Bibliographic record
Abstract
In 1916, as the adolescent Antonin Artaud was treated for “war neurosis” in a military hospital, he witnessed the birth of modern plastic surgery. These procedures, which rearranged injured bodies in new constellations of flesh and bone, helped to inspire Artaud’s first theatrical foray. “The spectator,” he writes in 1926, “will go to the theater the way he goes to the surgeon.” I argue that literal surgical practice is crucial to Artaud’s surgical metaphors. Plastic surgery revealed to Artaud the body’s plasticity: its capacity to morph, regrow, and heal. While the physical culture movement in interwar France promoted militarized and medicalized models of the body, Artaud used surgical motifs in his plays, poems, and films to explore how physical and mental habits might be dissevered and how they might regenerate. Although Artaud ultimately considered his attempts at theatrical surgery to have failed, I conclude by looking at current applied theatre work with US military veterans, which has been shown to transform participants’ neural networks – performing, as Artaud would put it, a kind of “brain surgery.”
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.029 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".