La migration de l’aura ou comment explorer un original par le biais de ses fac-similés
Bibliographic record
Abstract
En prenant l’exemple de la duplication par l’intermédiaire de techniques numériques des Noces de Cana de Véronèse et de son accrochage dans son lieu palladien d’origine à San Giorgio à Venise, les auteurs envisagent la possibilité d’un détachement de l’aura par rapport à l’oeuvre originale. Grâce aux nouvelles techniques de fac-similisation, l’aura pourrait s’attacher à l’une ou l’autre des reproductions selon la qualité de ce que l’on peut considérer être les versions d’une oeuvre et selon la réussite de leur inscription dans un lieu particulier. Selon cette nouvelle logique, parallèle à celle des arts performatifs, l’oeuvre originale ne serait plus qu’une matrice première, l’origine d’une longue lignée de reproductions qui viendrait l’actualiser. Et dans la mesure où tous les originaux devraient être reproduits pour « survivre », il importera désormais de savoir distinguer les bonnes des mauvaises reproductions.
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 | 0.002 | 0.005 |
| 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 | 0.014 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.017 | 0.003 |
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".