Bibliographic record
Abstract
In Measure for Measure Shakespeare addresses a question that is both straightforward and hard to answer: how do we make people obey the law? Over the course of the play, this simple question gives way to a complex set of problems about human will, political legitimacy, and the origins of sovereign power. Measure for Measure is concerned with illicit activity and ineffective government. But in this comedy—this “problem play”—Shakespeare is especially interested in the political mechanism by which authority and obedience are restored. How is a delinquent population, used to license, brought under control? Shakespeare examines one strategy in this play, one he has seemingly adapted from the Florentine political theorist Niccolò Machiavelli. Multiple critics have recognized that the story of Duke Vincentio and his deviant deputy, Lord Angelo, bear a striking resemblance to the story Machiavelli tells about Cesare Borgia and Remirro de Orco in Chapter 7 of The Prince. Here, I build upon these analyses to offer a new account of Shakespeare’s relationship to Machiavelli and political realism more generally. The Cesare story provides Shakespeare with an opportunity to explore how spectacle and theatricality can be used—not only to subdue an unruly population but to legitimate sovereign authority. However, Shakespeare delves deeper than Machiavelli into the mechanism whereby political authority is reestablished, first by considering the psychological conditions of the Duke’s subjects (both before and during his spectacular display of power), and second, by emphasizing the need for individual citizens to will sovereign authority into being. As we will see, in Shakespeare’s Vienna, order can only be restored once the delinquent people beg to be governed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".