Re-presenting Shylock: An Examination of Post-Holocaust and Adaptation in The Merchant of Venice Play and Film Adaptations
Bibliographic record
Abstract
This paper examines the depiction of Jews, particularly the character of Shylock, in William Shakespeare's The Merchant of Venice in comparison with those of two adaptations: Arnold Wesker's play The Merchant and Michael Radford's film The Merchant of Venice. Shakespeare's original work has been the subject of much scholarly discussion, with some perceiving it as perpetuating negative stereotypes and others as offering a nuanced and complex view of the character. Wesker's adaptation reinterprets the portrayal of Jews to challenge the negative representation in Shakespeare's play, highlighting themes of love, family, and relationships. Radford's film, on the other hand, offers a more nuanced and dynamic portrayal of the Jewish community than we are used to seeing in representations on film, and sheds light on the impact of anti-Semitic prejudice. It focuses on highlighting the Jewish/Christian disagreement and the extent to which Jews are victimized in Shakespeare's play, using filmic techniques to create a powerful representation with a deeper understanding of justice, discrimination, and dehumanization. Both adaptations offer a more nuanced portrayal of the Jewish community and challenge negative stereotypes perpetuated by Shakespeare's original work.
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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 | 0.011 | 0.014 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".