First Nation and Medical Student Perspectives on the Participation in Culturally Immersive Learning Experiences During Medical Training
Bibliographic record
Abstract
ABSTRACTImmersive cultural learning placements in First Nations communities allow medical students to develop a first-person perspective and a deeper understanding of the determinants of Indigenous health. Complementary student and community viewpoints on a medical student placement at Mattagami 71 reserve, a First Nations community in Northern Ontario, are presented in this commentary. RÉSUMÉLes placements d’apprentissage culturel par immersion dans les communautés des Premières Nations permettent aux étudiants en médecine de développer une perspective personnelle et une compréhension approfondie des déterminants de la santé chez les personnes autochtones. Ce commentaire présente les points de vue complémentaires d’une étudiante et d’un membre de la communauté sur un placement étudiant à la réserve Mattagami 71, une communauté des Premières Nations dans le nord de l’Ontario.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.008 | 0.007 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".