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Record W2905651185 · doi:10.32920/ryerson.14645265.v1

A critical analysis of the deep geologic repository siting process in Ontario

2021· preprint· en· W2905651185 on OpenAlexaffabout
Anam Ahmad

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldSocial Sciences
TopicRisk Perception and Management
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsOpposition (politics)Radioactive wasteEnvironmental planningPublic participationPlan (archaeology)Qualitative analysisProcess (computing)EngineeringBusinessCivil engineeringQualitative researchWaste managementPublic administrationPolitical scienceEnvironmental scienceComputer scienceGeographyArchaeologySociologyLawPolitics

Abstract

fetched live from OpenAlex

This research paper is a case study of OPG’s siting process for a low and intermediate level radioactive waste facility. The chosen site is in Kincardine, Ontario, where nuclear waste is currently stored above ground. The Town of Kincardine is in support of the project; however, several individuals and organizations are actively opposing the facility. The objective of this paper is to understand why the facility is facing so much opposition, what steps could have been taken to prevent it and how to proceed with the project plan. An inductive analysis of qualitative data was performed using explanation building and pattern matching. Lessons were drawn from cooperative siting guidelines specific to nuclear waste repositories in Ontario. The conclusion was drawn that omission of extensive public consultation in the siting process resulted in significant public opposition. Increasing community involvement when moving forward with the project may assist in reducing public opposition.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.473
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.035
GPT teacher head0.347
Teacher spread0.312 · 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 teacher head, not a consensus.

Study designObservational
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

Citations1
Published2021
Admission routes2
Has abstractyes

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