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Record W209951533

On Obligations and Contamination: The Crown-Aboriginal Relationship in the Context of Internationally-Sourced Infringements

2009· article· en· W209951533 on OpenAlexaffabout
Constance MacIntosh

Bibliographic record

VenueSSRN Electronic Journal · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicEnvironmental law and policy
Canadian institutionsDalhousie University
Fundersnot available
KeywordsMercury contaminationPolitical scienceContext (archaeology)JurisprudenceLawSustenanceLaw and economicsSociologyGeographyEcology
DOInot available

Abstract

fetched live from OpenAlex

This paper considers and questions several aspects of how the jurisprudence has come to conventionalize approaches to Aboriginal rights and Crown obligations. Although intended as an exploratory work, this paper is grounded in the case study of mercury biocontamination of "country food," which provides physical and cultural sustenance to northern Aboriginal peoples. I selected this case study for the very reason that it seems to fall outside the scope that the traditional analysis of Aboriginal rights and Crown obligations embraces. Although the tight relationship between cultural integrity and practices of collecting and sharing food in the north would surely substantiate a s. 35(1) rights claim, there is no particular domestic Canadian law or regulation that can be meaningfully targeted as the infringing "smoking gun" due to the contaminant having multiple international sources. Mercury contamination arises as a general byproduct of world-wide fossil fuel based industrial activity and is also being released from Arctic sinks as a result of climate change. This fact pattern differs considerably from those that have come before Canadian courts, and so it can ground a speculative engagement concerning where the principles of s. 35(1) take us when the Crown is not responsible, per se, for a situation which threatens Aboriginal rights, but where the Crown has the power to act to try to change the situation. Within my analysis, I consider and try to address some of the inconsistencies potentially operating in the logic of how Aboriginal rights claims are often framed.

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)0.017
metaresearch head score (Gemma)0.015
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: Empirical · Consensus signal: none
Teacher disagreement score0.643
Threshold uncertainty score0.710

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.015
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0350.109
Scholarly communication0.0150.010
Open science0.0040.016
Research integrity0.0150.013
Insufficient payload (model declined to judge)0.0030.000

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 head0.011
GPT teacher head0.307
Teacher spread0.296 · 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
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

Citations0
Published2009
Admission routes2
Has abstractyes

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Same venueSSRN Electronic JournalSame topicEnvironmental law and policyFrench-language works237,207