Bibliographic record
Abstract
In J. M. Barrie’s final, published version of Peter Pan (1928), the characterization of Hook is vague because of the censorship of plays at that time. Thus, a dramaturgic reading of Hook based on pantomime is mandatory with a survey of the novel, Peter and Wendy (1911), a silent film scenario (1921), and “Captain Hook at Eton” speech (1927). This process evolved the characterization of Hook, washing out its comic part of the original manuscript. Hook became a graduate of Eton and Barrie finally grafted the vestiges of Charles II and Macbeth onto Hook making him a loser of the self-mobilization process for success. This paper aims to investigate the final characterization of Hook by Barrie and provide a guideline for realistic acting of this tragic hero, which is significantly different from that of Peter, a stock character of Harlequin in commedia dell’arte.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.028 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.005 |
| 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".