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Record W2897798488 · doi:10.18584/iipj.2018.9.3.4

The Canadian Crown's Duty to Consult Indigenous Nations' Knowledge Systems in Federal Environmental Assessments

2018· article· en· W2897798488 on OpenAlexaffvenueabout
Stephen S. Crawford

Bibliographic record

VenueInternational Indigenous Policy Journal · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental and Social Impact Assessments
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsLegislationIndigenousGovernment (linguistics)DutyPublic administrationPolitical scienceTraditional knowledgeLawEnvironmental protectionGeography

Abstract

fetched live from OpenAlex

In 2016, the Government of Canada undertook a review of regulatory processes for federal environmental assessments (EAs) in preparation for replacing the Canadian Environmental Assessment Act. An EA Expert Panel was appointed to review numerous oral and written submissions from Indigenous nations, government agencies, and the public. The Panel's final report included recommendations that were considered by Canada in the development of its currently proposed new legislation regarding federal EAs: Bill C-69. The goal of this analysis is to evaluate the extent to which Canada’s review and proposed legislation actually addressed the Crown’s duty to consult Indigenous nations' knowledge systems. Detailed examination of the Panel's review and Canada's response shows clearly that the Crown's duty has not been fulfilled by the proposed legislation, in either spirit or practice.

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)0.043
metaresearch head score (Gemma)0.080
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.969
Threshold uncertainty score0.890

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0430.080
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.005
Science and technology studies0.0310.016
Scholarly communication0.0220.005
Open science0.0040.006
Research integrity0.0090.010
Insufficient payload (model declined to judge)0.0040.001

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 head0.017
GPT teacher head0.339
Teacher spread0.322 · 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.

Study designTheoretical or conceptual
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

Citations4
Published2018
Admission routes3
Has abstractyes

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