[COMPETENCY BASED MEDICAL EDUCATION - A NEW PARADIGM FOR ISRAELI PHYSICIAN TRAINING].
Bibliographic record
Abstract
INTRODUCTION: During the last decades the dominant paradigm, in which the duration of a rotation/course, the required content to be learnt (the material covered) and a test (usually a multiple choice one) evaluating the knowledge of the content, were paramount, is being replaced by a new paradigm: outcome/competency based medical education (CBME, OBME). In this paper the reasons for adopting this change in the developed world are presented, its nature and basic assumptions enumerated and national examples of its adoption from Scotland, Canada, UK and USA described. We will present in some detail the changes this approach entails, the new definitions it adopts, the learning outcomes it aspires to and how to evaluate them. Finally, we will present a draft outcomes proposal adapted to the Israeli reality. Since the Medicine Deans Forum and the Scientific Council of the Israeli Medical Association have adopted the new paradigm for the training of Israeli physicians, it is an opportune moment to expose the readership of Harefuah (i.e. Israel's physicians and medical students) to this relatively new paradigm.
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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 | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.009 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".