Bibliographic record
Abstract
Cet article vise à construire un nouveau concept de restauration du film qui se fonde sur l’idée deleuzienne de simulacre. Cette façon de concevoir la restauration se distingue de la visée traditionnelle qui cherche à assurer la réduplication d’un original. Elle entend plutôt préserver le potentiel de métamorphose que possède cet original. S’inspirant du concept deleuzien de l’image-temps, notre essai offre une analyse de la dernière restauration en date de Metropolis de Fritz Lang intitulée The Complete Metropolis. Cette exemple sert ici à explorer certaines formes cinématiques et certains effets de la restauration conçue comme simulacre. Notre article explore tout particulièrement la juxtaposition d’images restaurées numériquement avec des images qui comportent des marques de dégradation physique que l’on retrouve dans The Complete Metropolis. Alors que cette restauration a été critiquée pour la façon dont elle entretient un sentiment de stagnation historique associée paradoxalement à l’accroissement des technologies numériques propre au capitalisme tardif, notre article montre comment la restauration conçue comme simulacre peut permettre de combattre cette stagnation. La restauration cinéma - tographique devient alors potentiellement une forme radicale de cinéma.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 0.008 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 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".