Medical Doctors in Health Reforms
Bibliographic record
Abstract
Medical doctors play a crucial role in the allocation and use of resources in health care systems. They shape capacities to renew policy orientations and innovate models of care. However, little attention has been paid to their specific role in health reforms. This book explores this aspect by looking at the role of the medical profession in health reforms in two mature welfare states with publicly-funded healthcare systems (PFHS): Canada and England. Specifically, the book investigates the multifaceted and paradoxical situation where a dominant profession – medicine – faces increasing pressures to become an active player and an ally in major policy efforts and system-wide reforms driven by governments. The conceptual underpinning of this work builds on the contribution of various areas of studies, namely the sociology of professions, studies on professions and organisations and law. The analysis investigates reformative processes from the inception of both PFHS and identifies the role of the medical profession in policy formulation. The focus is predominantly on the role of organised medicine (unions, professional associations and colleges) with their political struggles to promote and advance medical values and interests in a context where governments aim to transform health care systems. Empirically, the book builds on a socio-historical and institutional narrative of health care reforms and on the role played by the medical profession in both countries. The book offers insights into the government's ability to drive change in the health care system and to engage medical doctors as partners in health reforms.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.014 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.013 | 0.003 |
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".