‘I need readers to trust that this <i>can</i> happen’: relational realism in Catherine Bush’s and Doreen Vanderstoop’s climate crisis novels
Bibliographic record
Abstract
This article demonstrates how, challenged by Amitav Ghosh’s claim that realist fiction is ill-suited to deal with the climate crisis, and inspired by Indigenous relational thinking, Catherine Bush and Doreen Vanderstoop turn to ‘relational realism’ in their recent novels. I argue that they use realist narrative strategies creatively to represent climate catastrophes as a symptom of the carbon economy. But rather than portraying a world that is radically different, Blaze Island and Watershed are concerned with everyday reality, are set in clearly identifiable Canadian geographies, and focus on the eco-anxieties of ordinary characters. In addition to discussing intergenerational climate justice and emphasising the need for Indigenous leadership in combating global warming, the two novels enter into conversation with Shakespeare’s The Tempest and early twentieth-century prairie realist novels respectively to tease out their ecological undercurrents and implications. In so doing, they foreground the interplay of realist narrative strategies and relational thinking to emphasise the creative potential of the novel in addressing climate change and the need for communities to come together to save the planet.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.021 | 0.052 |
| Scholarly communication | 0.014 | 0.008 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.004 | 0.009 |
| Insufficient payload (model declined to judge) | 0.005 | 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".