Re-presenting Genocide: The Canadian Museum of Human Rights and Settler Colonial Power
Bibliographic record
Abstract
Abstract In settler societies like Canada, United States, and Australia, the bourgeoning discourse that frames colonial violence against Indigenous people as genocide has been controversial, specifically because there is much debate about the meaning and applicability of genocide. Through an analysis of the Canadian Museum for Human Rights, this paper analyzes what is revealed about settler colonialism in the nexus of difficult knowledge, curatorial decisions, and political debates about the label of genocide. I specifically examine competing definitions of genocide, the primacy of the Holocaust, the regulatory role of the settler state, and the limits of a human rights framework. My argument is that genocide debates related to Indigenous experiences operationalize a range of governing techniques that extend settler colonialism, even as Indigenous peoples confront existing hegemonies. These techniques include: interpretative denial; promoting an Oppression Olympics and a politics of distancing; regulating difference through state-based recognition and interference; and depoliticizing claims that overshadow continuing practices of assimilation, extermination, criminalization, containment, and forced movement of Indigenous peoples. By pinpointing these techniques, this paper seeks to build on Indigenous critiques of colonialism, challenge settler national narratives of peaceful and lawful origins, and foster ways to build more just relations between Indigenous and non-Indigenous peoples.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.037 | 0.058 |
| Scholarly communication | 0.013 | 0.004 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.014 | 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".