Authorship Diversity in General Surgery Related Cochrane Systematic Reviews
Notice bibliographique
Résumé
Background
 This study sought to determine the gender and country diversity in authorship representation in the authorship of Cochrane systematic reviews related to General Surgery.
 
 Methods
 We searched and extracted data from the Cochrane Library on 3 September 2022 using ‘keyword:General surgery’, and included published reviews, protocols, and withdrawn publications. We extracted authors’ details and searched online to determine their gender, attempting to capture at least one webpage demonstrating it. Authors whose gender could not be ascertained were excluded from gender-based analyses. For graphical representation, we used a choropleth-style map. We treated a collaborative author group belonging to a single country, e.g., MRC Clinical Trials Unit (UK), as a single author. A second author independently cross-verified the extracted data.
 
 Result
 Two hundred and fifty publications with a total of 1420 authors were included in the current study. Four authors had affiliation to two countries. The leading five represented nations (Figure 1A) in authorship were United Kingdom (n=562, 39.4%), China (n=163, 11.5%), Italy (n=144, 10.1%), Canada (n=91, 6.4%), and United States of America (n=89, 6.2%). 
 Syria is the only country among all the low-income countries which had authorship representation and constituted 0.34% (n=5) of all the authors. India (n=8, 0.6%) and Nigeria (n=2, 0.1%) were the only countries from lower-middle income groups who had representation.
 Male (n=957) to female (n=453) ratio in this study was 2.11:1 (Figure 1B). Sex data for ten authors couldn’t be retreived and were categorized as ‘unknown’ group. There were 169 (67.3%) male and 82 (32.6%) female first authors (sex ratio 2.06:1). One study had designated two authors as co-first authors. Women (n= 81) constituted 32.4% of all the corresponding authors (sex ratio 2.06:1). One article didn’t have any designated corresponding author. One hundred and fifty (60%) studies didn’t have any female representation in any lead author (corresponding or first author) position. Fifty-eight (23.2%) studies didn’t have any female authors at all, whereas in contrast there were only eight studies (3.2%) which did not have any male authors.
 
 Conclusion
 Authors from high-income countries continue to be the largest contributors to Cochrane systematic reviews in General Surgery, source of one of the highest quality evidence. There is extremely poor representation of female authors and authors from low and low-middle-income countries. Active capacity-building efforts are needed in several countries for advancing authorship diversity.
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,024 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,003 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,004 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,010 | 0,000 |
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 tête enseignante, 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 ».