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Record W3156952952 · doi:10.29173/af29428

Les disparus du Japon dans la littérature francophone contemporaine À propos des Evaporés de Thomas B. Reverdy et des Eclipses japonaises d’Eric Faye

2021· article· fr· W3156952952 on OpenAlexvenueno aff
Philippe Wellnitz

Bibliographic record

VenueALTERNATIVE FRANCOPHONE · 2021
Typearticle
Languagefr
FieldMedicine
TopicHistorical and Scientific Studies
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesArt

Abstract

fetched live from OpenAlex

Deux auteurs français qui ont séjourné au Japon, Thomas B. Reverdy et Eric Faye, ont écrit chacun un roman abordant le sujet des personnes disparues au Japon. Le roman de Thomas B. Reverdy, Les Évaporés (2013) décrit la disparition volontaire d’un homme aux prises avec les sombres affaires entourant la catastrophe de Fukushima. Ces disparitions volontaires, connues sous le terme de jôhatsu (« évaporé »), concernent environ 100.000 personnes par an au Japon et y sont peu évoquées en public. Eric Faye aborde dans son roman Éclipses japonaises (2016) qui s’inspire étroitement de la réalité historique, le sujet des citoyens japonais enlevés par les services secrets nord-coréens, les rachi, phénomène longtemps passé sous silence par les autorités japonaises. En s’attaquant ainsi à des sujets sociétaux brûlants du Japon, Eric Faye (qui a écrit plusieurs romans et essais sur le Japon) et Thomas B. Reverdy, renouvellent par ces thématiques politiques l’approche du Japon par la littérature francophone qui s’était progressivement ouverte aux réalités de la culture japonaise depuis les années 1970.

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)0.002
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.114
Threshold uncertainty score0.226

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0090.005
Scholarly communication0.0040.004
Open science0.0000.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0100.001

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 head0.037
GPT teacher head0.289
Teacher spread0.252 · 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
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 routes1
Has abstractyes

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