The Politics of Confinement: Indigenous Homelands, Carceral Imperialism, and the Making of the Deep North
Bibliographic record
Abstract
This dissertation examines Indigenous and settler-colonial geographies and politics, and their relationship to processes of incarceration and other forms of confinement. Anchored in Očhéthi Šakówiŋ history, it examines carceral state formation within a broader analysis of sites that promoted Indigenous geographic and bodily confinement by the U.S. and Canadian settler states during the nineteenth and twentieth centuries. These sites included military forts and jails, reservations and reserves, and boarding and residential schools. The geographic area of the study is a place Indigenous peoples call the Deep North, a cross-border region comprised of hundreds of Indigenous homelands, four U.S. states (Montana, North Dakota, South Dakota, Minnesota), and three Canadian provinces (Alberta, Saskatchewan, Manitoba). This region has the highest rates of Indigenous incarceration on the continent. Using historical and critical methodologies, this project demonstrates that while incarceration of Indigenous peoples in North America resembles the incarceration of other minoritized peoples, it has a distinct historical genealogy that can be traced to coercive colonial practices designed to eliminate Indigenous lifeways, knowledge systems, and tribal identification to dispossess Indigenous lands.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.013 | 0.031 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| 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".