Restor(y)ing Indigenous Sovereignty in Cherie Dimaline’s Empire of Wild
Bibliographic record
Abstract
A fascinating, multi-layered narrative, Empire of Wild was Indigo’s Best Book of 2019. Love story intersects with the reclamation of Indigenous sovereignty as a Métis woman in search of her lost husband gets in the way of neocolonialist interests. The article looks at how the novel uses the rogarou, a canine-human monster found in French-Canadian and Métis oral traditions, its meanings constructed in different discourses, to restore and ‘re-story’ the Métis in their homeland through the agency of Indigenous womanhood. In discussing the conflict between the main character, Joan, and the man who holds her husband in his power, I endeavor to demonstrate how the novel turns the colonialist discourse of Indigenous savagery on its head, exposes the dynamics of “settler memory” (Kevin Bruyneel), and engages in “re-solution” (Layli Long Soldier) as an act of meaning making from a Métis subject position. Joan’s dual otherness as a Métis (and a) woman reclaims Métis sovereignty through performing it, her (becoming) story—a process of Métis resistance and reemergence.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.015 | 0.015 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".