Grand-Guignol cinema and the horror genre sinister tableaux of dread, corporeality and the senses
Bibliographic record
Abstract
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
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.010 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".