Risk, Mortality, and Memory: The Global Imaginaries of Cherie Dimaline’s The Marrow Thieves, M.G. Vassanji’s Nostalgia, and André Alexis’s Fifteen Dogs
Bibliographic record
Abstract
This paper examines three contemporary Canadian novels that depict global risk society through a speculative fictional form that asks the question "What if?" Cherie Dimaline's The Marrow Thieves (2017) and M.G Vassanji's Nostalgia (2016) imagine dystopian worlds ravaged by climate change to critique humanist ideals of Progress.André Alexis's Fifteen Dogs (2015) uses the animal fable to address what it means to be a mortal animal.Each asks what an awareness of risk means for agency and ethics: for Indigenous people in The Marrow Thieves; for Torontonians in the context of a heightened global apartheid in Nostalgia; and for dogs wrestling with a god-granted human intelligence in the contemporary Toronto of Fifteen Dogs.In negotiating risk, each fiction turns to the roles of memory, creativity, and alternative forms of subjectivity and community in ensuring survival.Each novel finds fragile yet necessary steps toward alternative futures in the ability to imagine otherwise.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".