Ethnicity and gender trends of UK authors in The British Medical Journal and the Lancet over the past two decades: a comprehensive longitudinal analysis
Notice bibliographique
Résumé
Background While gender equity among academic authors has been extensively investigated, there is a significant gap in our understanding of racial/ethnic authorship trends, despite the recognition of barriers to authorship along both ethnic and gender lines. Leveraging the meta-data for all articles published in The British Medical Journal (The BMJ) and the Lancet and between 2002 and 2022 (inclusive), we explore demographic trends among UK academic medicine authors in two of the world's leading British medical journals. Methods We systematically searched PubMed's MEDLINE for all articles published in The BMJ and Lancet between January 1st 2002 and December 31st 2022. Filtering for articles with a UK affiliation, we predicted gender using a publicly-validated name-to-gender dictionary, while data was analysed to explore and investigate ethnicity using the Consumer Data Research Centre's (CDRC) Ethnicity Estimator. Data was analysed to explore and investigate: (a) the proportion of female/male author publications, (b) the proportion of the various UK author ethnicity groups, and (c) the overlap/intersection between gender and ethnic identities among first and last authors. This comprehensive longitudinal analysis was conducted on 82,143 articles (51,209 from The BMJ and 30,934 from the Lancet ) which represents >97% of all published articles between 2002 and 2022. As we sought to understand how academic authorship reflects the diversity of the UK population, we limited our analysis to first and last authors who had a UK affiliation and excluded "news" and "comments" pieces (16,736 articles for The BMJ and 4678 articles from the Lancet ). The main outcome measures were the trends in first and last authorship demographics of academic medicine, focusing on the proportion of female/male authors, ethnicity and their intersectionality. Findings Our findings show that, while women have made substantial headway towards equity among first and last authorship in The BMJ (peaking at 42% and 43%), they remain under-represented in the Lancet (35% and 27%). In both The BMJ and Lancet , Black authors have remained severely under-represented as both first and last authors (below 1% for most of the two decades), while Asian authors have increased proportionally to match their fraction in the general population (ranging from 2 to 10%). Interpretation Analysis over the past two decades has shown that the gender author gap is decreasing quickly in The BMJ and Lancet . However, despite the two journals' growing focus on structural inequalities in medical academia, little progress has been made in rectifying the large gap between White British authors and other ethnic groups, especially Black authors. Without more awareness, diversity initiatives which have resulted in positive gains for White women do not seem to translate well for authors of colour. Funding None.
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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 | 0,016 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,005 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 ».