Bibliographic record
Abstract
"Enter the Man" is a study of representations of sexual violence that focuses on the trope of male/male rape as it has gained prominence as a linguistic and cultural metaphor in USAmerican, British, and Canadian society. This dissertation attempts to disaggregate the assumptions that adhere to representations of male/male rape, and to discuss the various uses to which representations of male/male rape have been asked to work by artists working in theatre, film, literature, and television. "Enter the Man" uses gender theory, queer theory, theories of violence, and trauma theory, to explore why male/male rape has become a popular literary, theatrical, and cinematic trope within Anglo-American media. "Enter the Man" is also a history text, detailing and analyzing the development of this trope. The dissertation follows a chronology of these representations beginning with the productions of Canadian dramatist John Herbert's playFortune and Men's Eyes. This document also considers James Dickey'sDeliveranceboth as a book and in its film version. Other texts analyzed include Miguel Piñero'sShort Eyes, Rick Cluchey'sThe Cage, John Schlesinger'sMidnight Cowboy, and Howard Brenton'sThe Romans in Britain. "Enter the Man" ends with the new movement of British playwriting in the 1990s with an examination of Anthony Neilson'sPenetrator, Sarah Kane'sBlasted, and Mark Ravenhill'sShopping and Fucking.
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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 | 0.001 | 0.003 |
| 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 | 0.004 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.176 | 0.054 |
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".