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Record W2968767409 · doi:10.1162/glep_a_00518

Rendering Technical, Rendering Sacred: The Politics of Hydroelectric Development on British Columbia’s Saaghii Naachii/Peace River

2019· article· en· W2968767409 on OpenAlexaffabout
Caleb Behn, Karen Bakker

Bibliographic record

VenueGlobal Environmental Politics · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicHydropower, Displacement, Environmental Impact
Canadian institutionsRoyal Society of Canada
Fundersnot available
KeywordsHydroelectricityHydropowerPoliticsScholarshipTreatyAdjudicationIndigenousEnvironmental politicsPolitical sciencePublic administrationArchaeologyLawGeographyEcology

Abstract

fetched live from OpenAlex

This article analyzes debates over the Site C Dam on the Saaghii Naachii/Peace River in northeastern British Columbia (BC), Canada. After heated debate over the past several decades, construction on the CN$10 billion hydroelectric project—the largest in the province’s history—recently commenced. The article focuses on debates over the analysis and adjudication of cumulative effects, and concomitant treaty rights infringement, within the environmental review process. The shortcomings of the regulatory review process used to assess cumulative effects are analyzed in two ways: first, by a conventional academic assessment, and second, by a Dunne-Za teaching of the interrelationships between land, water, and animals in the dam-affected region. Through juxtaposing these two modes of analysis, the article engages with scholarship in political ecology and Indigenous political theory.

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)0.002
metaresearch head score (Gemma)0.004
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.981
Threshold uncertainty score0.546

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0190.012
Scholarly communication0.0090.001
Open science0.0010.003
Research integrity0.0010.003
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 head0.011
GPT teacher head0.305
Teacher spread0.294 · 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 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

Citations42
Published2019
Admission routes2
Has abstractyes

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