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Record W2802534228 · doi:10.1080/22423982.2018.1466605

Factors associated with drinking and being satisfied with tap water in Indigenous communities in Saskatchewan, Canada

2018· article· en· W2802534228 on OpenAlexafffundabout
Silvia Bermedo-Carrasco, Lalita Bharadwaj, Cheryl Waldner

Bibliographic record

VenueInternational Journal of Circumpolar Health · 2018
Typearticle
Languageen
FieldNursing
TopicChild Nutrition and Water Access
Canadian institutionsUniversity of Saskatchewan
FundersCanadian Institutes of Health Research
KeywordsIndigenousTap waterGeographyEnvironmental healthGerontologyPsychologyEnvironmental protectionMedicineEnvironmental scienceEcologyBiologyEnvironmental engineering

Abstract

fetched live from OpenAlex

Previous studies have described concerns regarding tap water in Indigenous communities, yet there is little information on participants who report drinking their tap water and being satisfied with its quality. This study undertaken with members of 8 Indigenous communities in Saskatchewan, Canada, and identified factors associated with both the decision to drink tap water at home and being satisfied with its quality. We examined the importance of factors such as individual attributes, experiences, attitudes, household and community-based variables. Less than one-quarter of participants (23.4%) drank tap water and were satisfied with its quality. Individuals who did not boil tap water (odds ratio [OR] = 5.76, 95% confidence interval [CI] = 1.68-19.8), those who did not experience tap water odour (OR = 2.38, 95% CI = 1.26-4.50) and participants living in communities away from urban centres (OR = 2.74, 95% CI = 1.63-4.51) were more likely to drink and be satisfied with their tap water. Concerns about the environment had the most impact on community members aged 55+ years. Those not reporting concerns about environmental problems affecting water (OR = 11.4, 95% CI = 3.10-42.2) were much more likely to drink and be satisfied with their tap water. Programmes to improve water quality, reduce the need for boil water advisories and increase community confidence in the environment could improve tap water satisfaction and consumption.

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)0.000
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 score0.604
Threshold uncertainty score0.632

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.019
GPT teacher head0.271
Teacher spread0.252 · 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

Citations17
Published2018
Admission routes3
Has abstractyes

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