Bibliographic record
Abstract
We began with Lavinia dehumanized by violence; we end with Macbeth and Lady Macbeth, the perpetrators of violence, humanized. We began with Lavinia unable to name the crime because she has been physically deprived of language; we end with Macbeth and Lady Macbeth unable to name the crime because they are afraid of language. As the ideas of violation and identity develop through these seven tragedies we see a series of reactions and contradictions as one play ricochets against another; and we see an internalization of what in Titus Andronicus is physical and literal. To begin with the contradictions: the physical assault on Lavinia includes taking her identity, which her father restores, claiming she is not just a ruined thing, she is still Lavinia. In the family, she gets her name back. The rape has been a parody of a love-encounter, beginning with conventional love-language. Romeo and Juliet come together in a genuine love-encounter which, if we put the plays together, seems to reverse and heal the violence of Lavinia's rape. While Lavinia's loss of identity is a horror, Romeo and Juliet long for a free space in which they would have no names. The involvement of their families, and of Romeo's friends, for whom their names matter, brings violence into the private world of their love and ends in a second wedding night in which Juliet's blood is shed as Lavinia's was.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.149 | 0.040 |
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".