William J. Shakespeare's Hamlet: An Analysis of Revenge Quest & Procrastination
Bibliographic record
Abstract
In expounding Shakespeare’s Hamlet, a trio of important plots comes to the top with great significance; the revenge plot, the Hamlet-Ophelia romance story, and Norway’s looming war. The trio of significant plots has laid the first stone for Hamlet to procrastinate the act of revenge as it is undone until the final act of Shakespeare’s drama. On the other hand, Hamlet’s playwright gives a picture of the tradition’s direct reference using the literary device Metadrama, i.e. the play within the play exemplified by The Murder of Gonzago. Attaining true justice for his father’s murder, Hamlet beautifies The Murder of Gonzago with grim insistence; Hamlet is determined to recognize the culprit behind the death of his father. Having this uneasy mission comes true causes Hamlet to ponder and slow down about various things. Along these lines, Hamlet goes through a slow decision process to revenge on his father’s murderer. Consequently, various deaths happen, namely: Polonius, Ophelia, Rosencrantz, Guildenstern, Laertes, and Gertrude. Shakespeare’s exposition of various characters incapable of revenging heroically and determinedly draws a picture of Hamlet’s incapability to promptly avenge. Laertes, for example, plots to murder Hamlet to avenge for murdering Polonius, Laertes’s father, and in the last part of this play, Laertes successfully kills Hamlet with the poisonous sword. As various studies focus on the issues of romance, politics, and throne successions using descriptive and historical approaches, this study using the analytical approach, however, demonstrates Hamlet as a play structured on revenge, as the whole revenge events are appropriately incorporated by Shakespeare.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.014 | 0.021 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 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".