Bibliographic record
Abstract
This paper starts by briefly reviewing the history, theory and practice of the settings approach to promoting public health—highlighting its ecological perspective, its under-standing of settings as dynamic open systems and its prim-ary focus on whole system organization development and change. It goes on to outline perceived benefits and consider why, almost 20 years after the Ottawa Charter advocated the approach, there remains a relatively poorly developed evidence base of effectiveness. Identifying three key challenges—relating to the construction of the evidence base for health promotion, the diversity of conceptual understandings and real-life practice and the complexity of evaluating ecological whole system approaches—it suggests that these have resulted in an ongoing tendency to evaluate only discrete projects in settings, thus failing to capture the ‘added value ’ of whole system working. It concludes by exploring the potential value of theory-based evaluation and identifying key issues that will need to be addressed in moving forward—funding evalu-ation within and across settings; ensuring links between evi-dence, policy and practice; and clarifying and articulating the theories that underpin the settings approach generically and inform the approach as applied within particular settings. Key words: ecology; evaluation; evidence; organization development; settings; systems
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.543 | 0.313 |
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".