Reducing Open Defecation Through Community-Led Total Sanitation in Fort Dauphin, Madagascar: A Case Study
Bibliographic record
Abstract
Globally, an estimated 4.5 billion people lack safe water and sanitation services. In Madagascar, open defecation is particularly commonplace, with nearly half of the population practicing it. Construction of latrines alone is ofen insufcient in reducing this number, as availability does not mean the latrines will be used by the community. Community-Led Total Sanitation (CLTS) is an approach which aims to reduce the prevalence of open defecation by catalyzing community action towards increasing use of latrines and other personal hygiene behaviors. Tis case study evaluates the hybridCLTS approach implemented by SEED Madagascar in Fort Dauphin, Madagascar, between 2014 and 2017. Specifcally, the intervention’s impact on sanitation and hygiene behavior outcomes, and health outcomes are investigated. Te report concludes that this intervention is a successful example of adapting a CLTS approach to an urban context where open defecation practices are driven by a complex set of traditional and cultural beliefs. However, signifcant challenges must be overcome to support such an approach, including ensuring adequate stakeholder engagement, sustainable fnancing, and broader Water Sanitation and Hygiene (WASH) strategies. Recommendations include fostering partnerships with other organizations, integrating participatory planning approaches, and promoting sustainable sanitation entrepreneurship.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".