Community engagement: A central feature of NOSM’s socially accountable distributed medical education
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Northern Ontario School of Medicine (NOSM) serves as the Faculty of Medicine of Lakehead and Laurentian Universities, and views the entire geography of Northern Ontario as its campus. This paper explores how community engagement contributes to achieving social accountability in over 90 sites through NOSM's distinctive model, Distributed Community Engaged Learning (DCEL). METHODS: Studies involving qualitative and quantitative methods contribute to this paper, which draws on administrative data from NOSM and external sources, as well as surveys and interviews of students, graduates and other informants including the joint NOSM-CRaNHR (Centre for Rural and Northern Health Research) tracking and impact studies. RESULTS: Community engagement contributes throughout the lifecycle stages of preadmission, admission, and undergraduate medical education. High school students from 70 Northern Ontario communities participate in NOSM's week-long Health Sciences Summer Camps. The MD admissions process involves approximately 128 volunteers assessing written applications and over 100 volunteer interviewers. Thirty-six Indigenous communities host first year students and third-year students learn their core clinical medicine in 15 communities, throughout Northern Ontario. In general, learners and communities report net benefits from participation in NOSM programs. CONCLUSION: Community engagement makes a key contribution to the success of NOSM's socially accountable distributed medical education.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.034 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.005 |
| Insufficient payload (model declined to judge) | 0.091 | 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 it