Dead Center: Tragedy and the Reanimated Body in Marina Carr’s <i>The Mai </i>and <i>Portia Coughlan</i>
Bibliographic record
Abstract
If, as Martin Esslin argues, the actor’s body is the “iconic sign par excellence:a real human being who has become a sign for a human being” (56), what happens to an audience’s experience of the theatrical event when the central such sign of the drama, the body of the hero, “dies” in the middle of the play? “A corpse on stage” quite obviously “demands attention” (Swander 139), much more so when the corpse in question is that of the title character. Yet a dead body on stage, which is, after all, not in fact dead, can be reanimated, and doing so, either through a disruption of linearity or through the dramatic presentation of an afterlife, testifies to the vitality and malleability of the theatrical experience. In attempting to represent “death,” the bodily sign implies a chronological endpoint, a culminating stillness that provokes analytical engagement: like the conclusion of any motion, “the stillness thus draws […] the attention of the spectator […] and calls for some effort either of aesthetic appreciation or interpretation” (McAuley 106–07). Stillness and motion define one another, and later motions of the “revived” body must always be read though the audience’s remembrance of the character’s ultimate conclusion, as if the theatrically animated figure becomes a trace of its own imaginatively extinguished self.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.038 | 0.039 |
| Scholarly communication | 0.013 | 0.006 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.005 | 0.009 |
| Insufficient payload (model declined to judge) | 0.010 | 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".