The Turn to Indigenization in Canadian Writing: Kinship Ethics and the Ecology of Knowledges
Bibliographic record
Abstract
This article heeds the recent shift in cultural criticism and creative writing toward imagining "a functional ecology of knowledges in Canada" (Coleman, "Toward" 8) that takes its conceptual lead from Indigenous epistemologies.Through close reading Thomas King's novel The Back of the Turtle (2014), Wayde Compton's short story collection The Outer Harbour (2014), and Daniel Coleman's nonfiction book Yardwork: A Biography of an Urban Place (2017), the article connects Indigenous notions of kinship to the turn to trans-systemic epistemologies in contemporary Canadian literature and criticism.My analysis draws on Indigenous theories of kinship underlying Indigenous resurgence and decolonization and sets them in conversation with King's reflections on storytelling and world-building, Compton's theoretical charting of African Canadian space as Afroperipheral within diaspora criticism, and Coleman's self-retraining to redefine settler belonging and knowledge.This analysis concludes that, by promoting an awareness of the interdependence between the natural environment, humans, and other-than-human beings that is central to Indigenous epistemologies, these works contribute to the shift toward the construction of an ecology of knowledges and hold the potential for renewed decolonizing efforts, social justice, and environmental sustainability.
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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 | 0.008 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.050 | 0.103 |
| Scholarly communication | 0.018 | 0.007 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 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".