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Record W4408701800 · doi:10.1088/2634-4505/adc3bc

Convenience over control: qualitative insights from water system users in a rural setting in Gujarat, India

2025· article· en· W4408701800 on OpenAlexaff
Florence Anne Olson Udenby, Samantha LeValley, Srinivas Chokkakula, David Meyer

Bibliographic record

VenueEnvironmental Research Infrastructure and Sustainability · 2025
Typearticle
Languageen
FieldEngineering
TopicWater resources management and optimization
Canadian institutionsCentre for Global Health ResearchHudbay Minerals (Canada)
Fundersnot available
KeywordsQualitative researchControl (management)GeographyEnvironmental planningComputer scienceSociologySocial scienceArtificial intelligence

Abstract

fetched live from OpenAlex

Abstract Piped water systems have become an increasing focus of global and national development goals. India is providing piped-to-premise water supplies to more than two million rural inhabitants every week. But rural piped water systems often operate intermittently and may not always provide water that is available when needed. This paper presents insights from a qualitative study that draws on 30 interviews and 11 focus group discussions investigating the extent to which piped-to-premise interventions have improved access to water supply in 6 rural hamlets in eastern Gujarat, India. Households with access to piped water revealed that the rigidity of the intermittent piped water schedules limited water availability, necessitating their use of additional water sources. Households that relied on handpumps or private wells described greater agency in how and when they collect water. Throughout the year, but particularly in monsoon season, participants reported that grid-powered and solar-powered piped water systems underperformed due to electricity blackouts (lasting as long as seven days) and cloudy weather, respectively. To mitigate the drawbacks of intermittently operated piped water systems, and to decrease the necessity for potentially harmful coping strategies, this study suggests that piped water system designs should enable operational flexibility, tailored to community needs, so that water is available when needed. To increase the resilience and reliability of rural piped systems, we recommend that systems design incorporate more storage and rely on robust and resilient energy sources.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.023
Threshold uncertainty score0.534

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.004
GPT teacher head0.255
Teacher spread0.251 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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