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Record W2790795367 · doi:10.1111/socf.12419

The Shelf Life of a Disaster: Post‐Fukushima Policy Change in The United States And Germany

2018· article· en· W2790795367 on OpenAlexaff
Steve Hoffman, Paul Durlak

Bibliographic record

VenueSociological Forum · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicRisk Perception and Management
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsGermanPoliticsNuclear disasterNuclear energy policyPolitical sciencePolitical economyPublic administrationSociologyNuclear powerLawHistoryEngineering

Abstract

fetched live from OpenAlex

How can large‐scale disasters prompt policy change beyond the local environment in which they occurred? Working at the intersection of political sociology, disaster studies, and cultural sociology, we introduce the concept of the shelf life of a disaster to analyze the short and limited impact of Fukushima Daiichi on U.S. nuclear energy policy and its vitality within Germany. American media, nuclear industry representatives, regulators, and policy makers contributed to a tepid political environment for policy change by expanding symbolic distance from Fukushima, focusing on U.S. superiority to Japanese infrastructures. While this technicist orientation was evident in Germany as well, its distancing effects were offset by a conjunction of mechanisms that packaged Fukushima as a precursor to an inevitable German nuclear catastrophe.

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)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.088
Threshold uncertainty score0.175

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.003
Scholarly communication0.0030.002
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.057
GPT teacher head0.372
Teacher spread0.315 · 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 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

Citations16
Published2018
Admission routes1
Has abstractyes

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