<i>Blasted </i>’s Hysteria: Rape, Realism, and the Thresholds of the Visible
Bibliographic record
Abstract
A curious blind spot remains in the critical response to Sarah Kane’s Blasted : the rape of Cate by Ian. In a play famous for its onstage violence, why is this rape, one of its pivotal moments of brutality, left unstaged? My article seeks to worry this lacuna by exploring the theoretical and historical dimensions of the ‘‘missing’’ in Kane’s play. I argue that Kane’s representation of Cate’s rape as missing signals both her engagement with the history of rape’s representation – an elusive, evasive history rather than an outrageous, in-yer-face one – as well as a deft understanding of how the ‘‘missing’’ operates as realism’s menace, the ghost of what realist representations must garrison away in order to instantiate their truth-claims. I frame my reading of Kane’s critique of both genre and history by exploring how Blasted charges us, as contemporary spectators of realism, to recognize the schism between knowledge and the eye, the limits of our powers of sight.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.068 |
| Scholarly communication | 0.013 | 0.006 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".