Bibliographic record
Abstract
Le présent article s’interroge sur les potentialités narratives d’un média que l’on a tendance à croire guère approprié au récit : la photographie. Peu apte en elle-même, du moins à première vue, à rendre le temps, la narration et surtout la fiction, la photographie souffre encore davantage de la comparaison avec le média nouveau qui l’a « remédié » (au sens de Bolter et Grusin) : le cinéma. L’analyse d’un exemple, une image photographique de Cartier-Bresson qui existe également sous forme cinématographique, montre cependant que, dans certains cas, le pouvoir narratif d’une image fixe peut dépasser celle d’une image mobile. Pour comprendre un tel écart paradoxal, il importe cependant de situer la narrativité sur le plan de la lecture de l’image, et non plus sur celui de ses formes.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".