Power through humour: Thomas King's strategies for decolonizing Canada
Bibliographic record
Abstract
This dissertation is about power, humour and various comic and ironic strategies contemporary Native writers and artists apply in their works to challenge the outdated Indian stereotypes and obsolete systems of cultural and aesthetic representation. The artists employ a combination of comedy and irony as favoured modes of expression in order to contest, subvert and critically deconstruct the oppressive hegemonic ideologies and power structures still present in Canada and the United States. Their novels, poetry, essays, films, documentaries, theatre performances, paintings and other works of art strive to emphasize the marginalization and rights of all Native people in North America who have suffered over the hundreds of years of colonization, acculturation and violent cultural appropriation. In the last decade, there have been growing calls from academia, Native communities as well as the government, to reconceptualise the bi-cultural politics between the First Nation peoples and the Canadian nation-state. A great amount of models for an inclusionary and multifaceted identity politics have been proposed by several Canadian cultural analysts and critics, including for example Diana Brydon, Smaro Kamboureli, and Lily Cho. However, before they can be successfully implemented, a creation of an alternative space...
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.054 | 0.021 |
| Scholarly communication | 0.011 | 0.004 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.008 | 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".