Hamlet’s Mobility: The Reception of Shakespeare’s Tragedy in US American and Canadian Narrative Fiction
Bibliographic record
Abstract
This essay presents a comprehensive study of how Hamlet figures in North American fiction. Gabriele Rippl takes her cue from Stephen Greenblatt’s notion of Shakespeare’s ‘theatrical mobility’ (Greenblatt, Cultural Mobility . Cambridge University Press, 2010). This initial mobility, based on the playwright’s own borrowings, appears to facilitate, or even instigate further migrations. Rippl proceeds to give an overview of adaptations of Shakespeare’s Hamlet in the USA and Canada, thus providing an insight into the historical and cultural uses to which the play has been put by authors such as John Updike or Margaret Atwood. Phenomena such as the ‘republicanization’ of Shakespeare (James Fenimore Cooper), or his appropriation for a feminist counter-discourse in Canada circumscribe a space for the negotiation of cultural and political identities. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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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 | 0.003 | 0.004 |
| Science and technology studies | 0.045 | 0.027 |
| Scholarly communication | 0.010 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| 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".