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Record W2906332175 · doi:10.1093/inthealth/ihy094

Household water sharing: a missing link in international health

2018· article· en· W2906332175 on OpenAlexaff
Justin Stoler, Alexandra Brewis, Leila M. Harris, Amber Wutich, Amber L. Pearson, Asher Y. Rosinger, Roseanne C. Schuster, Sera L. Young

Bibliographic record

VenueInternational Health · 2018
Typearticle
Languageen
FieldNursing
TopicChild Nutrition and Water Access
Canadian institutionsUniversity of British Columbia
FundersNational Institute of Mental HealthInnovative Methods and Metrics for Agriculture and Nutrition ActionsGovernment of the United KingdomNational Institutes of HealthNational Science Foundation
KeywordsWater scarcityNatural disasterCoping (psychology)Public healthBusinessPsychological interventionGlobal healthEnvironmental healthEconomic growthEconomicsPsychologyGeographyMedicine

Abstract

fetched live from OpenAlex

Water insecurity massively undermines health, especially among impoverished and marginalized communities. Emerging evidence shows that household-to-household water sharing is a widespread coping strategy in vulnerable communities. Sharing can buffer households from the deleterious health effects that typically accompany seasonal shortages, interruptions of water services and natural disasters. Conversely, sharing may also increase exposure to pathogens and become burdensome and distressing in times of heightened need. These water sharing systems have been almost invisible within global health research but need to be explored, because they can both support and undermine global public health interventions, planning and policy.

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)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.021
Threshold uncertainty score0.071

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.004
Scholarly communication0.0030.008
Open science0.0010.004
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0210.001

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 head0.060
GPT teacher head0.371
Teacher spread0.311 · 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 designNot applicable
Domainnot available
GenreCommentary

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

Citations46
Published2018
Admission routes1
Has abstractyes

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