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Record W4386704059 · doi:10.1080/17441692.2023.2256831

Attention to the needs of women and girls in WASH: An analysis of WASH policies in selected sub-Saharan African countries

2023· article· en· W4386704059 on OpenAlexaff
Maurice Anfaara Dogoli, Abraham Marshall Nunbogu, Susan J. Elliott

Bibliographic record

VenueGlobal Public Health · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicSex work and related issues
Canadian institutionsUniversity of Waterloo
FundersMinistry of Water Resources
KeywordsEmbeddednessContext (archaeology)Gender analysisSummative assessmentEconomic growthGender equalitySociologyDeveloping countryPoison controlGender studiesPolitical scienceMedicineEnvironmental healthSocial scienceGeographyFormative assessmentEconomicsPedagogy

Abstract

fetched live from OpenAlex

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.

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.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.203
Threshold uncertainty score0.966

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.016
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.023
GPT teacher head0.332
Teacher spread0.309 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations12
Published2023
Admission routes1
Has abstractyes

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