MétaCan
Menu
Back to cohort
Record W3214659931 · doi:10.4000/ebisu.6037

La vie des réfugiés volontaires de l’accident nucléaire

2021· article· fr· W3214659931 on OpenAlexaff
Shōichirō Takezawa

Bibliographic record

VenueEbisu · 2021
Typearticle
Languagefr
FieldSocial Sciences
TopicRisk Perception and Management
Canadian institutionsMusée de la Civilisation
Fundersnot available
KeywordsPolitical scienceHumanitiesArt

Abstract

fetched live from OpenAlex

L’accident de la centrale nucléaire de Fukushima Daiichi a fait 170 000 évacués, et leur nombre dépasse encore les 40 000 dix ans plus tard. Le gouvernement japonais a fixé des normes d’indemnisation pour les évacués et a ordonné à Tepco de les payer. Beaucoup d’entre eux sont néanmoins mécontents du montant de l’indemnisation et du manque d’excuse du gouvernement : environ 15 000 personnes ont déposé 28 poursuites contre Tepco et le gouvernement. Sur la base des déclarations soumises au tribunal et de nos questionnaires, cet article s’efforce de dresser un document de vie de 171 personnes évacuées (54 ménages) qui ont déposé une plainte devant le tribunal de Kyoto.

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)0.002
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 score0.055
Threshold uncertainty score0.110

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.034
GPT teacher head0.344
Teacher spread0.310 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueEbisuSame topicRisk Perception and ManagementFrench-language works237,207