J-Horror: New Media's Impact on Contemporary Japanese Horror Cinema
Bibliographic record
Abstract
Les récents films d’épouvante japonais, connus collectivement sous le terme de « J-Horror », exemplifient le phénomène de la dispersion transnationale d’un cinéma digital multî-médiatîque qui est, paradoxalement, déterminé par des contingences culturelles, industrielles et économiques régionales. Le potentiel véritable du cinéma digital ne se retrouve pas dans les effets spéciaux générés par ordinateur qui apparaissent dans la série Star Wars, mais plutôt dans les mouvements régionaux, comme le « J-Horror », qui renversent le courant traditionel des capitaux et de la culture, c’est-à-dire, le monopole hollywoodien. Ce phénomène n’est pas nouveau dans l’histoire du cinéma. Ce qui le rend unique est le déploiement vernaculaire de sa spécificité médiatique, temporelle et régionale.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".