White settler death drives: settler statecraft, white possession, and multiple colonialisms under Treaty 6
Bibliographic record
Abstract
This article analyzes histories of white settler colonial violence in Treaty 6 territory by arguing that the 1870 Hudson’s Bay Company charter and transfer of Rupert’s Land and the North-Western Territory to the Dominion of Canada helped to make past imperial violence an ongoing settler colonial terror structure into the present. It argues that this transition from imperial to settler colonial control of territory is best understood by using a multiple colonialisms framework, to examine the ways in which heteropatriarchal family structures transitioned from Indigenous-European to white settler kin networks that crystallized whiteness as a racialized means to control land as private property. Following Kanien’kehá:ka feminist scholar Audra Simpson’s work, I suggest that this territory’s multiple and overlapping colonial histories (French, English/British, and Canadian) are a crucial lens through which to understand the historical and ongoing formation of Canada as a white settler state, and that these histories still relationally drive anti-Indigenous violence and the settler killing of Indigenous peoples today. The essay concludes by arguing that the seeming daily placidity of white settler violence against Plains Indigenous peoples under Treaty 6 ultimately supports a relational violence that supports a killing state and its armed citizens in the name of protecting private property for white settlers.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.020 | 0.025 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".