Rebalancing health systems toward community-based care: The role of subsectoral politics
Bibliographic record
Abstract
There has been increased policy discourse urging a "rebalancing" of health systems from institutionally-based to community-based approaches. This paper offers an analysis of the subsectoral dynamics that condition opportunities to strengthen community-based care relative to acute care. We report on the results of a policy study in Ontario, Canada that explored factors impacting on the capacity to expand community-based care. In so doing, we highlight the challenges associated with the community subsector's ability to develop 'critical' status and challenge the dominance of the acute subsector. We conclude that attempts to rebalance health systems toward community-based care should begin by understanding that health care is not a monolithic policy sector, but rather a collection of proximate policy sub-sectors, inclusive of community care, acute care, and institutional care, each with their own internal characteristics and dynamics that impact sectoral directions.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".