MétaCan
Menu
Retour à la cohorte
Enregistrement W2158541802

Characteristics of first-year students in Canadian medical schools.

2002· article· en· W2158541802 sur OpenAlexafffundabout
Irfan A. Dhalla, Jeff Kwong, David L. Streiner, Ralph E. Baddour, Andrea Waddell, Ian L. Johnson

Notice bibliographique

RevuePubMed · 2002
Typearticle
Langueen
DomaineMedicine
ThématiqueMedical Education and Admissions
Établissements canadiensUniversity of Toronto
Organismes subventionnairesMemorial University of NewfoundlandUniversity of British ColumbiaOntario Medical AssociationCanadian Medical AssociationMcMaster UniversityQueen's UniversityAlberta Medical AssociationUniversity of TorontoDalhousie UniversityUniversity of Ottawa
Mots-clésSocioeconomic statusDisadvantagedCensusEthnic groupDemographyPopulationGraduation (instrument)Proxy (statistics)MedicineImmigrationFamily medicinePsychologyGeographySociologyPolitical science
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

BACKGROUND: The demographic and socioeconomic profile of medical school classes has implications for where people choose to practise and whether they choose to treat certain disadvantaged groups. We aimed to describe the demographic and socioeconomic characteristics of first-year Canadian medical students and compare them with those of the Canadian population to determine whether there are groups that are over- or underrepresented. Furthermore, we wished to test the hypothesis that medical students often come from privileged socioeconomic backgrounds. METHODS: As part of a larger Internet survey of all students at Canadian medical schools outside Quebec, conducted in January and February 2001, first-year students were asked to give their age, sex, self-described ethnic background using Statistics Canada census descriptions and educational background. Postal code at the time of high school graduation served as a proxy for socioeconomic status. Respondents were also asked for estimates of parental income and education. Responses were compared when possible with Canadian age-group-matched data from the 1996 census. RESULTS: Responses were obtained from 981 (80.2%) of 1223 first-year medical students. There were similar numbers of male and female students (51.1% female), with 65% aged 20 to 24 years. Although there were more people from visible minorities in medical school than in the Canadian population (32.4% v. 20.0%) (p < 0.001), certain minority groups (black and Aboriginal) were underrepresented, and others (Chinese, South Asian) were overrepresented. Medical students were less likely than the Canadian population to come from rural areas (10.8% v. 22.4%) (p< 0.001) and were more likely to have higher socioeconomic status, as measured by parents' education (39.0% of fathers and 19.4% of mothers had a master's or doctoral degree, as compared with 6.6% and 3.0% respectively of the Canadian population aged 45 to 64), parents' occupation (69.3% of fathers and 48.7% of mothers were professionals or high-level managers, as compared with 12.0% of Canadians) and household income (15.4% of parents had annual household incomes less than $40,000, as compared with 39.7% of Canadian households; 17.0% of parents had household incomes greater than $160,000, as compared with 2.7% of Canadian households with an income greater than $150,000). Almost half (43.5%) of the medical students came from neighbourhoods with median family incomes in the top quintile (p < 0.001). A total of 57.7% of the respondents had completed 4 years or less of postsecondary studies before medical school, and 29.3% had completed 6 or more years. The parents of the medical students tended to have occupations with higher social standing than did working adult Canadians; a total of 15.6% of the respondents had a physician parent. INTERPRETATION: Canadian medical students differ significantly from the general population, particularly with regard to ethnic background and socioeconomic status.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,003
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,104
Score d'incertitude au seuil0,209

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,003
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,001
Bibliométrie0,0020,004
Études des sciences et des technologies0,0030,001
Communication savante0,0010,000
Science ouverte0,0010,001
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0050,001

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.

Tête enseignante Opus0,030
Tête enseignante GPT0,292
Écart entre enseignants0,262 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations158
Publié2002
Routes d'admission3
Résumé présentoui

Explorer davantage

Même revuePubMedMême sujetMedical Education and AdmissionsTravaux en français237 207