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Record W3119530334 · doi:10.1002/eet.1923

Evaluating deliberative participation from a social learning perspective: A case study of the 2012 National Energy Deliberative Polling in <scp>post‐Fukushima</scp> Japan

2021· article· en· W3119530334 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEnvironmental Policy and Governance · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicRisk Perception and Management
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsDeliberationSocial learningCitizen journalismContext (archaeology)DialogicPublic relationsCorporate governancePublic participationPolitical scienceGovernment (linguistics)Collaborative governanceNuclear powerSociologyPublic administrationEconomicsPedagogyManagement

Abstract

fetched live from OpenAlex

Abstract Nuclear power has remained a hugely controversial energy technology since the 1970s and became particularly so after the 2011 Fukushima nuclear accident. Engaging citizens in making energy decisions have thus become an increasingly important governing approach to post‐Fukushima energy transitions in many countries. Deliberative participatory processes and learning through social interactions have been increasingly regarded as critical elements of effective public engagement. Yet, little is known about who learns what, how they learn, and what impacts learning has on nuclear governance. Even less is known about the contextual factors influencing social learning. Advancing the literature on nuclear governance, deliberative participation, and social learning, this paper proposes a learning‐oriented framework to evaluate the outcomes of deliberative participation in the context of nuclear governance. We apply this framework in a case study of a national deliberative poll (DP) on energy conducted in Japan in 2012. We critically examine the extent to which and how social learning occurs under the influence of pre‐existing government‐industry‐society relations as a key contextual factor. Mainly based on a qualitative analysis of transcribed materials from a two‐day deliberation over the DP involving 285 citizens, this study has three main findings. First, participating citizens of the DP were able to acquire all of the three orders of social learning through deliberative processes in the DP process. Second, the provision of multiple sources of information, access to diverse perspectives, and the availability of plenty of dialogic processes are identified as factors that were found to facilitate advancement toward higher orders of learning. Third, the “nuclear iron triangle”—a pro‐nuclear coalition—appeared to constrain social learning impacts in the wider socio‐political systems of nuclear governance in Japan.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.332
Threshold uncertainty score0.973

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.042
GPT teacher head0.374
Teacher spread0.332 · 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