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Record W1516521952 · doi:10.7202/045149ar

L’horreur post-apocalyptique ou cette terrifiante attraction du réel 1

2011· article· fr· W1516521952 on OpenAlexaffvenue
Richard Bégin

Bibliographic record

VenueCinémas Revue d études cinématographiques · 2011
Typearticle
Languagefr
FieldSocial Sciences
TopicGothic Literature and Media Analysis
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsHumanitiesArtPhilosophy

Abstract

fetched live from OpenAlex

Le film post-apocalyptique plonge le survivant dans une situation où le recours aux références symboliques qui fondent sa culture occidentale s’avère impossible. Dans la « zone » post-apocalyptique, le survivant fait d’emblée l’expérience de la destruction de son monde, tout en étant confronté aux restes matériels et vivants d’une réalité sociale dont l’événement catastrophique n’aura préservé que l’abîme ; cet abîme étant celui du réel tel que l’a théorisé Jacques Lacan. Le réel est ce qui résiste au sens tout en devant sa persistance attractionnelle à une culture qui ne cherche qu’à en refouler la misère essentielle. Le survivant post-apocalyptique erre ainsi dans un avenir indéterminé où se perpétue l’image traumatique d’une culture occidentale désormais impossible. Cette impossibilité constitue le coeur négatif de la réalité sociale, sa part de réel. Le film d’horreur post-apocalyptique institue l’économie narrative de cette impossibilité en personnifiant l’image traumatique de la culture occidentale par l’entremise du zombie, véritable figure refoulée du sujet socialisé. C’est en introduisant ainsi l’abîme dans le registre de l’iconicité que le film d’horreur post-apocalyptique fait le récit d’une impossibilité inhérente à la réalité sociale et sur laquelle repose l’attraction d’une monstruosité originaire et refoulée.

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)0.000
metaresearch head score (Gemma)0.001
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: none
Teacher disagreement score0.032
Threshold uncertainty score0.063

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0040.006
Scholarly communication0.0030.002
Open science0.0000.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0120.001

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 head0.045
GPT teacher head0.269
Teacher spread0.224 · 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

Citations6
Published2011
Admission routes2
Has abstractyes

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