The Northern Ontario School of Medicine: Responding to the Needs of the People and Communities of Northern Ontario
Bibliographic record
Abstract
INTRODUCTION: Northern Ontario, like many rural and remote regions around the world, has a chronic shortage of health professionals. Recognizing that medical graduates who have grown up in rural areas are more likely to practice in rural settings, the Government of Ontario, Canada established a new medical school with a social accountability mandate to contribute to improving the health of the peoples and communities of Northern Ontario. BACKGROUND: The Northern Ontario School of Medicine (NOSM) is a joint initiative of Laurentian University in Sudbury and Lakehead University in Thunder Bay, cities one thousand kilometers apart. The NOSM model of medical education is built on several recent educational developments including rural-based medical education, social accountability of medical education and electronic distance education. This paper describes these developments as background to presenting the Northern Ontario School of Medicine as a socially accountable, geographically distributed rural-based medical school. NOSM MD PROGRAM: The school actively seeks to recruit students for the MD program from Northern Ontario or similar northern, rural, remote, Aboriginal, and Francophone backgrounds. The holistic, cohesive curriculum is grounded in Northern Ontario and relies heavily on broadband electronic communications to support distributed, community engaged learning. Students, both in classroom and clinical settings, explore cases as if they were physicians in Northern Ontario communities. Clinical education takes place in a wide range of community and health service settings so that students can experience the diversity of communities and cultures in Northern Ontario. CONCLUSION: Although NOSM is still in the early stages of development, there are encouraging signs that the school's evidence-based model of medical education will be successful in developing a sustainable, community responsive health workforce for 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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.017 | 0.005 |
| Scholarly communication | 0.006 | 0.001 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.026 | 0.003 |
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".