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Record W2905302417 · doi:10.1007/978-94-6265-267-5_12

Nuclear Law, Oversight and Regulation: Seeking Public Dialogue and Democratic Transparency in Canada

2018· book-chapter· en· W2905302417 on OpenAlexfundaboutno aff
Kerrie Blaise, Theresa McClenaghan, Richard Lindgren

Bibliographic record

VenueT.M.C. Asser Press eBooks · 2018
Typebook-chapter
Languageen
FieldSocial Sciences
TopicRisk Perception and Management
Canadian institutionsnot available
FundersUniversity of Manitoba
KeywordsTransparency (behavior)Public administrationPolitical scienceCommissionGovernment (linguistics)Public participationNuclear energy policyDemocracyRadioactive wasteBusinessLawNuclear powerPoliticsEngineering

Abstract

fetched live from OpenAlex

To begin public discourse on acceptable policies and strategies surrounding Canada’s continued reliance on nuclear energy and the waste legacy it generates, this chapter explains the work of the Canadian Nuclear Safety Commission (CNSC), the regulatory body which oversees Canada’s nuclear industry. The authors describe the federal laws surrounding nuclear licensing and environmental approvals. They comment on current plans relating to radioactive waste disposal and emergency planning in light of the Fukushima Daiichi accident. They conclude that to strengthen the independence of the CNSC, opportunities for meaningful public participation should be developed, Indigenous engagement in CNSC decision-making processes be affirmed, and the federal government’s role and responsibilities for nuclear emergency management clarified.

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)0.005
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.254
Threshold uncertainty score0.865

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.007
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.005
Science and technology studies0.0270.040
Scholarly communication0.0240.005
Open science0.0020.005
Research integrity0.0060.007
Insufficient payload (model declined to judge)0.0060.000

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 head0.046
GPT teacher head0.246
Teacher spread0.200 · 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 designTheoretical or conceptual
Domainnot available
GenreOther

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

Citations3
Published2018
Admission routes2
Has abstractyes

Explore more

Same venueT.M.C. Asser Press eBooksSame topicRisk Perception and ManagementFrench-language works237,207