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Record W2976151420

Rhetoric Deployed in the Communication Between the National Energy Board and Aboriginal Communities in the Case of the Trans Mountain Pipeline

2019· article· en· W2976151420 on OpenAlexaffabout
Lidia Cooey-Hurtado, Danielle Tan, Breagh Kobayashi

Bibliographic record

VenueYoung scholars in writing · 2019
Typearticle
Languageen
FieldArts and Humanities
TopicRhetoric and Communication Studies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMetisIndigenousRhetoricGovernment (linguistics)Indigenous rightsSupreme courtDutyPolitical scienceDeclarationPower (physics)Human rightsRhetorical questionLawCorporationPublic administrationEcology
DOInot available

Abstract

fetched live from OpenAlex

The Canadian government has a duty to consult Aboriginal peoples on projects that impact them. However, the overall framework of the consultation and the definition of certain key terms, such as “impact” and “consent,” are decided exclusively by the government. Retaining hold of this decision-making power is inconsistent with rulings by the Supreme Court of Canada and United Nations’ Declaration on the Rights of Indigenous Peoples. The rhetoric used in the proposal, advertisement, and approval of the Trans Mountain Pipeline Expansion reflects and perpetuates both the power imbalance and the failure of the Canadian government to invest in a symbiotic and long-term relationship with First Nations, Metis, and Inuit peoples of Canada. The Canadian government uses similar rhetorical strategies as Kinder Morgan, such as accentuating pipeline positives and downplaying negatives, which construct a perspective that favours economic development and marginalizes Indigenous rights, human well-being, and ecological intactness.

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)0.022
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: none
Teacher disagreement score0.400
Threshold uncertainty score0.805

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.022
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.003
Science and technology studies0.0430.049
Scholarly communication0.0130.006
Open science0.0020.007
Research integrity0.0060.009
Insufficient payload (model declined to judge)0.0030.000

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 head0.039
GPT teacher head0.297
Teacher spread0.258 · 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

Citations4
Published2019
Admission routes2
Has abstractyes

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