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Validity and Reliability Analysis of the Household Water Insecurity Experiences Scale: The Case of Argentina

2025· preprint· en· W4409016489 on OpenAlexaff
Ianina Tuñón, Matías Maljar, Nazarena Bauso, Olga P. García, Hugo Melgar Quiñonez

Bibliographic record

VenuePreprints.org · 2025
Typepreprint
Languageen
FieldNursing
TopicChild Nutrition and Water Access
Canadian institutionsMcGill University
Fundersnot available
KeywordsScale (ratio)Reliability (semiconductor)PsychologyGeographyCartographyPhysics

Abstract

fetched live from OpenAlex

Objective. Evaluate the validity and reliability of the Household Water Insecurity Experiences Scale (HWISE) as a tool to assess the experiences of households and the Argentine population regarding insecurity in access to water. Material and methods. The scale was administered as part of the Argentine Social Debt Survey (EDSA), on a probabilistic sample of 5,799 households. Results. The HWISE scale proved to be reliable globally and in each of its items (Cronbach's Alpha of 0.95 at a total level and greater than 0.94 in each of the items), and criterion validity in terms of correlation with a broad set of indicators of social deprivations, sanitary infrastructure, food insecurity, and psychological health. Finally, the scale showed internal consistency, with a total Omega coefficient value of 0.96, suggesting that all scale indicators refer to the same concept of deprivation in water access. Conclusions. The HWISE scale applied to the case of Argentina is deemed appropriate for estimating household water insecurity.

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)0.004
metaresearch head score (Gemma)0.010
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 score0.031
Threshold uncertainty score0.061

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.099
GPT teacher head0.346
Teacher spread0.247 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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