Doctors for the People: The History of Medical Education and the Current Role of Social Accountability
Bibliographic record
Abstract
There have been various movements in medical education in North America over the last two hundred years that have drastically changed the face of the educational experience.From a grass-roots profession with no standardization, North American medical schools now have common curricula and educational techniques, stemming primarily from the 1910 report Medical Education in the United States and Canada by Abraham Flexner.Developments since the release of the Flexner report have included organ-based block teaching and, more recently, the addition of problem-based learning to the educational process.The latest trend in medical education is the movement towards social, cultural and geographic proximity: the inclusion of social and cultural minorities (those considered underserviced by the medical community) in the student body and in the curriculum, and the placement of schools (or of the classes themselves) near to or within these underserviced communities.This movement towards social accountability, though new in application, was suggested by Flexner who suggested that it is in "[the] interest of the public […] to have well trained practitioners in sufficient number for the needs of society."It is within this movement that the roots of the Northern Ontario School of Medicine (NOSM) lie.Within this paper, we will examine aspects of the history of medical education in North America, including this latest trend and the contribution of NOSM to it.
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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 | 0.007 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.019 | 0.073 |
| Scholarly communication | 0.012 | 0.009 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.008 | 0.013 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".