Sex Differences in Faculty Rank and Leadership Positions Amongst Hematologists and Oncologists in United States: A Cross-Sectional Study
Notice bibliographique
Résumé
Introduction: We have previously reported underrepresentation of female faculty at senior academic ranks in hematology/oncology (H/O). In this analysis we aimed to investigate the influence of sex in attaining leadership positions amongst academic hematologists/oncologists in United States. Methods: Faculty members were identified at 146 H/O fellowship programs listed on fellowship and residency electronic interactive database (FREIDA.) Data was collected on demographics, academic rank and research output using Doximity and Scopus databases. We compared the unadjusted characteristics of men and women by using two-sided t-tests and χ2 tests where appropriate. In primary analysis, logistic regression models were used to evaluate sex differences on probability of having full professorship (versus assistant and associate professorship) and of achieving leadership positions including division chief, Program Director (PD) and Associate Program Director (APD). Adjusted models included the following variables: clinical experience in years, number of publications, h-index, appointment at top 20 hospital, clinical trial investigator status and National Institutes of Health funding. Stratified analysis was performed adjusting for duration of clinical experience (≤15 vs >15 years) Results: Fewer women were full Professors (21.9% vs 78.1%), division chiefs (16.7% vs 83.3%), and PDs (30.5% vs 69.5) but the number was similar for Associate Program Directors (47.1% vs 52.9%). In a univariate unadjusted model, women were less likely to be full professors compared to men (OR 0.39; 95% confidence interval [CI], 0.31-0.48; P<.001). However, in the multivariable adjusted model no statistically significant sex difference in full professorship was found (OR 1.05; 95% CI 0.71, 1.57; P=.85; Table). The likelihood of full professorship was positively associated with clinical experience in years, number of first/last author publications, h-index, and being a primary investigator on at least one clinical trial.In a univariate unadjusted model, women were less likely to be division chiefs as compared to males (OR 0.35; 95% CI, 0.16, 0.80; P=.01). However, in the multivariable adjusted model, there was no statistically significant sex difference in achieving the position of division chief (OR 0.57; 95% CI 0.20, 1.58; P=.28; Table). No significant difference was found between females and males for being program directors or associate program directors in both univariate and multivariate analysis. Similarly, a stratified analysis adjusting for duration of clinical experience (≤15 vs >15 years) found no significant sex differences in attaining leadership position (Table) Conclusion: We found that women are underrepresented at higher academic ranks and in leadership positions in hematology/oncology, but that sex is not a significant negative predictor to women obtaining leadership positions after correcting for traditional predictors of academic success. However, "non-traditional" and therefore less measurable and analyzable factors such as networking, mentorship, sponsorship, gender bias, balancing work and home responsibilities and many others may contribute and should be further investigated. Disclosures No relevant conflicts of interest to declare.
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 | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 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 ».