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Record W7027637681

Considerations For Source Water Protection In Ontario

2018· other· en· W7027637681 on OpenAlexaffabout

Bibliographic record

VenueYork University Digital Library (York University) · 2018
Typeother
Languageen
FieldEconomics, Econometrics and Finance
TopicRegional resilience and development
Canadian institutionsYork University
Fundersnot available
KeywordsSustainabilityEcosystem servicesWater resourcesScope (computer science)Clean Water ActWatershed managementRaw waterWatershedWater securityTotal maximum daily load
DOInot available

Abstract

fetched live from OpenAlex

Source water protection under the Ontario Clean Water Act (2006) emerged after the fatal E. coli outbreak in Walkerton, Ontario in 2000. It is the protection of raw drinking water at its source, and it is carried out at a local watershed and municipal level primarily through land use planning tools and stewardship in Ontario. The scope of source water protection is limited to anthropocentric considerations, and therefore it misses the opportunity to protect watersheds for the sake of ecosystem integrity and to conserve the many critical ecosystem services provided by watersheds. There are numerous threats to watersheds and other considerations that are not currently addressed by the regulation that undermine effective source water protection, such as groundwater quantity, urban growth, and existing contaminated lands. In addition, a jurisdictional gap has led to a water crisis in many First Nations communities, for whom contaminated source water is a primary concern. However, source water protection in First Nations communities is made difficult by external and internal threats, and as a tool, it is neither holistic nor aligned with traditional water management practices. Management of watersheds and water sources requires complex solutions and strong governance and institutions. Global freshwater resources are under unprecedented strain, and the lessons from Ontario can be emulated and expanded upon to achieve sustainability and ecosystem integrity.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.145
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.002

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 head0.033
GPT teacher head0.152
Teacher spread0.119 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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
Published2018
Admission routes2
Has abstractyes

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