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Record W2092265928 · doi:10.3390/ijerph110504634

Drinking Water Quality Guidelines across Canadian Provinces and Territories: Jurisdictional Variation in the Context of Decentralized Water Governance

2014· review· en· W2092265928 on OpenAlexaffabout
G. Dunn, Karen Bakker, Leila M. Harris

Bibliographic record

VenueInternational Journal of Environmental Research and Public Health · 2014
Typereview
Languageen
FieldEnvironmental Science
TopicEnvironmental and Social Impact Assessments
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsContext (archaeology)Corporate governanceWater qualityVariation (astronomy)GeographyQuality (philosophy)Environmental planningBusinessEcologyBiologyArchaeology

Abstract

fetched live from OpenAlex

This article presents the first comprehensive review and analysis of the uptake of the Canadian Drinking Water Quality Guidelines (CDWQG) across Canada's 13 provinces and territories. This review is significant given that Canada's approach to drinking water governance is: (i) highly decentralized and (ii) discretionary. Canada is (along with Australia) only one of two Organization for Economic Cooperation and Development (OECD) member states that does not comply with the World Health Organization's (WHO) recommendation that all countries have national, legally binding drinking water quality standards. Our review identifies key differences in the regulatory approaches to drinking water quality across Canada's 13 jurisdictions. Only 16 of the 94 CDWQG are consistently applied across all 13 jurisdictions; five jurisdictions use voluntary guidelines, whereas eight use mandatory standards. The analysis explores three questions of central importance for water managers and public health officials: (i) should standards be uniform or variable; (ii) should compliance be voluntary or legally binding; and (iii) should regulation and oversight be harmonized or delegated? We conclude with recommendations for further research, with particular reference to the relevance of our findings given the high degree of variability in drinking water management and oversight capacity between urban and rural areas in Canada.

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)0.007
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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.959
Threshold uncertainty score0.984

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.110
GPT teacher head0.466
Teacher spread0.356 · 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 designOther design
Domainnot available
GenreReview

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

Citations54
Published2014
Admission routes2
Has abstractyes

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