Participation as a Core Principle of Community Health Promotion: General Account and Examples
Bibliographic record
Abstract
One of the key principles of the Ottawa Charta is participation. Community health interventions should involve the community, i.e., residents and local actors. In Hamburg, we tried to put this principle into practice during a project initiated by the municipal health service in a disadvantaged quarter with about 3000 inhabitants. The contribution starts with an account of the meaning of participation in health promotion (1) and gives an overview of participation methods in general (2). The next part contains a short account of our project (3). Five examples are presented in part four: a survey with key actors and two approaches to listening to residents’ perceptions of capacity building in the neighborhood. Another survey of residents was meant to explore the use of health promotion offers and the preparedness to get involved. The last example is the round table of local actors as a sort of steering committee for health promotion interventions (4). Key findings of the examples are: Surveys do result in valuable information for the local actors. The expressed willingness to participate is larger than the actual participation. Opportunities to participate (in surveys and at the round table) are welcome by local actors. In the last section we discuss the advantages, problems and some illusions concerning participation in health promotion (5).
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.010 | 0.005 |
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".