Bibliographic record
Abstract
This thesis focuses generally on the critically neglected area of stock characterisation in Renaissance history plays. Specifically, it examines the role of stock women characters in these plays, particularly the "wailing woman" type. My readings of three plays - John Bale's <em>King Johan</em>, Thomas Preston's <em>Cambises</em>, and William Shakespeare's <em>King John </em>- challenge typical twentieth-century approaches to them. In addition, I prove that feminist critics in general, though they often refute the assertions of other twentieth-century critics, tend to make the same mistakes as their non-feminist contemporaries in their analyses of female characterisation. While feminist criticisms purport to reassert the importance of female dramatic characterisation, they often discredit female characters' power, even during their identification of it. My thesis redresses these issues, emphasising the essential power of stock characterisation in Renaissance histories and arguing the centrality of "women of woe" in these three plays.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.149 | 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 teacher head, 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".