Community Power–Building Groups And Public Health NGOs: Reimagining Public Health Advocacy
Bibliographic record
Abstract
Public health frameworks have grappled with the inequitable distribution of power as a driver of the social conditions that determine health. However, these frameworks have not adequately considered building community power as a strategy to shift the distribution of power. Community power-building organizations build and organize a base of affected people to take collective action to transform their material conditions, using advocacy and other tactics. We conducted qualitative interviews with representatives of twenty-two national nongovernmental public health organizations (public health NGOs) and thirteen community power-building organizations to explore the nature and potential of partnerships between public health and community power-building organizations. Our findings suggest ways to close advocacy gaps within the public health ecosystem and ways in which public health can strategically leverage its power, resources, and expertise to support social justice campaigns and movements.
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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 | 0.072 | 0.048 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.030 | 0.066 |
| Scholarly communication | 0.018 | 0.025 |
| Open science | 0.003 | 0.030 |
| Research integrity | 0.009 | 0.011 |
| Insufficient payload (model declined to judge) | 0.007 | 0.000 |
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".