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Record W4392662090 · doi:10.3828/bjcs.2024.3

‘I need readers to trust that this <i>can</i> happen’: relational realism in Catherine Bush’s and Doreen Vanderstoop’s climate crisis novels

2024· article· en· W4392662090 on OpenAlexaboutno aff
Petra Fachinger

Bibliographic record

VenueBritish Journal of Canadian Studies · 2024
Typearticle
Languageen
FieldArts and Humanities
TopicContemporary Literature and Criticism
Canadian institutionsnot available
Fundersnot available
KeywordsRealismHistoryLiteraturePolitical sciencePsychologyArt

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.735
Threshold uncertainty score0.935

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.057
GPT teacher head0.247
Teacher spread0.190 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2024
Admission routes1
Has abstractyes

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