Diana Brydon and Irina R. Makaryk, eds. Shakespeare in Canada: A World Elsewhere
Bibliographic record
Abstract
Co-editors Diana Brydon and Irene Makaryk's claims to offer multi-faceted critically challenging perspectives on the history and reception of Shakespeare in Canada are amply fulfilled in the seventeen diverse chapters reflecting Shakespeare "as cultural icon, exemplary script, or infinitely adaptable medium for local selfexpression" (Preface xi). Indeed, Makaryk's opening chapter outlining the scope of the selections succeeds perhaps too well in problematizing her own question as to whether Canada has been able to recreate a "Shakespeare" that reflects its particular image or simply reinvents our colonial past. As she points out, the chronological arrangement of the chapters grouped into four parts is intended to set up an open-ended dialogue between past and present. A brief commentary on each of the chapters will give the reader some sense of the range of materials that Brydon and Makaryk have included in order to facilitate the debate.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".