Explaining Inconsistencies in Shakespeare's Character Henry V on the Basis of the Emotional Undertones of His Speeches
Bibliographic record
Abstract
Shakespeare's character Henry V is infamous, among 20th-century analysts of drama, for his inconsistent disposition. Some analysts highlight this character's reformation and others his Machiavellian tendency to moderate his disposition in tune with changing situations. The Dictionary of Affect in Language (Whissell, 2009) was used to score the emotional undertones of words in Henry V's dialogue. Analyses of these undertones, described in terms of Pleasantness and Activation, demonstrated that the character Henry V was, in overall terms, emotionally average, that there was minimal evidence of growth or reform in him across time, and that situational factors (e.g., revelry, kingship, courtship, battle) were associated with the dramatic changes in his speeches. The character employed more passive language in private and personal situations and more active language in his (public) royal role. Four categories of Henry V's speeches (Condescension, Control, Self-definition, and the Courtship of Good Opinion), represented in both public and private discourse, reflected increasing pleasantness in emotional undertones.
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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 | 0.001 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".