Settler governmentality in Canada and the Algonquins of Barriere Lake
Bibliographic record
Abstract
Abstract In September 2009, Canadian Prime Minister Stephen Harper declared to the global media that Canada had ‘no history of colonialism’. Such expressions of the post-colonial Canadian imaginary are common, despite Canada’s dubious legacy of settler colonialism. This article uses Canada’s Access to Information Act to examine how mechanisms of security are mobilized against members of the Algonquins of Barriere Lake (ABL), whose persistent calls for sovereign control of their land and customary governance system have been translated by Canadian authorities into a security threat to settler society. Contributing to the literature on postcolonialism, as well as works on critical security studies and colonial governmentality, this article suggests that distinct rationalities underline colonial activities in settler states. The authors contend that the term ‘settler governmentality’ is more appropriate for settler states such as Canada, and they present the case study of the ABL to argue that (in)security governance of indigenous groups in Canada incorporates techniques that are necessarily grounded in a logic of elimination. The authors detail how an analysis of the interventions in the traditional governance of the ABL contributes to understanding recent security trends regarding ‘Aboriginal extremism’ and indigenous ‘hot spot’ areas in Canada, which are often framed as matters of ‘national security’.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.021 | 0.011 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".