Bibliographic record
Abstract
CONTEXT: Medical education research has been an academic pursuit for over 50 years, tracing its roots back to the Office of Medical Education at the State University of New York at Buffalo, New York, with George Miller. As the field has matured, the nature of the questions posed and the disciplinary bases of its practitioners have evolved. METHODS: I identify three chronological 'generations' of academics who have contributed to the field, at intervals of roughly 10-15 years. RESULTS: Members of the first generation came from diverse and unrelated academic backgrounds and essentially learned their craft on the job. A second generation, emerging in the 1980s and 1990s, consisted of individuals with PhD-level training in relevant fields such as psychology, psychometrics and sociology, who actively chose a career in health sciences education, often during graduate work. These individuals brought a strong disciplinary orientation to their research. Finally, the proliferation of graduate programmes in medical education means that we are now seeing the evolution of a new type of academic, often a health professional, whose only discipline is medical education. CONCLUSIONS: I propose that we should strike a balance between seeking to create a separate specialty of medical education and continuing to actively recruit from other academic disciplines. I believe that the strong disciplinary roots of these individuals are a critical element in the continuing growth and progress of medical education research.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 | 0.045 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".