Reconstructing a lost tradition: the philosophy of medical education in an age of reform
Bibliographic record
Abstract
CONTEXT: At the 100th anniversary of Abraham Flexner's landmark report on medical education, critical reassessment of the direction of medical education reform evinced valuable interdisciplinary contributions from biomedicine, sociology, psychology and education theory. However, to date, philosophy has been absent from the discussion despite its long standing contribution to studies on education in other professions. METHODS: This discussion paper examines how the philosophical tradition can contribute to scholarship in medical education. It begins with an explanation of the scholarly tradition of philosophy of education and its role in thinking in education more generally. It then makes links between this tradition and the context of medical education in the Flexner era of education reform. The paper then argues that this tradition is necessary to the understanding of medical education reform post-Flexner and that doctors must benefit from an education derived from this tradition in order to be able to carry out their work. DISCUSSION: These foundations are characterised as a hidden, but always present, tradition in medical education. Two ways in which this 'lost tradition' can inform medical education theory and practice are identified: firstly, by the establishment of a public canon of medical education texts that express such a tradition, and, secondly, by the incorporation of a variety of 'signature pedagogies' exemplary of liberal education.
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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 | 0.020 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.009 | 0.094 |
| Scholarly communication | 0.011 | 0.016 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.005 | 0.014 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".