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Record W7056636717

Grand-Guignol cinema and the horror genre sinister tableaux of dread, corporeality and the senses

2023· other· en· W7056636717 on OpenAlexaffabout

Bibliographic record

Venuenot available
Typeother
Languageen
FieldEngineering
TopicParticle accelerators and beam dynamics
Canadian institutionsJohn Abbott College
Fundersnot available
KeywordsMovie theaterScholarshipPsychoanalytic theoryPeriod (music)Key (lock)Affect (linguistics)
DOInot available

Abstract

fetched live from OpenAlex

Grand-Guignol Cinema and the Horror Genre traces important contributions of the Parisian Grand-Guignol theatre's Golden Age as theoretical considerations of embodiment and affect in the development of horror cinema in the twentieth century. This study traces key components of the Grand-Guignol stage as a means to explore the immersive and corporeal aspects of horror cinema from the sound period to today. The book is a means to explore the Grand-Guignol not only as a historical place and genre, but also, theoretically, as a conceptual framework that opens up an affective mapping of Grand-Guignol attractions in cinema. This study's restoration of a long Grand-Guignol tradition in cinema makes it a significant contribution to new theorizations of horror. It brings seemingly disparate traditions into conversation, as American, Canadian, French, and Italian cinema are all important sites for thinking through cinematic embodiment. These four countries have developed their own important genres and movements of Grand-Guignol cinema: the slasher, the 'French Films of Sensation,' Canadian 'body horror' and the giallo. The Grand-Guignol famously operated in a dead-end of Chaptal Street, in the Pigalle district of Paris; this study offers affective and corporeal readings that open up new byways beyond the dead-end of psychoanalytic readings that continues to be dominant in horror genre scholarship

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)0.001
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: Other
Teacher disagreement score0.019
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0030.010
Scholarly communication0.0050.002
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.000

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 head0.011
GPT teacher head0.212
Teacher spread0.201 · 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
Published2023
Admission routes2
Has abstractyes

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