MétaCan
Menu
Back to cohort
Record W2073766054 · doi:10.7202/800524ar

Resistance to Nuclear Waste Disposal: Credentialed Experts, Public Opposition and their Shared Lines of Critique

2009· article· en· W2073766054 on OpenAlexafffundvenueabout
Darrin Durant

Bibliographic record

VenueScientia Canadensis Canadian Journal of the History of Science Technology and Medicine · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicRisk Perception and Management
Canadian institutionsYork University
FundersGovernment of Ontario
KeywordsFraming (construction)Opposition (politics)Atomic energyResistance (ecology)Statutory lawQuarter (Canadian coin)LawPolitical sciencePublic policyPublic administrationSociologyPublic relationsLaw and economicsEngineeringSocial sciencePoliticsCivil engineeringHistory

Abstract

fetched live from OpenAlex

This article asks the question whether, in regard to controversial technical decision-making, lay public groups advance different kinds of resistance than credentialed experts. This question is explored via a case-study analysis of one of Canada's major public controversies of the past quarter century—nuclear waste disposal. Having arrived on the policy radar in 1977, nuclear waste remained an internal government/nuclear industry matter until terms of reference for a public inquiry were announced in 1989. Several access points for public input followed that announcement: scoping sessions in 1990, comments received during 1994-96 on an Environmental Impact Statement (EIS) prepared by Atomic Energy Canada Limited (AECL), nation-wide public hearings in 1996-97, and ongoing public consultation since 2002. This article focuses on the comments on the EIS, and discusses several lines of shared resistance: the expert judgment of AECL was disputed, the lack of peer review was criticized, accusations of unreliability were made, and general deficiencies in the EIS were attributed to narrow terms of reference and poor institutional culture. This article recommends the use of a dramaturgical approach to technical texts, and reveals the assumptions framing the dualist notion that one can unambiguously separate technical and social criticisms of technical projects.

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)0.102
metaresearch head score (Gemma)0.193
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.985
Threshold uncertainty score0.539

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1020.193
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0080.005
Science and technology studies0.0300.092
Scholarly communication0.0310.012
Open science0.0040.018
Research integrity0.0250.016
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 head0.019
GPT teacher head0.265
Teacher spread0.246 · 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

Citations8
Published2009
Admission routes4
Has abstractyes

Explore more

Same venueScientia Canadensis Canadian Journal of the History of Science Technology and MedicineSame topicRisk Perception and ManagementFrench-language works237,207