Effectiveness and sustainability of community-led total sanitation in Yobe State, Nigeria
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Since 2012, Action Against Hunger is working with local authorities in Yobe State, Northern Nigeria, to trigger 138 communities using the Community-Led Total Sanitation methodology. This approach aims to empower communities to realize the negative impacts of open defecation, and thus mobilize themselves to eliminate open defecation and improve sanitation with limited external intervention. In mid-2017, Action Against Hunger conducted a review of triggered communities to garner best practices and lessons learned for CLTS effectiveness and sustainability. The study found significant progress towards achieving open defecation free status among project villages. Communities demonstrated high commitment to constructing and maintaining latrines and sustaining behaviour change. Key lessons learned included: the need for gender-specific programming; the potential for improved training of local artisans and natural leaders to offer improved sanitation options; and the importance of consistent community follow-up and continued engagement with community and local leaders and stakeholders.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 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 it