Sovereignty Through Security? Canada's Arctic Defence in the Surveillance Age
Bibliographic record
Abstract
This project considers how materials, practices and semiotics align and structure the development and use of security technologies in the Canadian Arctic. The dissertation asks: does the development of new technologies geared towards surveillance of the Canadian Arctic represent a new approach to security in the North? \n \nIt is argued that current technological developments are grounded in a particular sociotechnical imaginary that is at once predicated on historical state practices while drawing from a more comprehensive assemblage of modern state strategies that are refracted through a lens of futurity. Notably, how the Arctic is understood and rationalized as a space of social and political life is dependent on a uniquely securitized image of the future. Within this imaginary, the Canadian state's rhetorical claims to sovereignty are threatened by the potential for competing expressions of power enabled by climate change, technological diffusion, and other trends at the international scale. Consequently, technologies developed for surveillance, intelligence, and Arctic security more broadly are designed to support practices of pre-emption as techniques of state power. \n \nCanada is prioritizing technological innovation as a governance strategy designed to rationalize and consolidate its power over its Arctic territory. Broadly, this strategy is predicated on illuminating the Arctic using the visible and non-visible spectrums, which contributes to sovereignty as a rhetorical, material, and symbolic signifier of state power and control. In order to demonstrate the interplay between this imaginary and material expressions of state sovereignty, the concept of full-spectral dominance is deployed as a technique of power that captures the state's security ambitions through the joint practices of surveillance and intelligence (sensing). This concept is illustrated through an examination of current technological developments being pursued by the Canadian state through the All Domain Situational Awareness (ADSA) Program led by National Defence along with related programs and developments. In sum, these developments exhibit how increasingly imaginative views of the Arctic’s future contour state-led practices in the present.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.031 | 0.024 |
| Scholarly communication | 0.018 | 0.005 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".