Bibliographic record
Abstract
Clément Paradis reçoit le soutien de l'Arc5 et de la région Auvergne-Rhône-Alpes.1 En 2017, l'historien de la photographie Vincent Lavoie publiait L'Affaire Capa, investigation roborative sur les méthodes d'authentification de la photographie, qui se répartissent pour l'auteur en trois catégories : la parole des témoins, les documents d'archives et l'expertise criminalistique.Ces trois éléments ont un rôle éminemment paradoxal : à travers eux, on cherche à « restaurer la foi en l'authenticité des images tout en refusant la croyance dans le visible ».L'Affaire Capa, notamment grâce à un solide appareil de note, dessinait les contours d'une recherche de fond, celle qui permettrait d'expliquer et de comprendre comment, dans l'histoire occidentale, s'est transformé le statut juridique de l'image photographique et la confiance accordée à ce type de représentation dans sa relation du réel.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.007 |
| Scholarly communication | 0.009 | 0.008 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.027 | 0.009 |
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".