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Record W2765300743 · doi:10.3138/jcs.51.1.153

Destabilizing the Consultation Framework in Alberta’s Tar Sands

2017· article· en· W2765300743 on OpenAlexvenueaboutno aff
Jennifer S. Mills

Bibliographic record

VenueJournal of Canadian Studies · 2017
Typearticle
Languageen
FieldEngineering
TopicMining and Resource Management
Canadian institutionsnot available
Fundersnot available
KeywordsIndigenousIndigenous rightsPublic administrationGovernment (linguistics)DemocracyTreatyPolitical scienceOil sandsLawHuman rightsPoliticsGeography

Abstract

fetched live from OpenAlex

The 2015 election of the New Democratic Party (NDP) in Alberta and the NDP government’s commitment to implementing the United Nations Declaration on the Rights of Indigenous Peoples has opened up new possibilities for reforming the province’s relationship with First Nations and Métis communities. Alberta’s tar sands regulatory process and consultation policy with Indigenous peoples, however, has so far remained the same, and the provincial government continues to support expanding the industry. This article argues that the 2014 Consultation Guidelines imposed by the previous Progressive Conservative government severely limit the participation rights of Indigenous peoples and violate treaty rights by not adequately addressing cumulative impacts. Despite sustained critique by legal scholars and Indigenous communities, previous reforms to the consultation system have not substantively addressed their concerns. In response, several First Nations in Alberta have launched legal actions challenging both the consultation regime and specific project approvals. Following a discussion of consultation and consent in Canada, the article uses recent legal cases to illustrate how Indigenous peoples in Alberta have been excluded from key decision-making around the oil industry. Finally, it considers how the regulatory process must change to respect Indigenous rights and self-determination.

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)0.001
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.518
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.033
GPT teacher head0.267
Teacher spread0.234 · 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 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

Citations6
Published2017
Admission routes2
Has abstractyes

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