Speculative fictions: contemporary Canadian novelists and the writing of history
Bibliographic record
Abstract
Herb Wyile provides a comparative analysis of the historical concerns and textual strategies of twenty novels published since the appearance of Rudy Wiebe's groundbreaking The Temptations of Big Bear in 1973. Drawing on the work of theorists and critics such as Hayden White, Mikhail Bakhtin, Fredric Jameson, Linda Hutcheon, and Michel De Certeau, Speculative Fictions examines the nature of these novels' engagement with Canadian history, historiography, and the writing of historical fiction. In the 1970s and early 1980s, writers such as Wiebe, Joy Kogawa, and Timothy Findley set the stage for a predominantly postcolonial and postmodern interrogation of traditional conceptions of Canadian history, the writing of history and fiction, and the idea of nation. Through his comparative approach, Wyile emphasizes the ways in which this spirit has been sustained in more recent historical novels by Jane Urquhart, Guy Vanderhaeghe, Tom Wharton, Margaret Atwood, and others. He concludes that the writing of history in English-Canadian fiction over the last thirty years makes a substantial contribution to a revisioning of history and to a postcolonial renegotiation of Canada and Canadian society as we enter into a new century.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.007 | 0.010 |
| Science and technology studies | 0.036 | 0.034 |
| Scholarly communication | 0.019 | 0.005 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".