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Record W2576310476

Free, Prior, and Informed Consent and Reconciliation in Canada: Proposals to Implement Articles 19 and 32 of the UN Declaration on the Rights of Indigenous Peoples

2017· article· en· W2576310476 on OpenAlexaffabout
Sasha Boutilier

Bibliographic record

VenueScholarship@Western (Western University) · 2017
Typearticle
Languageen
FieldEngineering
TopicMining and Resource Management
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsIndigenousParliamentPolitical scienceCommissionDeclarationLegislaturePublic administrationLawIndigenous rightsHuman rightsPolitics
DOInot available

Abstract

fetched live from OpenAlex

Canadian Prime Minister Justin Trudeau has repeatedly promised to meet the Indian Residential School Truth and Reconciliation Commission’s recommendation to implement the United Nations Declaration on the Rights of Indigenous Peoples (UNDRIP) as a framework for reconciliation. This commitment is significant as Canada’s position on UNDRIP has been highly contested. In particular, the compatibility of UNDRIP’s Free, Prior, and Informed Consent (FPIC) standard with Canadian law has been repeatedly called into question. This work evaluates the possibility and importance of implementing FPIC in Canada. It begins with an overview of FPIC internationally and of FPIC in relation to Canadian law. It then suggests potential policy measures to implement two key articles of UNDRIP containing FPIC requirements. To meet Article 32’s FPIC requirement for project approvals for development on their territory, this work draws upon Assembly of First Nations recommendations in suggesting amendments to environmental assessment processes. To implement Article 19’s FPIC requirement for legislative and administrative measures affecting Indigenous Peoples, it suggests revisiting the Royal Commission on Aboriginal People’s recommendation for a House of First Peoples (or Aboriginal Parliament) and informs this suggestion with reflection on the Sámi peoples’ experience with the Sámi Parliament in Norway.

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 score0.896
Threshold uncertainty score0.995

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 studies0.0000.000
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 head0.069
GPT teacher head0.262
Teacher spread0.193 · 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

Citations26
Published2017
Admission routes2
Has abstractyes

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