Bibliographic record
Abstract
Aujourd’hui, de nouvelles pratiques artistiques intègrent des techniques scientifiques liées à la recherche médicale modifiant in vivo les performances biologiques du corps, le transformant en un singulier objet de laboratoire. Ainsi, certains artistes font œuvre de leurs corps en le soumettant à diverses procédures biotechnologiques le plus souvent invasives. Augmenté, le corps biologique de ces artistes-performeurs devient un lieu d’expérimentation. Adeptes du DIY (Do It Yourself) ou accompagnés de biologistes et de médecins, ces « bio-artistes » sont-ils les témoins des changements d’une nouvelle mécanisation du corps humain dont nous commençons à peine à prendre connaissance et dont nous n’avons pas encore mesuré toute la complexité ? Pourrait-il exister, au nom de l’art, des raisons qui justifient la mise en œuvre de corps utopiques, non eschatologiques, et susceptibles de nous faire croire au pire ou au meilleur des mondes ? En prenant appui sur les performances de Stelarc, de Yann Marussich, de Marion Laval-Jeantet et du duo Quimera Rosa, notre propos vise à analyser les enjeux de cette nouvelle fabrique du corps hors de ses limites biologiques.
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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.007 | 0.035 |
| Scholarly communication | 0.013 | 0.011 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.005 | 0.009 |
| Insufficient payload (model declined to judge) | 0.014 | 0.006 |
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".