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Record W4291019350 · doi:10.1038/s41467-022-31867-3

Inequality of household water security follows a Development Kuznets Curve

2022· article· en· W4291019350 on OpenAlexaff
Feng Mao, Joshua D. Miller, Sera L. Young, Stefan Krause, David M. Hannah, Alexandra Brewis, Alex Trowell, Amber L. Pearson, Amber Wutich, Andrea Sullivan, Asher Y. Rosinger, Ashley Hagaman, Cassandra L. Workman, Chad Staddon, Désiré Tshala-Katumbay, Divya Krishnakumar, Ellis Adjei Adams, Ernesto C. Sánchez-Rodríguez, Genny Carrillo, Gershim Asiki, Hala Ghattas, Hassan Eini‐Zinab, Hugo Melgar‐Quiñonez, Farooq Ahmed, Javier Morán‐Martínez, Jonathan Maupin, Jorge Escobar-Vargas, Justin Stoler, Jyoti S. Mathad, Kelly Chapman, Kenneth Maes, Luisa Samayoa-Figueroa, Mahdieh Sheikhi, Mallika Alexander, Marianne V. Santoso, Matthew C. Freeman, Michael J. Boivin, Milton Marin Morales, Mobolanle Balogun, Monet Ghorbani, Nasrin Omidvar, Nathaly Triviño, Nicola L. Hawley, Patrick Mbullo Owuor, Raymond Asare Tutu, Roseanne C. Schuster, Sabrina Rasheed, Shalean M. Collins, Sonali Srivastava, Stroma Cole, Wendy Jepson, Yihenew Tesfaye, Zeina Jamaluddine

Bibliographic record

VenueNature Communications · 2022
Typearticle
Languageen
FieldNursing
TopicChild Nutrition and Water Access
Canadian institutionsMcGill UniversitySte. Anne's Hospital
FundersNational Institute of Environmental Health SciencesCardiff UniversityNational Institutes of HealthUnited States Agency for International DevelopmentUniversity of BirminghamHigher Education Funding Council for WalesInnovative Methods and Metrics for Agriculture and Nutrition ActionsArizona State UniversityNorthwestern UniversityUniversity of MiamiForeign, Commonwealth and Development OfficeEuropean CommissionBill and Melinda Gates FoundationNational Science Foundation
KeywordsKuznets curveInequalitySustainable developmentWater securityEconomicsIncome distributionEnvironmental economicsNatural resource economicsEconomic growthWater resourcesPolitical scienceMathematicsEcology

Abstract

fetched live from OpenAlex

Water security requires not only sufficient availability of and access to safe and acceptable quality for domestic uses, but also fair distribution within and across populations. However, a key research gap remains in understanding water security inequality and its dynamics, which in turn creates an impediment to tracking progress towards sustainable development. Therefore, we analyse the inequality of water security using data from 7603 households across 28 sites in 22 low- and middle-income countries, measured using the Household Water Insecurity Experiences Scale. Here we show an inverted-U shaped relationship between site water security and inequality of household water security. This Kuznets-like curve suggests a process that as water security grows, the inequality of water security first increases then decreases. This research extends the Kuznets curve applications and introduces the Development Kuznets Curve concept. Its practical implications support building water security and achieving more fair, inclusive, and sustainable development.

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)0.002
metaresearch head score (Gemma)0.018
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.018
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.004
Science and technology studies0.0010.003
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0070.001

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 head0.042
GPT teacher head0.315
Teacher spread0.273 · 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

Citations23
Published2022
Admission routes1
Has abstractyes

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Same venueNature CommunicationsSame topicChild Nutrition and Water AccessFrench-language works237,207