Bibliographic record
Abstract
Partant de l’évocation de scènes historiques gravées en nous sur le registre de l’onirique, de l’imaginaire ambiant ou encore du trauma, (par exemple, la Grande Guerre, le 11 septembre, Abou Ghraib, etc.), le texte cherche à dégager ce qui constituerait la spécificité d’un théâtre récent de la violence et de certaines de ses voies de frayage. Voies de frayage inédites jusqu’à notre époque, et dont on peut se demander si elles ne contaminent pas le mode du penser contemporain, en contribuant de surcroît à produire une dé-signification de la violence agie, jusque dans le langage du sexuel. Prenant appui notamment sur l’œuvre de Jean Baudrillard, on posera la question de l’emprise du simulacre dans la culture du tournant du xxie siècle et ses impacts sur les processus inconscients. La différenciation, qui semble de plus en plus ténue, entre réalité formelle historiquement advenue, et réalité virtuelle, et « la précession de la réalité par le simulacre » pourraient-elles aller jusqu’à induire chez certains sujets une collusion entre les espaces intrapsychiques de la mise en pensée ?
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.016 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.015 | 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".