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Record W3137003860 · doi:10.55016/ojs/sppp.v12i1.68159

Understanding Consultation and Engagement with Indigenous Peoples in Resource Development

2019· article· en· W3137003860 on OpenAlexaffabout
Brendan Boyd, Sophie Lorefice

Bibliographic record

VenueThe School of Public Policy Publications · 2019
Typearticle
Languageen
FieldEngineering
TopicMining and Resource Management
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsIndigenousResource (disambiguation)Political scienceSociologyEngineering ethicsEngineeringComputer scienceEcologyBiology

Abstract

fetched live from OpenAlex

Canada’s legal system has repeatedly ruled that the Crown has a duty to consult with Indigenous Peoples when approving and shaping resource development projects that are located on their land or could infringe on their rights. But the duty to consult means different things to Indigenous groups, government and industry. Different understandings among stakeholders, in particular Indigenous groups dissatisfaction with consultation, has often led to court challenges of project decisions. Recently, the Federal Court of Appeal’s decision to overturn the federal government’s approval of the Trans Mountain pipeline project in 2018 has attracted the attention of politicians, media and the public. Legal challenges have also occurred over smaller, yet still important, activities and decisions, where Indigenous communities and organizations find formal consultation processes, and the overall approach to engagement taken by industry and government, to be lacking. While these represent a small portion of the total number of cases where the legal duty to consult has been triggered (Newman 2017) they have an outsized impact on the relationships and level of trust between Indigenous Peoples, industry and governments. Finding ways to resolve these conflicts and improve relations can contribute to reconciliation between Indigenous Peoples, non-Indigenous Canadians and the Canadian state and is essential to the future of Canada’s natural resource industries.

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)0.017
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.637
Threshold uncertainty score0.730

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.017
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.002
Science and technology studies0.0430.049
Scholarly communication0.0140.011
Open science0.0020.016
Research integrity0.0060.006
Insufficient payload (model declined to judge)0.0070.000

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 head0.055
GPT teacher head0.248
Teacher spread0.194 · 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

Citations0
Published2019
Admission routes2
Has abstractyes

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