"I'le Tell My Sorrowes Unto Heaven, My Curse to Hell": Cursing Women in Early Modern Drama
Bibliographic record
Abstract
The female characters in Shakespeare’s 2 Henry VI and Richard III; Rowley’s All’s Lost by Lust; Fletcher’s The Tragedy of Valentinian; Rowley, Dekker, and Ford’s The Witch of Edmonton; and Brome and Heywood’s The Late Witches of Lancashire curse their enemies because, as women, they have no other way to fight against the injustices they experience. At once an extension of the early modern belief that words are “women’s weapons,” and dangerously beyond the feminine ideal of silence, the curse, as a performative speech act, resembles the physical weapons wielded by men in its potential to cause serious harm. Using Judith Butler’s theory of gender as performative and J. L. Austin’s theory of performative utterances, this thesis argues that curses function as part of the cursing woman’s performative identity, and by using speech as a weapon, the cursing woman gains a measure of social agency within the social order even if she cannot change her place within it.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.018 | 0.030 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".