Bibliographic record
Abstract
"Occupants of Memory: War in Twentieth-Century Canadian Fiction" examines key novels and short stories about wartime and post-war experience spanning nine decades. Beginning with Sara Jeannette Duncan's The Imperialist (1904) and ending with Timothy Findley's "Stones" (1988), this dissertation juxtaposes works by such well-known Canadian authors as Ralph Connor, Hugh MacLennan, and L.M. Montgomery with lesser-known but important works by William Allister, Charles Yale Harrison, Edward McCourt, and Colin McDougall. Unlike previous studies of Canadian war literature, most of which focus on an individual author, a single war, or a particular theme, this dissertation argues that war fiction is a tradition in which authors influence, reflect, and counter one another throughout the century. Discourses of social memory and nationalism/anti-nationalism provide a theoretical basis for discussion, and descriptions of major events from the South African War, through the two world wars, to the Cold War form an historical context for authors and their works. References to European and American war literature and its critics show Canadian works to be comparable to, yet different from, their international counterparts. Particularly notable is the way in which Canadian works emphasize a dichotomy between romance and realism, rarely broaching the high modernism that is the hallmark of many international works. Occupants of Memory lays the groundwork for a broad critical discourse of Canadian war literature and its related subjects.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.036 | 0.016 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".