Regionalization in Canada: A Promising Heritage to Build On
Bibliographic record
Abstract
Regionalization has been a major policy experiment in Canadian healthcare. Objectives attached to this policy were ambitious and somewhat unrealistic. Regional health authorities have shown that they can play a useful role in implementing healthcare reform. However, their legitimacy is difficult to sustain, and they need to renew their roles in order to remain a valuable asset in the improvement of healthcare delivery. A model of leadership for RHAs based on content and process dimensions is proposed to support the development of their role in improving the delivery of care. RHAs need to depart from a too distant mode of managing healthcare and support more healthcare organizations in their search for innovative ideas and organizing models and strategies. By adopting such an approach to their roles, it is expected that RHAs will further contribute to the improvement of healthcare and consequently will gain legitimacy to develop more autonomous policies with regard to broad ideals such as democratization and health improvement.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.018 | 0.007 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.018 | 0.017 |
| Insufficient payload (model declined to judge) | 0.009 | 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".