Shared Medical Regulation in a Time of Increasing Calls for Accountability and Transparency
Bibliographic record
Abstract
In the United States, Canada, and the United Kingdom, the medical profession is accountable to the public for the delivery and quality of care provided to patients. Traditionally, this accountability has been achieved through the development and maintenance of professional standards established by the profession itself-self-regulation. Medical self-regulation is being re-examined by regulators, government, and the profession in response to a range of drivers including payers seeking ways to hold physicians accountable for cost-effective care; patients seeking more information about their physician's qualifications; and the emergence of a number of high-profile cases of unacceptable medical practice. This article outlines the current state of medical regulation in the United States, Canada, and the United Kingdom and highlights the increasing external pressure on the self-regulatory framework that is leading to a shift toward shared regulation between the profession and other stakeholders.
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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 | 0.099 | 0.121 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.020 | 0.070 |
| Scholarly communication | 0.024 | 0.021 |
| Open science | 0.004 | 0.026 |
| Research integrity | 0.024 | 0.048 |
| Insufficient payload (model declined to judge) | 0.004 | 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".