Attention to the needs of women and girls in WASH: An analysis of WASH policies in selected sub-Saharan African countries
Bibliographic record
Abstract
There has been a push for understanding gendered violence in WASH in recent times. Attention is therefore shifting to how these issues are conceptualised, considering their embeddedness in context. One step primarily is to understand how existing policies in WASH acknowledge the needs of women and girls in WASH. In doing this, we conducted a summative content analysis of selected policy documents on WASH: five at the international level and five each from Ghana, Uganda and Kenya. Findings suggest that existing policies inadequately acknowledge WASH related gender-based violence and pay little attention to the complex ways gender and WASH relations are intimately connected. Generally, a holistic policy approach for addressing gender-based violence in WASH is needed. The paper recommends a system policy approach to address the unique needs of women and girls in WASH in sub-Saharan Africa.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.016 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".