Les catégories de l’exemplarité. La sémiotique des formes de vie au service de la théorie cavellienne des stars
Bibliographic record
Abstract
Parmi les importantes contributions théoriques de Stanley Cavell autour du cinéma, il y a sa conception singulière de la star : de film en film, par ses performances singulières, la star peut être appréhendée comme un exemple de manière d’agir et de vivre, source de spéculation morale. Cette appréhension esthético-morale d’une figure médiatique nous apparait d’une grande actualité – notamment propice aux études sur l’imaginaire cinématographique et social – et, afin d’en permettre le développement, l’enjeu de l’article consiste à en favoriser l’appropriation par des chercheurs en sciences de l’information et de la communication. Nous proposons ainsi un cadrage conceptuel, en faisant dialoguer la théorie cavellienne des stars avec la sémiotique des « formes de vie » (Fontanille ; Perusset). Cette dernière permet de repérer et qualifier des manières d’être et de faire ; son cadrage conceptuel et ses typologies permettront de caractériser les domaines où les stars incarnent un certain modèle d’exemplarité.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.026 |
| Scholarly communication | 0.007 | 0.009 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.011 | 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".