Bibliographic record
Abstract
BACKGROUND: The universal goal of medical education is to train excellent physicians, able to maintain the health of individuals and communities. The route to achieving this goal has shifted over time. This paper describes the absolutes and ambiguities of philosophical vision, responsiveness to stakeholders, curriculum content and delivery, and assessment of trainees and training programs across much of the developed world. DESCRIPTION: Traditional medical education is content focused and organized by organ systems. Newer curricula, informed by current learning theories, emphasize a competencies based approach, with clinical scenarios at the centre of teaching and assessment of students. Associated with this is a shift from the in-depth knowledge of the specialist to a 'what must a generalist know' approach. These models are explored as are options for curriculum delivery, input from governments, students, the public and faculty, and methods and importance of accreditation. CONCLUSION: The goals and the process of training physicians to achieve these exhibit numerous commonalities across time and place throughout the developed world while still allowing for cultural or national adaptations. All models and content aim for minimum basic knowledge, while emphasizing communication skills, cultural awareness and professionalism amongst future physicians.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".