Rethinking professional governanceInternational directions in healthcare
Bibliographic record
Abstract
This book opens up new perspectives in the health policy debate, examining the emerging international trends in the governance of health professions and the significance of national contexts for the changing health workforce. In bringing together research from a wide range of continental European countries as well as the United Kingdom, Canada and Australia, the chapters highlight different arenas of governance, as well as the various players involved in the policy process. They expand the public debate on professional governance — hitherto mainly limited to medical self-regulation — to encompass a broad span of health care providers, from nurses and midwives to alternative therapists and health support workers. The book provides new data and geopolitical perspectives in the debate over how to govern health care. It helps to better understand both the enabling conditions for, and the barriers to, making professionals more accountable to the interests of a changing public.
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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 | 0.007 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.027 |
| Scholarly communication | 0.018 | 0.017 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.005 | 0.009 |
| Insufficient payload (model declined to judge) | 0.006 | 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".