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Record W2140359649

Profane, Steal, or Usurp: Kingship, Divine Right, and Regicide in Shakespeare's Macbeth and Richard II

2014· article· en· W2140359649 on OpenAlexaff
Rachael Hencher

Bibliographic record

VenueVerso: An Undergraduate Journal of Literary Criticism · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicAmerican Constitutional Law and Politics
Canadian institutionsDalhousie University
Fundersnot available
KeywordsAdmirationTragedy (event)PhilosophyAsideMonarchyWitnessPower (physics)RulerLiteratureArtLawPolitical science
DOInot available

Abstract

fetched live from OpenAlex

A year ago Rachael Hencher was a student in my Shakespeare class (English 2214X/Y). The term paper she wrote in the second term was the first draft of the essay she presents here under the title, “Profane, Steal, or Usurp.” Those three words by themselves are a clever indication of the problem Rachael has identified, namely, how do you change the government in a society accustomed to monarchy, and where monarchs believe (or at least say they believe) they are anointed by God and rule by divine right? Rachael shows with great subtlety how and why this question is troublesome when we’re interpreting a tragedy like Macbeth or a history play like Richard II. The essay she has written speaks for itself, and all I can do here is recommend it to you. And I can add, with admiration, that Rachael remains firmly aware of the differences which separate the two texts she is studying. “In Macbeth ,” she writes in her final paragraph, “the audience sees a man of certain ambition rise to the greatest heights of power by compromising his conscience, only to be torn down due to his illegitimate claim”; in Richard II , by contrast, we witness a struggle between “a legitimate king who is a weak ruler, and an illegitimate usurper who is a strong leader.” What Rachael’s analysis offers us is an appreciation of Shakespeare’s willingness to wrestle with these ambiguities. Dr. Ronald Huebert

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.851
Threshold uncertainty score0.615

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.021
GPT teacher head0.307
Teacher spread0.286 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueVerso: An Undergraduate Journal of Literary CriticismSame topicAmerican Constitutional Law and PoliticsFrench-language works237,207