“The old ones that sing to you in your dreams” : an examination of trickster methodology in Eden Robinson’s trickster trilogy
Bibliographic record
Abstract
This thesis examines Eden Robinson’s Trickster Trilogy series through theoretical trickster discourse as opposed to a comparison to the Canadian Gothic. Part of this focus will consider the complications with subsuming distinct Indigenous storytelling practices into Canadian literary categories. One consequence of relying on this form of critique is that it omits the specific and unique histories and ideologies of the Indigenous Nations from which these trickster stories originate. It becomes especially problematic when comparing modern Indigenous stories to the Canadian Gothic due to how Indigenous peoples frequently appear within the Gothic tradition as historical, ghostly, or only from the past. Robinson bases this story on Heiltsuk and Haisla trickster stories to put this story in conversation with the experiences of Indigenous youth in modern-day society. These methodologies are not historical; they necessitate ongoing modernization and comprehension. This ensures these stories function as an activation point for contemporary Indigenous listeners and readers to reflect and reconnect their locality with their distinct cultural values. This thesis will explore how the Trickster Trilogy reinforces Indigenous lifeways, dialogue, and resilience by centering on trickster story methodologies.
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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 | 0.012 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.023 | 0.063 |
| Scholarly communication | 0.013 | 0.008 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 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".