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Record W1585590194 · doi:10.4000/entrelacs.1103

Vox post-mortem, poétiques de la disparition après le 11 septembre 2001

2014· article· fr· W1585590194 on OpenAlexaff
Vincent Souladié

Bibliographic record

VenueEntrelacs · 2014
Typearticle
Languagefr
FieldArts and Humanities
TopicContemporary Literature and Criticism
Canadian institutionsCanadian Heritage
Fundersnot available
KeywordsPoeticsArtLiteratureMedicinePsychoanalysisPsychologyPoetry

Abstract

fetched live from OpenAlex

Dans son court-métrage réalisé à l’occasion du film collectif 11’09“01 - September 11 (2002), le réalisateur mexicain Alejandro Gonzales Iñárritu élabore un dispositif visuel et sonore multi-référentiel. Tout au long des onze minutes et neuf secondes que dure le film, l’écran reste presque intégralement noir. Notre attention est alors focalisée sur le mixage prédominant : un entrelacs acoustique réunit un crescendo de voix hétérogènes, de plus en plus nombreuses, de plus en plus intenses, jusqu’à créer une musique verbale lancinante. Nous pouvons rapidement reconnaître cette cacophonie comme étant un assemblage de véritables archives sonores du 11/9 (commentaires des présentateurs télévisés, témoignages d’anonymes ou messages post-mortem des défunts, enregistrés sur répondeurs). En résistance à la profusion des images médiatiques, Iñarritu semble chercher à employer cette matière phonique pour leur substituer des images intérieures et personnelles. Mais cette poétique de la disparition est-elle seulement en mesure de mettre à nu la réalité sous la robe du visible, ou bien l’esthétisation du montage vocal désincarne-t-il encore autrement la violence de l’événement ?

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)0.003
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: Other · Consensus signal: none
Teacher disagreement score0.023
Threshold uncertainty score0.056

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0080.003
Scholarly communication0.0030.002
Open science0.0000.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0170.003

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 head0.012
GPT teacher head0.224
Teacher spread0.212 · 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
GenreOther

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
Published2014
Admission routes1
Has abstractyes

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