MétaCan
Menu
Back to cohort
Record W2916814861 · doi:10.3390/w11030406

Contested Knowledges in Hydroelectric Project Assessment: The Case of Canada’s Site C Project

2019· article· en· W2916814861 on OpenAlexafffundabout
Karen Bakker, Richard C. Hendriks

Bibliographic record

VenueWater · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental and Social Impact Assessments
Canadian institutionsUniversity of TorontoUniversity of British Columbia
FundersSocial Sciences and Humanities Research Council of CanadaUniversity of British Columbia
KeywordsCommissionHydroelectricityLegislationPublic administrationEnvironmental planningGovernment (linguistics)Political scienceEnvironmental impact assessmentGreenhouse gasImpact assessmentProcess (computing)Environmental resource managementEnvironmental protectionEngineeringLawGeographyEnvironmental science

Abstract

fetched live from OpenAlex

This paper analyzes contestation over aspects of the Site C Project on the Peace River in northeastern British Columbia, Canada. The $10.7 billion project, which is now under construction, has been vigorously debated for over 30 years. Initially proposed in the 1980s, project approval was not granted following review by the BC Utilities Commission, as the need for the project was not established. In 2010, the provincial government enacted legislation to exempt the project from future review by the BC Utilities Commission; an environmental assessment was initiated in 2012 and a constrained review by the Commission was undertaken in 2017, after construction had commenced. The paper explores key examples of contested knowledge regimes within the review process, focusing on debates over cumulative effects and greenhouse gas emissions. The analysis provides technical examples of the ways in which differing societal values are deployed and co-produced within regulatory processes.

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)0.105
metaresearch head score (Gemma)0.116
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: Empirical
Teacher disagreement score0.963
Threshold uncertainty score0.939

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1050.116
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0080.011
Science and technology studies0.0370.043
Scholarly communication0.0340.010
Open science0.0040.013
Research integrity0.0090.007
Insufficient payload (model declined to judge)0.0020.000

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 head0.009
GPT teacher head0.261
Teacher spread0.252 · 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

Citations29
Published2019
Admission routes3
Has abstractyes

Explore more

Same venueWaterSame topicEnvironmental and Social Impact AssessmentsFrench-language works237,207