Chronic Disease Prevention and the Politics of Scale: Lessons from Canadian Health Reform
Bibliographic record
Abstract
The authors examine the politics of health-promotion dissemination in health policy using provincial cases from the Canadian Heart Health Initiative (CHHI)-Dissemination Phase, a nationwide chronic disease prevention initiative that took place between 1994 and 2005. Drawing on an analysis of health policy documents and key informant interviews from three provincial CHHI projects, the authors highlight the challenges to incorporate health-promotion strategies oriented toward collective approaches to health within variably "individual" oriented policy climates during a time of health reform. In doing this, the authors uncover a "politics of scale" where researchers developed very different strategies to advance chronic disease prevention within a contested political terrain. What emerged were strategies unique to provincial context. Understanding the politics of scale within health policy development provides insight into how health-promotion strategies should be shaped to achieve maximum effect.
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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 | 0.014 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.035 | 0.039 |
| Scholarly communication | 0.016 | 0.005 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.005 | 0.006 |
| 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".