(Re)Writing Canadian Space: Dystopian Geographies in Larissa Lai’s Salt Fish Girl and M.G. Vassanji’s Nostalgia
Bibliographic record
Abstract
This paper examines how dystopian fiction opens up a productive space for disrupting naturalized assumptions, and shifting our understanding of taken-for-granted spaces. Drawing on Doreen Massey’s (2005) proposal that space must be seen as the product of constant interrelations, I argue that dystopian literature can similarly prompt us to reconsider our relationship to the spaces we inhabit. Using the concept of the “critical dystopia,” I examine how dystopian frameworks are operationalized in the Canadian context through a comparative analysis of two novels that speculate distinctly Canadian dystopian futures: Larissa Lai’s Salt Fish Girl (2002) and M.G. Vassanji’s Nostalgia (2016). By applying Massey’s theorization of space—its multiplicities, complexities, and political potentialities—to an examination of how Canadian spaces are transformed in the dystopian context, I then analyze how those representations challenge the spatial ideologies associated with globalization, and resist the neoliberal view of space as a surface to be crossed and conquered (Massey, 2005).
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".