Truth before reputation: an analysis of Canadian political discourses on settler-colonialism and genocide in China and Canada
Bibliographic record
Abstract
The discovery of 215 potential unmarked graves at the former Kamloops Indian Residential School in May 2021 sparked one of the last big debates on settler colonial genocide in Canada. On June 10, 2021, NDP MP Leah Gazan presented a motion to declare the Indian Residential School System (IRSS) genocide. However, it did not gain unanimous consent as politicians from several political parties voted against it. This was surprising as only a few months earlier Parliament had voted to recognize the ongoing Uyghur crisis in China genocide. What made this recognition significant was that several processes of group destruction that were part of the IRSS are evident in the Uyghur crisis, and several politicians even identified Uyghur destruction as settler-colonial in nature. The questions remain: why did Canadian politicians view settler-colonialism in China as a process of genocide, while avoiding this label for settler-colonialism in Canada? And what discursive strategies did they employ to highlight genocide in one context while minimizing it in another? Using the frameworks of conceptual constraint and “blame games,” this thesis examines how Canadian politicians portray China as a stereotypical “Villain” nation while upholding Canada as a “Hero” nation. It will also show how these views are maintained in the public sphere, and why we need to continue to monitor this latter discourse despite the Canadian House of Commons finally recognizing the IRSS as a genocide in October 2022.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".