The practice of community development approaches in heart health promotion
Bibliographic record
Abstract
There has been a recent shift in public health policy towards population-based approaches to the reduction of cardiovascular disease. This shift has been accompanied by a re-examination of strategies appropriate to the goal. Often, community development approaches, designed to affect socio-environmental change, are suggested as the most appropriate strategy for affecting community-wide change. Despite the fact that community development approaches have been used by several of the major community-based heart health initiatives, evidence of their use and usefulness remains sparse. This paper presents the findings of a qualitative study of the factors (i.e. community context, facilitators, barriers) affecting the use of community development approaches to heart health promotion in Ontario, Canada. Key informant interviews (n = 30) were conducted with stake-holders representing voluntary agencies, community health providers, boards of education and local coalitions in eight of the 42 health unit areas across Ontario. The qualitative analysis reveals (1) that the use of comprehensive community development approaches is limited and (2) that community agencies typically employ elements of community development approaches (e.g. community organization, community-based), often in combination and adapted to suit local conditions. The resulting landscape of community development approaches is characterized by a continuum of collaborative practices indicating that no one type of community approach is appropriate for all initiatives and in all communities. Therefore, from a programmatic perspective, it may not be realistic to advocate community development as the goal to which all communities should strive.
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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 | 0.159 | 0.125 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.018 | 0.060 |
| Scholarly communication | 0.014 | 0.008 |
| Open science | 0.005 | 0.024 |
| Research integrity | 0.005 | 0.008 |
| 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".