Settings, populations, and time: a conceptual framework for public health interventions
Bibliographic record
Abstract
This paper presents a conceptual framework displaying how combinations of settings and populations seen in a long-term perspective may guide public health and health promotion planning and research. The notion of settings constitutes a key element of health promotion as stipulated by the Ottawa Charter from 1986. The setting approach highlights the individual, social and structural dimensions of health promotion. Likewise, the notion of populations and how they are selected forms a center pillar of public health. By joining the two perspectives, four combinations of intervention strategies appear by addressing: (1) a single population segment within a single setting, (2) multiple population segments within a single setting, (3) a single population segment within multiple settings or (4) multiple population segments within multiple settings. Furthermore, the addition of a time dimension inspired by the life-course perspective illustrates how trajectories of individuals and projects change settings and population segments as time goes by. The conceptual framework displays how systematic awareness of long-term, multi-setting, multi-population trajectories allow health promotion planners and researchers to systematically develop, plan and analyze their projects.
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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 | 0.023 | 0.013 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.004 |
| Science and technology studies | 0.006 | 0.034 |
| Scholarly communication | 0.011 | 0.016 |
| Open science | 0.004 | 0.009 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 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".