Looking for Rules in a World of Exceptions: reflections on evidence-based practice
Bibliographic record
Abstract
After more than a decade, evidence-based medicine (EBM) is well established as an important influence in health care. EBM has engendered a wide range of responses from near-evangelical fervor to angered rejection, with supporters convinced of its scientific superiority and detractors of its needless reductionism. EBM is not a philosophical doctrine, and its originators and proponents have, for the most part, ignored critics and foresworn theorizing. However, EBM claims to be a normative guide to being a better physician. The theoretical, practical, and philosophical dimensions of EBM are intimately intertwined. This essay is a sustained reflection on the issues raised by EBM as experienced by a clinician/teacher who has tried to apply the tenets of EBM in clinical care and teaching over the past decade, and who has sought to expand the borders of EBM from a philosophical point of view.
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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 | 0.209 | 0.281 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.022 | 0.151 |
| Scholarly communication | 0.043 | 0.056 |
| Open science | 0.010 | 0.023 |
| Research integrity | 0.046 | 0.086 |
| Insufficient payload (model declined to judge) | 0.003 | 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".