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Record W2520642135 · doi:10.7202/1037084ar

Le dessin ou la vie : parcours d’un deuil dans la bande dessinée Catharsis (Luz, 2015)1

2016· article· fr· W2520642135 on OpenAlexaffvenue
Mouloud Boukala

Bibliographic record

VenueFrontières · 2016
Typearticle
Languagefr
FieldComputer Science
TopicCultural Insights and Digital Impacts
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsHumanitiesArtCatharsisPhilosophyLiterature

Abstract

fetched live from OpenAlex

Le 7 janvier 2015 en fin de matinée à Paris, les frères Chérif et Saïd Kouachi lancent une attaque contre la rédaction de l’hebdomadaire satirique Charlie Hebdo . Cagoulés, vêtus de noir et armés de kalachnikovs, ils déciment la rédaction, faisant douze morts dont huit journalistes. Cet article examine comment Renald Luzier (« Luz »), dessinateur de presse à Charlie Hebdo , se réconcilie avec la mort, la réapprend par le truchement de la bande dessinée Catharsis (2015) . Autrement dit, comment la bande dessinée parvient-elle à donner du sens à une expérience traumatique ? Comment contribue-t-elle, par une expérience graphique, à nouer des liens entre un passé récent indicible, un présent douloureux et un possible futur ? Peut-elle être un moyen de (re)construction de soi ? Autant d’interrogations qui font la matière de ce texte où la bande dessinée n’est pas envisagée comme une illustration à un processus de deuil mais dans ses potentialités symboliques, imaginaires – anthropologiques - où un dessinateur, Luz, vit la mort des autres dans sa propre vie.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.030
Threshold uncertainty score0.060

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0130.017
Scholarly communication0.0070.004
Open science0.0010.004
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0080.001

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 head0.063
GPT teacher head0.272
Teacher spread0.209 · 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

Citations3
Published2016
Admission routes2
Has abstractyes

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