Wonderworks in Canadian Indigenous Literature: The Case of Tanya Tagaq's Split Tooth
Bibliographic record
Abstract
This thesis explores the concept of "wonderwork," as defined by Canadian writer and literary critic Daniel H. Justice, within the context of the novel Split Tooth (2018) by contemporary Inuit author Tanya Tagaq. Wonderwork, a genre offering a fresh perspective on Indigenous speculative fiction, blends reality and unreality, rejects colonial stereotypes, and envisions a future distinct from the settler-colonizer narrative. This study examines the specific characteristics of wonderworks and how they are reflected in Tagaq's novel. The analysis utilizes a decolonial framework that prioritizes Indigenous perspectives. By conducting a close reading of Split Tooth, supported by Justice's theoretical writings and relevant scholarly sources on Indigenous and Inuit literature, this thesis demonstrates that the novel successfully exemplifies the genre of wonderwork. Split Tooth combines prose, poetry, and visual elements to narrate the coming-of-age story of a girl in 1970s Nunavut, Canada. The novel merges "the real" and "the unreal" elements into a unified narrative. The protagonist's interactions with natural and spiritual forces, such as the Northern Lights, mirror her experiences in the realistic setting of the Arctic region. This interplay reinforces the novel's cohesive structure. By portraying...
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.061 | 0.032 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| 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".