Community cost-benefit discussions that launched the Camino Verde intervention in Nicaragua
Bibliographic record
Abstract
BACKGROUND: Recent literature on community intervention research stresses system change as a condition for durable impact. This involves highly participatory social processes leading to behavioural change. METHODS: Before launching the intervention in the Nicaraguan arm of Camino Verde, a cluster-randomised controlled trial to show that pesticide-free community mobilisation adds effectiveness to conventional dengue controls, we held structured discussions with leaders of intervention communities on costs of dengue illness and dengue control measures taken by both government and households. These discussions were the first step in an effort at Socialising Evidence for Participatory Action (SEPA), a community mobilisation method used successfully in other contexts. Theoretical grounding came from community psychology and behavioural economics. RESULTS: The leaders expressed surprise at how large and unexpected an economic burden dengue places on households. They also acknowledged that large investments of household and government resources to combat dengue have not had the expected results. Many were not ready to see community preventive measures as a substitute for chemical controls but all the leaders approved the formation of "brigades" to promote chemical-free household control efforts in their own communities. CONCLUSIONS: Discussions centred on household budget decisions provide a good entry point for researchers to engage with communities, especially when the evidence showed that current expenditures were providing a poor return. People became motivated not only to search for ways to reduce their costs but also to question the current response to the problem in question. This in turn helped create conditions favourable to community mobilisation for change. TRIAL REGISTRATION: ISRCTN27581154 .
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 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".