A Closer Look at Regional Medical Campuses
Notice bibliographique
Résumé
To the Editor: “Are Regional Medical Campuses More Isolating for Minority Students?” was asked in a recent letter to the editor by Campbell and Rodríguez.1 Although the authors raise a thoughtful concern, we feel they are generalizing the potential for isolation at regional campuses without data to support their conclusion. Regional medical campuses (RMCs) are a diverse mix across North America. It is our perspective that RMCs are uniquely qualified to support all students, including those who traditionally have been underrepresented in medicine, and perhaps even exceed main campus outcomes in doing so. Of course, each case is different, so the outcomes depend on the specifics. Some students might be better nurtured at an RMC while others might find the main campus more accommodating. Typically, RMCs with their smaller size are more nimble than main campuses; often, RMC students are more closely connected to one another and can have closer ties to host communities. Students from RMCs commonly cite their increased clinical exposure as an advantage. Having a medical education campus is important to the communities that host RMCs, and the goodwill is often expressed through impressive systems of caring for the entire RMC family. In many ways, this is what can be attractive to underrepresented students. The University of Minnesota’s Duluth RMC is one such example. They have the enviable record of averaging 6 to 7 Native American students within a cohort of 60; in 2016 they had 11 Native American students in the entering class! In support of the Duluth RMC mission, 18% of the faculty is Native American. We have all experienced students transferring from RMCs back to the main campus, but we also know of numerous examples when students successfully moved in the opposite direction. Ultimately, RMCs come in many different shapes and sizes; there is no one-size-fits-all rule. The time is ripe to learn more about these nuances. In doing so, we think there are many treasures to be discovered. Lanita Carter, PhDDirector, Medical Education and Student Services, Huntsville Regional Campus, UAB School of Medicine, Huntsville, Alabama; [email protected]Gerry Cooper, EdDAssociate dean, Windsor Campus, Schulich School of Medicine & Dentistry, Western University, Windsor, Ontario, Canada.Alan Johns, MD, MEdAssociate dean for medical education, Duluth Regional Campus, University of Minnesota Medical School, Duluth, Minnesota.
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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 | 0,003 | 0,006 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,002 | 0,002 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,003 | 0,001 |
| Intégrité de la recherche | 0,011 | 0,027 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,032 | 0,008 |
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 ».