Learning from health system reform trajectories in seven Canadian provinces
Bibliographic record
Abstract
In publicly funded health systems, reform efforts have proliferated to adapt to increasingly complex demands. In Canada, prior research (Lazar et al., 2013, Paradigm Freeze: Why is it so Hard to Reform Health Care in Canada?, McGill-Queen's Press) found that reforms at the end of the 20th century failed to change the fundamentals of the Canadian system based on physician independence and assured universal coverage only for medical and hospital services. This paper focuses on reforms since the turn of the millennium to explore the transformative capacities developed in seven provinces within this system architecture. Longitudinal case studies, based on scientific and grey literature, and interviews with key informants, trace the patterns of reform in each province and reveal five objectives that, to varying degrees, preoccupied reformers: (1) address chronic disease, (2) align health system actors with provincial objectives, (3) shift from hospital to community-based care, (4) integrate physicians, and (5) develop improvement capacities. The range of strategies adopted to achieve these objectives in different provinces is compared to identify emerging pathways of reform and extract lessons for future reformers. We find significant cross-learning between provinces, but also note an emergent dimension to reforms, where multiple strategies aggregate through time to create unique patterns, presenting their own set of possibilities and limitations for the future.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".