Medical Education in the United States and Canada, 2010
Bibliographic record
Abstract
The authors present an overview of the educational programs, infrastructure to support them, and the assessment strategies of 128 medical schools in the United States and Canada, based on reports submitted by those schools and published in this supplement to Academic Medicine. The authors explore many important changes that have occurred since the publication of the Flexner Report in 1910 as well as the progress that is evident since a similar collection of medical school reports was published in September 2000, also as a supplement to Academic Medicine. Drawing on the reports, the authors summarize, among other topics, the advances that have taken place in the support for faculty, the funding of medical student education, changes in pedagogy and assessment, and the expansion of medical education to distributed models and regional campuses.The authors observe that the reports from the 128 schools illustrate that medical student education has undergone and continues to undergo substantive change, has advanced markedly since the reforms stimulated by the Flexner Report, and has continued to evolve during the past decade. The reports illustrate the strength of support for the educational programs, even in a time of financial constraints, and the increasing recognition of the scholarly contributions of faculty through teaching. The authors provide examples of the changes in pedagogy and new topics in the required curriculum in the past decade and describe selected highlights of the 128 educational programs.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".