Community engagement in public health: rethinking training-based initiatives for prevention and promotion
Bibliographic record
Abstract
Community training in health prevention and promotion is widespread. However, training of community members in public health often takes on limiting roles, reducing the potential and the effectiveness of their interventions. This commentary critically examines the current landscape of training-based public health initiatives, highlighting the dominant forms and methods used to improve community health. We discuss issues and limitations of (para)professionalization, utilitarian approaches to community involvement, underemphasis on cultural and social factors, overreliance on behavioral change models, limited engagement of the broader community, and the implementation of narrow, fragmented actions. We argue for a stronger shift toward more supportive community-centered models and methods in line with the ideals of the new public health. By rethinking training and capacity-building initiatives in public health, we advocate for approaches that foster collective empowerment, sustained participation, and more meaningful health outcomes, with public health taking a step back to accompany communities rather than directing them.
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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 | 0.056 | 0.068 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.009 | 0.051 |
| Scholarly communication | 0.016 | 0.020 |
| Open science | 0.008 | 0.018 |
| Research integrity | 0.021 | 0.035 |
| 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".