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Record W4234509944 · doi:10.32920/ryerson.14648199

A capacity assessment and legislative review of the Clean Water Act in Ontario : past, present and future

2021· preprint· en· W4234509944 on OpenAlexafffundabout
Andrea Torok

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEnvironmental Science
TopicEnvironmental and Social Impact Assessments
Canadian institutionsToronto Metropolitan UniversityA&L Canada Laboratories (Canada)
FundersNatural Resources CanadaMinistry of Education, IndiaU.S. Geological SurveyOntario Ministry of Health and Long-Term CareU.S. Department of AgricultureU.S. Environmental Protection Agency
KeywordsLegislationClean Water ActLegislatureConsistency (knowledge bases)Environmental planningBusinessGovernment (linguistics)Capacity buildingDistribution (mathematics)Local governmentPoliticsEnvironmental resource managementPublic administrationPolitical scienceEnvironmental scienceWater qualityLaw

Abstract

fetched live from OpenAlex

Historically an unequal distribution of capacity existed among local Municipalities and Conservation Authorities with regards to protecting water in Ontario, as well there was no specific legislation pertaining solely to source water protection. The aim of this research project is to present and analyze through a comparative assessment, the financial capacity requirements and the technical, institutional, social and political capacity progress observed among the 19 Source Protection Regions across Ontario in terms of protecting source water following the Walkerton event and the enactment of the Clean Water Act (CWA). The results indicate that through the enactment of the CWA, capacity building initiatives have taken place through a top-down model with the provincial governments' guidance, direction and support to local municipalities and CAs. When the provincial government takes control and provides capacity related assistance, the lower level municipal and CA governments become regulated; functioning more effectively and with a level of consistency across the province.

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)0.012
metaresearch head score (Gemma)0.030
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: Review · Consensus signal: none
Teacher disagreement score0.141
Threshold uncertainty score0.996

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.030
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0090.018
Science and technology studies0.0050.003
Scholarly communication0.0050.002
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.023
GPT teacher head0.280
Teacher spread0.256 · 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
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

Citations1
Published2021
Admission routes3
Has abstractyes

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