Bibliographic record
Abstract
AARON, 25 ans, est un programme informatique, doté d’une intelligence artificielle qui peut faire des dessins à main levée. Il a été développé par Harold Cohen, un peintre expressionniste abstrait anglais. En 1968, ce dernier s’intéressait à l’intelligence artificielle et faisait de l’ordinateur le véhicule principal de sa démarche artistique. Dans les années 70, les images d’AARON se limitaient à des dessins géométriques abstraits et, vers le milieu des années 80, son programme « cognitif » s’élargissait pour inclure la reconnaissance de la morphologie humaine et végétale, permettant ainsi de produire des dessins à main levée de gens évoluant dans des environnements de jardins. Cet article retrace le développment conceptuel d’AARON par le biais de sa biographie, il explore les aspects spécifiquement masculins qui sous-tendent le programme et examine les implications de cette désignation sexuelle dans la construction des modèles théoriques de ce champ artistique en émergence.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.005 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.022 | 0.005 |
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".