Bibliographic record
Abstract
Cinema Inferno: Celluloid Explosions from the Cultural Margins addresses significant areas (and eras) of "transgressive" filmmaking, including many subgenres and styles that have not yet received much critical attention. This collection of essays covers both contemporary films and those produced in the last 50 years to provide a theoretical framework for looking at transgressive cinema and what that means. This volume begins with a number of essays that examine the aesthetic of "realism," tracing it through the late Italian Neo-Realism of Pasolini, the early films of Melvin Van Peebles, and Canadian filmmaker Guy Maddin. Another section focuses on '70s Italian horror and thrillers, including a substantially different examination of filmmaker Dario Argento, as well as essays on critically underrepresented directors Lucio Fulci and Sergio Martino. A section on New York looks at both radical independents like Troma and Andy Milligan, as well as the social context from which a view of the metropolis-in-decay emerged. Sections also cover the experimental work of the Vienna Action Group and controversial filmmaker Michael Haneke, as well as films and genres too idiosyncratic and disturbing to fit anywhere else, including analyses of Nazi propaganda films, fundamentalist Christian "scare" movies, and postwar Japanese youth films. The final essays try to come to terms with a mainstream flirtation with "transgressive" film and Grindhouse aesthetics.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.077 | 0.009 |
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".