Realist Fantasy and Narrative Decoherence: Decentering the Human in Catherine Bush’s Blaze Island and Thomas Wharton’s The Book of Rain
Bibliographic record
Abstract
For decades now, writers have attempted to grapple with and bring awareness to the growing issues of climate change through works of fiction, so much so that the genre term “cli fi” was coined by writer and journalist Dan Bloom as early as 2007. Still, despite the genre of “climate fiction” becoming increasingly prevalent year over year, there remains little consensus regarding the best approach to represent such a complex and interwoven problem effectively within fiction. From grounded realism to apocalyptic dystopia to speculative fantasy, all perspectives provide pros and cons in attempting to highlight the almost incomprehensively vast realities of climate change, with most running into the issue of being inherently and problematically self-centered. Two recent examples of Canadian climate fiction, Blaze Island by Catherine Bush and The Book of Rain by Thomas Wharton, take on this challenge by resisting a closed off understanding of genre and form, the former melding scientific realism with the magic of Shakespeare’s The Tempest, while the latter blends real-world accounts into a time-bending fantasy narrative. Going even further, both novels manipulate the standard structures of the novel by breaking down expectations surrounding chaptering and other narrative tools. By rejecting individual categorizations and common practices, these novels work to decenter the standard, expected perspectives, giving room for marginalized and non-human voices. Both Bush and Wharton work to unravel the human-centric position that has caused climate change in the first place, inviting their readers to imagine drastic, wonderous, and possibly deeply necessary new ways of seeing and being in the world.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.021 | 0.060 |
| Scholarly communication | 0.013 | 0.006 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.004 | 0.007 |
| 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".