The Storied North: Reimagining Climate Fiction Through Indigenous Narrative and Knowledge
Bibliographic record
Abstract
This paper argues that Northern Indigenous climate fiction reframes both the Arctic region and the climate crisis, challenging settler-colonial narratives that depict the North as barren, empty, or doomed. Drawing on close readings of Sheila Watt-Cloutier’s The Right to Be Cold (2015), Tanya Tagaq’s Split Tooth (2018), and Waubgeshig Rice’s Moon of the Crusted Snow (2018), I argue that these works position the North as both a literal and symbolic barometer for climate change – an inhabited, storied, and relational space where survival is collective, intergenerational, and culturally grounded. I place these texts in dialogue with dominant, often Euro-American, climate fiction (cli-fi), which reproduces colonial tropes of the Arctic as hostile and unknowable, demonstrating how these narratives advance a counter-vision rooted in Indigenous epistemologies and lived experiences. My analysis foregrounds how Indigenous temporal frameworks – particularly spiralic and cyclical understandings of time – offer a crucial pedagogical intervention, disrupting linear, progress-oriented Western models of crisis and futurity. In Split Tooth, Tagaq’s portrayal of nuna (land) as kin collapses the human–nature divide, while Moon of the Crusted Snow reframes “apocalypse” as a recurrent historical condition rooted in colonization. Both works resist speculative depictions of survival as exceptional or futuristic, instead grounding resilience in ancestral knowledge, ecological reciprocity, and everyday acts of care – while restoring narrative authority to Indigenous communities. This paper draws on scholarship on Indigenous futurisms, decolonial environmental humanities, and the politics of genre, offering a model for reading cli-fi through place-based, Indigenous epistemologies. Ultimately, I argue that by centring Indigenous voices, Northern cli-fi not only challenges extractive and dehumanizing portrayals of the North but also redefines cli-fi itself as a genre of survivance, relational ethics, and collective futurity – offering critical lessons for climate education and conversation today.
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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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.018 | 0.043 |
| Scholarly communication | 0.012 | 0.013 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 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".