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Record W2166403104 · doi:10.23865/arctic.v1.2

Food Fish, Commercial Fish, and Fish to Support a Moderate Livelihood: Characterizing Aboriginal and Treaty Rights to Canadian Fisheries

2010· article· en· W2166403104 on OpenAlexaffabout
Douglas C. Harris, Peter Millerd

Bibliographic record

VenueArctic review on law and politics · 2010
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsLivelihoodTreatyFishingFisheryIndigenousIndigenous rightsPolitical scienceFisheries managementFisheries lawRight to foodLawPoliticsGeographyFood securityEcologyAgricultureBiology

Abstract

fetched live from OpenAlex

The Aboriginal peoples of Canada stand in a different legal relationship to the fisheries than non-Aboriginal Canadians. They do so by virtue of a long history with the fisheries that precedes non-Aboriginal settlement in North America, and because of the constitutional entrenchment of Aboriginal and treaty rights in Canadian law. This article describes the characterizations of Aboriginal and treaty rights to fish in Canadian law and discusses what it means for rights characterized in terms of food fishing, commercial fishing, and fishing to support a moderate livelihood, to receive constitutional protection. The article then problematizes these characterizations and suggests that the simplest and broadest characterization, that is, of a right to fish without restriction as to purpose or use of fish, best coincides with the goals of effective management and fair distribution.

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)0.005
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.088
Threshold uncertainty score0.639

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.005
Science and technology studies0.0120.039
Scholarly communication0.0100.003
Open science0.0020.002
Research integrity0.0020.002
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 head0.032
GPT teacher head0.351
Teacher spread0.318 · 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 designQualitative
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

Citations27
Published2010
Admission routes2
Has abstractyes

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