Shakespeare and the “Cultural Lag” of Canadian Stratford in Alice Munro’s “Tricks”
Bibliographic record
Abstract
Shakespeare and the "Cultural Lag" of Canadian Stratford in Alice Munro's "Tricks"tronI y.Grande Shakespeare should have prepared her. -Alice Munro, "Tricks"A lice Munro has achieved iconic status on the Canadian literary scene and the world stage as the first Canadian to be chosen as a Nobel Laureate in Literature. 1 The Swedish Academy, in awarding Munro the 2013 Nobel Prize, proclaimed her international significance as "master of the contemporary short story" (Bosman 2013).After her eleventh original short-story collection, Runaway, was published in 2004, Jonathan Franzen (2004) called Munro "the best fiction writer now working in North America."Despite her retirement in 2012, Munro continues to spark a major industry in Canadian publishing, writing, and literary studies.Munro's literary allusiveness has been discussed by Ildikó de Papp Carrington (1989) and others, while more biographically focused critics such as Robert Thacker (2011) have pointed out the numerous parallels between Munro's work and her life experiences in small-town southwestern Ontario.No one, however, has examined Shakespeare's embedded presence in Munro's (2004) short story "Tricks." 2 Less than an hour's driving distance from "Alice Munro Country" (her "home place" in Huron County, as Thacker [2011, 463] puts it), the Ontario town of Stratford becomes a moving force in "Tricks," shaping the female protagonist's ironic quest to achieve a conventional comic ending.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.037 | 0.030 |
| Scholarly communication | 0.011 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.016 | 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".