Developing Cross Sectoral, Healthy Public Policies: A Case Study of the Reduction of Highly Toxic Pesticide Use among Small Farmers in Ecuador
Bibliographic record
Abstract
Agricultural development is a health determinant for small-scale farmers. This article examines the process of developing health and agricultural policy at the municipal level. Operational research was conducted in three rural, Andean municipalities in Ecuador. Policy development involved four steps: 1) proposal of a political agenda, 2) political analysis, 3) consultation, and 4) design and implementation of a political strategy. Our study of stage 2 included in-depth interviews with institutional and community leaders in each municipality. We also reviewed secondary sources and took field notes of observations made during the process. Content analysis was used for textual materials. We observed that institutional actors used a functionalist logic with respect to agricultural production processes; this – along with their individual attitudes and aptititudes – limited progress in policy development. On the other hand, social participation tended to facilitate the development of intersectoral programs. The promotion of cross-sectoral policy development fosters cross-sectoral approaches to action on the social determinants of health.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".