Arctic Security, Territory, Population: Canadian Sovereignty and the International
Bibliographic record
Abstract
Abstract Canada's policies to assert and maintain sovereignty over the High Arctic illuminate both the analytical leverage and blind spots of Foucault's influential Security, Territory, Population (2007) schema for understanding modern governmentality. Governmental logics of security, sovereignty, and biopolitics are contemporaneous and concomitant. The Arctic case demonstrates clearly that the Canadian state messily uses whatever governmental tools are in its grasp to manage the Inuit and claim territorial sovereignty over the High North. But, the case of Canadian High Arctic policies also illustrates the limitations of Foucault's schema. First, the Security, Territory, Population framework has no theorization of the international. In this article I show the simultaneous implementation of Canadian security-, territorial-, and population-oriented policies over the High Arctic. Next, I present the international catalysts that prompt and condition these polices and their specifically settler-colonial tenor. Finally, in line with the Foucauldian imperative to support the “resurrection of subjugated knowledges” (Foucault 2003, 7), I conclude by offering some of the Inuit ways of resisting and reshaping these policies, proving how the Inuit shaped Canadian Arctic sovereignty as much as Canadian Arctic sovereignty policies shaped the Inuit.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.017 | 0.023 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".