MétaCan
Menu
Back to cohort
Record W4230654436 · doi:10.4324/9781315767963

Nuclear Waste Politics

2017· book· en· W4230654436 on OpenAlexaboutno aff
Matthew Cotton

Bibliographic record

Venuenot available
Typebook
Languageen
FieldEngineering
TopicNuclear and radioactivity studies
Canadian institutionsnot available
Fundersnot available
KeywordsPoliticsRadioactive wasteWaste managementEnvironmental sciencePolitical scienceBusinessEngineeringLaw

Abstract

fetched live from OpenAlex

The question of what to do with radioactive waste has dogged political administrations of nuclear-powered electricity-producing nations since the inception of the technology in the 1950s. As the issue rises to the forefront of current energy and environmental policy debates, a critical policy analysis of radioactive waste management in the UK provides important insights for the future. Nuclear Waste Politics sets out a detailed historical and social scientific analysis of radioactive waste management and disposal in the UK from the 1950s up to the present day; drawing international comparisons with Sweden, Finland, Canada and the US. A theoretical framework is presented for analysing nuclear politics: blending literatures on technology policy, environmental ethics and the geography and politics of scale. The book proffers a new theory of "ethical incrementalism" and practical policy suggestions to facilitate a fair and efficient siting process for radioactive waste management facilities. The book argues that a move away from centralised, high capital investment national siting towards a regional approach using deep borehole disposal, could resolve many of the problems that the high stakes, inflexible "megaproject" approach has caused across the world. This book is an important resource for academics and researchers in the areas of environmental management, energy policy, and science and technology studies.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.026
Threshold uncertainty score0.088

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.004
Scholarly communication0.0060.005
Open science0.0010.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0260.010

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 head0.012
GPT teacher head0.201
Teacher spread0.190 · 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 designNot applicable
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

Citations13
Published2017
Admission routes1
Has abstractyes

Explore more

Same topicNuclear and radioactivity studiesFrench-language works237,207