Political Villainy on the Modern Stage: Arabic Translations and Adaptations of William Shakespeare’s Richard III
Bibliographic record
Abstract
The following paper explores the rhetorical use of anaphora in William Shakespeare’s Richard III and its impact on the translation of western conceptions of political villains to an Arabic audience. The analysis examines the use of anaphora in Richard’s soliloquies and public speeches that show Richard’s skills in rhetoric aimed primarily at political deception. The Arabic translations and adaptations of the play for contemporary audiences, on the other hand, were received poorly because the Arab world perceives political villains differently. The study proposes that a new translation or an adaptation should be based on an awareness of the historical background and the linguistic differences particular to the Shakespearean play so as to approximate the English model of political villainy for modern Arabic audiences. Key words : Richard III ; Shakespearean play; William Shakespeare; Arabic; English play Resume Le document qui suit explore l’utilisation rhetorique de l’anaphore dans William Shakespeare, Le Richard III et son impact sur la traduction de conceptions occidentales de mechants politiques a un public arabe. L’analyse porte sur l’utilisation de l'anaphore dans soliloques de Richard et de discours publics qui montrent les competences de Richard dans la rhetorique vise principalement a la tromperie politique. Les traductions en arabe et des adaptations de la piece pour un public contemporain, d’autre part, ont ete recues mal parce que le monde arabe percoit mechants politiques differemment. L’etude propose que une nouvelle traduction ou une adaptation devrait etre basee sur une prise de conscience du contexte historique et les differences linguistiques notamment pour la piece de Shakespeare de facon a approcher le modele anglais de la vilenie politique moderne publics arabes. Mots cles : Richard III; Piece de Shakespeare; William Shakespeare; Arabe; Piece en anglais
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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 | 0.004 | 0.005 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".