Canada’s New Medical School: The Northern Ontario School of Medicine: Social Accountability Through Distributed Community Engaged Learning
Bibliographic record
Abstract
Like many rural regions around the world, Northern Ontario has a chronic shortage of doctors. Recognizing that medical graduates who have grown up in a rural area are more likely to practice in the rural setting, the Government of Ontario, Canada, decided in 2001 to establish a new medical school in the region with a social accountability mandate to contribute to improving the health of the people and communities of Northern Ontario. The Northern Ontario School of Medicine (NOSM) is a joint initiative of Laurentian University and Lakehead University, which are located 700 miles apart. This paper outlines the development and implementation of NOSM, Canada's first new medical school in more than 30 years. NOSM is a rural distributed community-based medical school which actively seeks to recruit students into its MD program who come from Northern Ontario or from similar northern, rural, remote, Aboriginal, Francophone backgrounds. The holistic, cohesive curriculum for the MD program relies heavily on electronic communications to support distributed community engaged learning. In the classroom and in clinical settings, students explore cases from the perspective of physicians in Northern Ontario. Clinical education takes place in a wide range of community and health service settings, so that the students experience the diversity of communities and cultures in Northern Ontario. NOSM graduates will be skilled physicians ready and able to undertake postgraduate training anywhere, but with a special affinity for and comfort with pursuing postgraduate training and clinical practice in Northern 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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.007 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.030 | 0.004 |
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".