Gender Differences in the Pediatric Neurosurgical Workforce: Professional Practice, Work-Life Balance, and Beyond
Notice bibliographique
Résumé
BACKGROUND AND OBJECTIVES: Evidence suggests that female neurosurgeons experience unique challenges in the workplace including lack of academic advancement, challenges with work-life balance, harassment, and discrimination. How these factors influence the gender gap in neurosurgery remains unclear. This analysis investigated gender differences in pediatric neurosurgeons in professional and nonprofessional activities and responsibilities. METHODS: A survey examining professional activities, work-life balance, family dynamics, career satisfaction, and workplace discrimination and harassment was administered to 495 pediatric neurosurgeons. Response rate was 49% (n = 241). RESULTS: One-third of the pediatric neurosurgical workforce is female. There were no gender differences in race/ethnicity, American Board of Neurological Surgery/American Board of Pediatric Neurological Surgery certification rates, or pediatric neurosurgery fellowship completion. No gender differences were found in operative caseload, weekly hours worked, or working after 8 pm or weekends. Women took call more frequently than men ( P = .044). Men were more likely to work in academia ( P = .004) and have salary subsidization from external sources ( P = .026). Women were more likely to anticipate retirement by age 65 years ( P = .044), were less happy with call commitments ( P = .012), and worked more hours at home while off ( P = .050). Women more frequently reported witnessing and experiencing racial discrimination ( P = .008; P < .001), sexual harassment ( P = .002, P < .001), and feeling less safe at work ( P < .001). Men were more likely married ( P = .042) with 1 ( P = .004) or more children ( P = .034). Women reported significantly greater responsibility for child and domestic care ( P < .001). There were no gender differences in work-life balance, feeling supported at work, or having enough time to do things outside of work. CONCLUSION: Despite little difference in workload and professional responsibilities, women held more domestic responsibilities and experienced and witnessed more racial and sexual discrimination in the workplace. Surprisingly, there were no reported differences in work-life balance or feeling supported at work between genders. These findings suggest that factors unique to female neurosurgeons may contribute to continued gender disparity in the field.
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 | 0,004 |
| 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 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 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 ».