The Organization of Decision‐making and the Dynamics of Policy Drift: A Canadian Health Sector Example
Bibliographic record
Abstract
Abstract This historical‐institutionalist case study of public–private change in the rehabilitation health sector in Ontario, Canada, seeks to build on literature about the politics of policy drift, particularly with respect to health care systems. Rather than turning to higher‐order institutional factors, such as federalism and overall financing agreements between states and the medical profession, or to economic indicators such as change in expenditures, however, it posits that the particularities of how welfare‐policy sectors are organized with respect to their decision‐making contribute to drift. Such organization is framed by two factors. The first is the set of rules by which the public–private boundary is drawn, and the second is the structuring of public institutions that set legislation and regulation, and organize the policy networks attendant on them, around these boundaries. The degree of coordination or fragmentation among these, this case suggests, is a factor in the politics and dynamics of drift.
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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 | 0.012 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.031 | 0.034 |
| Scholarly communication | 0.012 | 0.003 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".