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Record W2992885016 · doi:10.2166/washdev.2019.077

Understanding empowerment in water, sanitation, and hygiene (WASH): a scoping review

2019· review· en· W2992885016 on OpenAlexaff
Florence Dery, Elijah Bisung, Sarah Dickin, Michelle Dyer

Bibliographic record

VenueJournal of Water Sanitation and Hygiene for Development · 2019
Typereview
Languageen
FieldNursing
TopicChild Nutrition and Water Access
Canadian institutionsQueen's University
FundersDepartment for International Development
KeywordsSanitationEmpowermentPsychological interventionHygienePublic relationsBusinessAccountabilityPolitical scienceEconomic growthNursingMedicineEconomics

Abstract

fetched live from OpenAlex

Abstract In low- and middle-income countries, a common component of water, sanitation, and hygiene (WASH) interventions is the goal of empowerment of beneficiaries, particularly poor households. Empowerment is viewed as an important development goal in itself, as well as a way to obtain improved WASH outcomes. However, empowerment is a complex and multi-dimensional concept, and it is often not clear how it is defined in WASH sector programming. This scoping review explores how concepts of empowerment have been used in the WASH sector and delineates relevant empowerment dimensions. Medline, Embase, and Global Health databases were searched for in the peer-reviewed literature published in English. A total of 13 studies were identified. Five major interrelated empowerment dimensions were identified: access to information, participation, capacity building, leadership and accountability, and decision-making. This review provides researchers and practitioners with a greater understanding of dimensions of empowerment that are relevant for strengthening WASH interventions, as well as tracking progress toward gender and social equality outcomes over time. This understanding can help ensure inclusive WASH service delivery to achieve gender-sensitive Sustainable Development Goal (SDG) targets for universal water and sanitation access. This article has been made Open Access thanks to the generous support of a global network of libraries as part of the Knowledge Unlatched Select initiative.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.481
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.000
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 head0.157
GPT teacher head0.376
Teacher spread0.219 · 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.

Study designSystematic review
Domainnot available
GenreReview

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

Citations70
Published2019
Admission routes1
Has abstractyes

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