CIOMS' Placebo Rule and the Promotion of Negligent Medical Practice
Bibliographic record
Abstract
Guideline 11 of the 2002 version of the Council of International Organizations of Medical Sciences' International Ethical Guidelines for Biomedical Research Involving Human Subjects supports the use of placebo controls in clinical trials even when an established effective intervention exist. A note of clarification added to the new World Medical Association's Declaration of Helsinki goes in the same direction, even though this note clearly contradicts other provisions in the Declaration. The article highlights how this approach to placebo controlled trials constitutes an endorsement of the violation of well-established legal obligations, related to the primacy of the human subject and physicians' duty of care. The authors analyse the legal standards of four national jurisdictions to support this view. The CIOMS rule thus exposes researchers, research ethics committees and institutions to legal liability under national law. Surprisingly, nothing in the CIOMS guideline gives any indication of legal duties of researchers under national law. The authors call for an explicit recognition by CIOMS and the World Medical Association of the binding nature of national law. They invite national regulatory agencies and other legal scholars to clarify the legal standards in their jurisdiction and to improve awareness of the existence of legal obligations in the context of research.
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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 | 0.210 | 0.366 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.007 | 0.040 |
| Scholarly communication | 0.012 | 0.011 |
| Open science | 0.006 | 0.010 |
| Research integrity | 0.079 | 0.036 |
| Insufficient payload (model declined to judge) | 0.004 | 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; 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".