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Record W2196699879

Testing the Waters: Jurisdictional and Policy Aspects of the Continuing Failure to Remedy Drinking Water Quality on First Nations Reserves

2008· article· en· W2196699879 on OpenAlexaffabout
Constance MacIntosh

Bibliographic record

VenueeYLS (Yale Law School) · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicAmerican Environmental and Regional History
Canadian institutionsDalhousie University
Fundersnot available
KeywordsWater qualityQuality (philosophy)BusinessNatural resource economicsEnvironmental planningEnvironmental scienceEconomicsEcologyBiology
DOInot available

Abstract

fetched live from OpenAlex

This paper considers why, from a policy and legal perspective, there is such a disparity between the water quality on First Nations reserves, and that experienced in the majority of other Canadian communities. This involves engaging with how jurisdictional allocations, governmental policies, statutory or policy-del-egated mandates, and operational practices con-verge. In this discussion, two inter-related tensions emerge. The first is between Aboriginal aspirations to self-govern and community capacity to effectively engage in governance activities. The second is Canada's proper role and responsibilities in resolving the governance/capacity tension, and in resolving the water quality problems.\nThis paper ultimately concludes that the federal government has erred in failing to legislate standards, which has allowed A potentially responsible parties to avoid an enforceable obligation to act. In finding that a legislative regime is required, this paper considers and refutes the propositions that jurisdictional uncertainty or the pressing need for Aboriginal governments to develop capacity and take on fuller governance roles are barriers to creating the required protective regime. That is, this paper contemplates a legislative regime which accommodates and addresses these issues.

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 score0.194
Threshold uncertainty score0.794

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 studies0.0010.002
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 head0.018
GPT teacher head0.231
Teacher spread0.213 · 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

Citations2
Published2008
Admission routes2
Has abstractyes

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