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Record W2102003061 · doi:10.2166/wp.2005.0013

Sustainable community water: managing supply systems in the mid-hills of Nepal

2005· article· en· W2102003061 on OpenAlexaff
B.S. Bhandari, Miriam Grant, Dipendra Pokharel

Bibliographic record

VenueWater Policy · 2005
Typearticle
Languageen
FieldNursing
TopicChild Nutrition and Water Access
Canadian institutionsUniversity of ReginaUniversity of Calgary
FundersInternational Centre for Integrated Mountain Development
KeywordsSustainabilityLivelihoodGovernment (linguistics)Work (physics)BusinessWater supplyEconomic growthEnvironmental planningEnvironmental resource managementAgricultureGeographyEconomicsEngineeringEnvironmental engineering

Abstract

fetched live from OpenAlex

This study examines the sustainability of rural drinking water supply (DWS) projects installed by non government organizations (NGOs), international non government organizations (INGOs) and government organizations (GOs) in two districts in the mid-hill region of Nepal. Comparative analyses of different systems installed by NGOs, INGOs and GOs, which portray the work and improvements needed for sustainability, are determined. This study shows that INGO installed projects are moving forward to sustainability in terms of performance compared to NGOs and GOs. One of the prime reasons of failure to maintain sustainability is poor involvement of women from the projects' early stages. A systematic random household survey was conducted of selected projects in the study area and this showed that most of the rural DWS projects need to improve management practices and gender equality during planning as well as operation and maintenance phases. Rural people are satisfied with DWS project water availability in their communities. Results indicate that water accessibility fails to have significant impacts on rural livelihood especially for the rural poor.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.001
Scholarly communication0.0030.002
Open science0.0010.002
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.014
GPT teacher head0.276
Teacher spread0.262 · 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 source (direct Gemma or distilled Codex), 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

Citations8
Published2005
Admission routes1
Has abstractyes

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