Notice bibliographique
Résumé
Context and setting A Canadian province, 4 times the size of the UK, has only 1 medical school. The northern and rural areas of the province are underserved medically, with difficulties in doctor recruitment and retention. In 2004, the medical school opened a northern campus for undergraduate medical education in partnership with a northern university. The programme's mission is to admit and train future doctors who are more likely to locate their clinical practice in northern and rural settings, requiring changes to the admissions process. Why the idea was necessary The standard admissions process for the main school is based 50% on cognitive and 50% on non-cognitive criteria, but no assessment is made on the student's background. Other schools have looked at geographical origin, race or the results of personality testing. However, we found no existing admissions process to meet the needs of this programme, namely to admit students who fit well in a northern programme site. What was done The partners developed an admissions tool, the Rural and Remote Suitability Score (RRSS) to evaluate applicants' suitability for education in the north. Predictors of eventual rural or northern practice location were developed by a literature review and focus groups, resulting in the development of admission criteria and a marking scheme. The instrument was piloted with northern students currently studying medicine, students in urban settings, and postgraduate trainees who had chosen a northern site for further training. Only 1 question was added to the admissions form, which already included an autobiographical essay and documentation of non-academic activities. Using this submitted material, the tool develops a score in 3 domains (northern background or experience, self-reliance, and recreational preferences) to develop an overall RRSS score out of 100. For example, experience of working in a rural community, participation in typical, rural outdoor activities such as fishing and hunting, and travelling independently or working in jobs requiring independent decision making would all score specific points in the RRSS score. The instrument was used to score applications in 2004 (n = 1308); interrater reliability alpha was 0·90, and RRSS scores were used in admissions decisions to the northern programme. Evaluation of results and impact Review of the applicant RRSS scores ensured an adequate pool of potential candidates for interview for the northern programme. Weighted use of the RRSS score in admissions decisions ensured that selected applicants were likely to fit well into this educational environment. In comparison to grade point average, interview scores and other admission criteria, the RRSS was the single significant predictor of the applicant's first choice of education location. All but 1 student selected for the northern programme had placed the northern programme in the top 2 out of 3 possible options. Most importantly, 25 students are happily studying on a northern campus, embraced by a community that feels they are the ‘right’ students for their site and programme.
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 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 | 0,002 | 0,013 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,031 | 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; les deux têtes enseignantes s’accordent sur ce qui est montré ici.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».