“Health promotion governance”: A framework for operationalizing the Ottawa charter mechanisms in health system governance
Bibliographic record
Abstract
Abstract According to the Geneva Charter for well‐being, health is a political choice and governments have crucial roles in providing the prerequisites of health and well‐being for people in societies. To initiate the creation of sustainable well‐being in societies, the health systems of all countries must be governed by a health promotion approach. To propose a “health promotion governance framework,” we apply the concepts of good governance and the Ottawa Charter strategies/action areas to health system governance. To implement the good governance components within health systems, policymakers need to apply the three Ottawa Charter's strategies. Applying these strategies, the policymakers will be led to perform the five mechanisms through community‐based interventions for health promotion. As a result, they will achieve a health system with “health‐promoting governance.” Such a system can act so effective, efficient, equitable, and inclusive that it brings about better health outcomes. In this way, the proposed “health promotion governance framework” might be helpful in giving reality to the governance of health promotion in health systems, which is the first step in creating sustainable well‐being in societies.
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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 | 0.042 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.007 | 0.043 |
| Scholarly communication | 0.018 | 0.010 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 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".