine the distribution of country, region, language, and gender diversity in the authorship of Cochrane and non-Cochrane systematic reviews. Methods We retrieved all published articles from the Cochrane Library (until November 6, 2023)—a web crawling technique that extracted pre-specified data fields, including publication date, review type, and author affiliations. We used E-utility calls to capture the data for non-Cochrane systematic reviews. We determined the country and region of affiliations and the gender of the first, corresponding, and last authors for Cochrane reviews, as well as the country and region of affiliations and the gender of the first authors for non-Cochrane reviews. Trends in geographical and gender diversity over time were evaluated using logistic regression. Fisher’s exact test was used for comparisons. The diversity of first authors between Cochrane and non-Cochrane reviews was explored through visual presentation, Pearson’s product-moment correlation, and the Granger Causality Test. We used R for data collection and analysis. Results A total of 22681 citations were retrieved. The United Kingdom had the highest first-author representation (33.2%), followed by Australia (11.6%) and the United States (7.0%). We observed an increase in the proportion of first authors from non-English speaking countries, from 16.7% in 1996 to 42.8% in 2023. Female first authorship increased steadily, from 15.0% in 1996 to 55.6% in 2023. The proportion of first authors from lower-and-middle-income countries (LMICs) was highest in 2012 at 23.2%. Since then, it has decreased to 18.4% in 2023. Similarly, the proportion of last authors from LMICs decreased over time (25.0% in 1996 vs. 16.2% in 2023). Among review groups, Sexually Transmitted Infections and Consumers and Communication were the most and least diverse groups with 68.1% and 1.6% of first authors from LMICs, respectively. In terms of gender diversity, Fertility Regulation had the highest percentage of female first authors (72.1%). Urology (28.1%) had the lowest percentage of female first authors. In 2023, over half of the non-Cochrane reviews had first authors from non-English-speaking countries (n=14,589, 56.9%), 50.8% (n=13,014) had first authors from LMICs, and 42.3% (n=10,841) had female first authors. The Pearson’s product-moment correlations between Cochrane and non-Cochrane reviews’ trends were 0.265 (P=0.450) for LMICs, 0.823 (P<0.001) for non-English speaking, 0.634 (P<0.001) Spanish-speaking, and 0.829 (P<0.001) for female first authorship. Conclusion Overall, this study found positive trends, with an increase in first authorship by individuals who were female and from non-English speaking countries. However, the representation of first authors from LMICs decreased. Future research could further explore these trends, identifying potential barriers influencing access and participation of individuals and groups and assessing strategies that help promote diversity and inclusion.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,078 | 0,299 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,011 | 0,025 |
| Bibliométrie | 0,026 | 0,033 |
| Études des sciences et des technologies | 0,001 | 0,002 |
| Communication savante | 0,007 | 0,007 |
| Science ouverte | 0,003 | 0,004 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».