The future of medical education: a Canadian environmental scan
Bibliographic record
Abstract
OBJECTIVES: One hundred years after the Flexner report remade medical education in North America, many countries are reviewing the purpose and organisation of medical education. In Canada, a national study is being undertaken to define important issues and challenges for the future of medical education. The objectives of this paper are to describe the process of conducting an empirical environmental scan at a national level, and to present the research findings of this scan. METHODS: Thirty national key informant interviews were conducted, transcribed and coded to identify key themes. Interview data were triangulated with data sourced from 34 commissioned literature reviews and a series of national focus groups. RESULTS: Ten key issues or priorities were identified and used to generate detailed review papers used by the Association of Faculties of Medicine of Canada to create a blueprint for the evolution of medical education. The new priorities have major implications for areas ranging from admissions, curriculum content, educational process and the need to articulate the purpose and responsibilities of medical schools in society. DISCUSSION: This research provides a case study of how an empirical research approach can be used to identify and validate priorities for changes in medical education at a national level. This approach may be of interest in other countries.
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How this classification was reachedexpand
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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".