Relevance of the Flexner Report to Contemporary Medical Education in South Asia
Bibliographic record
Abstract
A century after the publication of Medical Education in the United States and Canada: A Report to the Carnegie Foundation for the Advancement of Teaching (the Flexner Report), the quality of medical education in much of Asia is threatened by weak regulation, inadequate public funding, and explosive growth of private medical schools. Competition for students' fees and an ineffectual accreditation process have resulted in questionable admission practices, stagnant curricula, antiquated learning methods, and dubious assessment practices. The authors' purpose is to explore the relevance of Flexner's observations, as detailed in his report, to contemporary medical education in South Asia, to analyze the consequences of growth, and to recommend pragmatic changes. Major drivers for growth are the supply-demand mismatch for medical school positions, weak governmental regulation, private sector participation, and corruption. The consequences are urban-centric growth, shortage of qualified faculty, commercialization of postgraduate education, untenable assessment practices, emphasis on rote learning, and inadequate clinical exposure. Recommendations include strengthening accreditation standards and processes possibly by introducing regional or national student assessment, developing defensible student assessment systems, recognizing health profession education as a field of scholarship, and creating a tiered approach to faculty development in education. The relevance of Flexner's recommendations to the current status of medical education in South Asia is striking, in terms of both the progressive nature of his thinking in 1910 and the need to improve medical education in Asia today. In a highly connected world, the improvement of Asian medical education will have a global impact.
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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 | 0.009 | 0.030 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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".