A critical appraisal of evidence‐based medicine: some ethical considerations
Bibliographic record
Abstract
Evidence-based medicine (EBM) is a concept that has grown to dominate the medical literature over the last decade. EBM has provoked a variety of criticisms, scientific, philosophical and sociological. However, while its basic conclusion--that we should practise EBM--is ethical, there has been limited ethical analysis of EBM. This paper aims to provide an analysis of EBM from an ethical perspective and identify some of EBM's potential ethical implications. Following a description of what constitutes EBM, this paper will identify and assess some of the basic values and epistemological assumptions of EBM that provide support for the moral duty to practise EBM. It will then examine potential ethical implications that could arise from practising EBM, given the challenges that have been made of EBM's assumptions and claims to authority. This paper will conclude by arguing that practitioners could strengthen the ethics of EBM by embracing a broader definition of evidence and including ethical criteria in the critical appraisal of research studies.
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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 | 0.379 | 0.495 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.011 | 0.007 |
| Science and technology studies | 0.010 | 0.058 |
| Scholarly communication | 0.020 | 0.017 |
| Open science | 0.007 | 0.012 |
| Research integrity | 0.032 | 0.026 |
| Insufficient payload (model declined to judge) | 0.001 | 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".