De la filmologie à la sémiologie : figures de l’alternance au cinéma1
Bibliographic record
Abstract
Dans ses premiers travaux sémiologiques, Christian Metz s’est penché sur les divers mécanismes du montage cinématographique, ce dont rend bien compte son fameux tableau de la « grande syntagmatique ». Il s’agit dans cet article d’essayer de comprendre le rôle de ces travaux dans l’histoire de la théorie sur le montage, plus précisément en ce qui a trait aux figures de l’alternance (soit, essentiellement, le montage alterné et le montage parallèle). Les auteurs dressent d’abord un portrait de la « situation définitionnelle » des figures de l’alternance dans les écrits de théoriciens ou d’historiens français des années 1950 et du début des années 1960 (dont Étienne et Anne Souriau, Henri Agel, André Bazin et Jean Mitry), pour mettre ensuite en lumière la manière dont les propositions de Metz ont levé une part importante de l’ambiguïté qui prévalait dans la définition de ces figures de montage, ouvrant ainsi la voie à l’écriture d’une histoire renouvelée du montage alterné.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.017 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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.
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".