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Record W2063949320 · doi:10.1080/15287390490491864

DRINKING-WATER RISK MANAGEMENT PRINCIPLES FOR A TOTAL QUALITY MANAGEMENT FRAMEWORK

2004· article· en· W2063949320 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of Toxicology and Environmental Health · 2004
Typearticle
Languageen
FieldSocial Sciences
TopicWater Resources and Governance
Canadian institutionsUniversity of AlbertaProvincial Laboratory of Public Health
Fundersnot available
KeywordsMandateAccreditationBusinessBest practiceGovernment (linguistics)CommissionQuality (philosophy)Quality management systemQuality managementPublic relationsProcess managementEnvironmental resource managementOperations managementRisk analysis (engineering)EngineeringMarketingPolitical scienceLawFinanceEconomicsService (business)

Abstract

fetched live from OpenAlex

The Walkerton Inquiry Part 2 Report addressed the second part of the mandate from the Government of Ontario under the Public Inquiries Act, following the Walkerton tragedy, namely, "to make such findings and recommendations as the commission considers advisable to ensure the safety of the water supply system in Ontario." In addressing this mandate Justice O'Connor noted: "Perhaps the most significant recommendations in this report address the need for quality management through mandatory accreditation and operational planning. I recommend requiring all operating agencies to become accredited in accordance with a quality management standard-a standard that will be developed by the industry and others knowledgeable in the area and mandated by the MOE." This recommendation reflects a recognition that any narrow set of detailed requirements related to specific water quality issues will not be able to provide sufficiently comprehensive and flexible guidance to cover the diversity of challenges that exist. Rather, by creating and mandating a process to capture and codify the best technical, operating, and managerial practices, a system can be created that will seek to have these best practices adopted across the drinking-water industry. Done well, this will provide the industry and regulators with the culture and capacity to recognize and resolve problems to prevent future drinking-water tragedies. This paper provides some guiding principles that should foster the development of a practical accreditation standard to achieve the foregoing objectives.

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.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.500
Threshold uncertainty score0.429

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.025
GPT teacher head0.317
Teacher spread0.292 · 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