How can the functioning and effectiveness of networks in the settings approach of health promotion be understood, achieved and researched?
Bibliographic record
Abstract
Networks in health promotion (HP) have, after the launch of WHO's Ottawa Charter [(World Health Organization (WHO) (eds). (1986) Ottawa Charter on Health Promotion. Towards A New Public Health. World Health Organization, Geneva], become a widespread tool to disseminate HP especially in conjunction with the settings approach. Despite their allegedly high importance for HP practice and more than two decades of experiences with networking so far, a sound theoretical basis to support effective planning, formation, coordination and strategy development for networks in the settings approach of HP (HPSN) is still widely missing. Brößkamp-Stone's multi-facetted interorganizational network assessment framework (2004) provides a starting point but falls short of specifying the outcomes that can be reasonably expected from the specific network type of HPSN, and the specific processes/strategies and structures that are needed to achieve them. Based on outcome models in HP, on social, managerial and health science theories of networks, settings and organizations, a sociological systems theory approach and the capacity approach in HP, this article points out why existing approaches to studying networks are insufficient for HPSN, what can be understood by their functioning and effectiveness, what preconditions there are for HPSN effectiveness and how an HPSN functioning and effectiveness framework proposed on these grounds can be used for researching networks in practice, drawing on experiences from the ‘Project on an Internationally Comparative Evaluation Study of the International Network of Health Promoting Hospitals and Health Services’ (PRICES-HPH), which was coordinated by the WHO Collaborating Centre for Health Promotion in Hospitals and Health Services (Vienna WHO-CC) from 2008 to 2012.
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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 | 0.010 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".