Sex differences in first-year students at Canadian medical schools.
Notice bibliographique
Résumé
OBJECTIVES: To compare male and female medical students by age, level of education before admission to medical school, race/ethnicity, parental education level, socioeconomic status, and attitudes toward public health care. METHODS: In 2001, we conducted an Internet-based survey of all students enrolled in the 16 medical schools across Canada. Based on the high response rate, first-year medical students at Canadian medical schools outside of Quebec were included in this analysis. The interactions between sex and age, years of premedical education, race/ethnicity, parental occupation, education and household income, impact of finances on choice of medical school, future specialty and practice location, attitudes toward private funding in the Canadian health care system were examined using descriptive statistics and chi2 tests. RESULTS: There were no significant differences between male and female medical students in age, level of education before admission, and race/ethnicity. Female students' fathers (p=.046) and mothers (p=.061) were more likely to hold positions of higher occupational status than were those of male students. There was no significant difference between the parental household incomes of male and female students. Male students were more likely than female students to state that financial considerations would affect their choice of specialty (p=.002) and practice location (p=.002). Male students were more likely to express a positive attitude toward private funding in the health care system, both with respect to increasing the amount of private funding (p=.007) and the addition of private paying patients (p=.002). CONCLUSION: Although women have almost reached equity with men in undergraduate medical education, female students are more likely than male students to have highly educated parents, suggesting that some barriers to access may still exist. The differences in attitudes of female and male medical students to finances and the public health care system become increasingly important as more women practice medicine. These sex differences need to be investigated further, as they could have implications for health policy.
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 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,002 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,008 | 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 ».