Le difficile pilotage d’une réforme d’un système de santé : cas du Nouveau-Brunswick (Canada)
Bibliographic record
Abstract
INTRODUCTION: In many developed countries, reforms of public healthcare systems are ongoing but do not always achieve desired results. In this article, we present the history of the healthcare system reform in the Canadian province of New Brunswick with the objective of analyzing its difficult steering by the state, in light of the dynamics between the actors involved. METHOD: Qualitative methods were chosen. Data collection includes semi-structured interviews (N = 39) with representatives of the State, such as health ministers, and other relevant stakeholders, such as managers, citizens or health professionals. RESULTS: The stakeholders were compelled by various aspects of the reform, for example francophone health care services, that had consequences on the trajectory of change. To stay on target, the State must adapt to the dynamic interactions of the actors involved. CONCLUSION: Reforms take place over a long period of time and their programming by the State can be very difficult, as it requires the mobilization of different types of instruments at its disposal. In order to influence the behaviour of the actors concerned, the State must define a goal whose general orientations are agreed upon, succeed in forging bonds of trust and managing resistance, and finally, use standardized data in order to provide a normative framework and evaluate the progress of the reform project.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.004 |
| 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; both teacher heads 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".