Arctic (in)security and Indigenous peoples: Comparing Inuit in Canada and Sámi in Norway
Bibliographic record
Abstract
Abstract While international relations has increasingly begun to recognize the political salience of Indigenous peoples, the related field of security studies has not significantly incorporated Indigenous peoples either theoretically or empirically. This article helps to address this gap by comparing two Arctic Indigenous peoples – Inuit in Canada and Sámi in Norway – as ‘securitizing actors’ within their respective states. It examines how organizations representing Inuit and Sámi each articulate the meaning of security in the circumpolar Arctic region. It finds that Inuit representatives have framed environmental and social challenges as security issues, identifying a conception of Arctic security that emphasizes environmental protection, preservation of cultural identity, and maintenance of Indigenous political autonomy. While there are some similarities between the two, Sámi generally do not employ securitizing language to discuss environmental and social issues, rarely characterizing them as existential issues threatening their survival or wellbeing. Drawing on securitization theory, this article proposes three factors to explain why Inuit have sought to construct serious challenges in the Arctic as security issues while Sámi have not: ecological differences between the Canadian and Norwegian Arctic regions, and resulting differences in experience of environmental change; the relative degree of social inclusion of Inuit and Sámi within their non-Indigenous majority societies; and geography, particularly the proximity of Norway to Russia, which results in a more robust conception of national security that restricts space for alternative, non-state security discourses. This article thus links recent developments in security studies and international relations with key trends in Indigenous politics, environmental change, and the geopolitics of the Arctic region.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.010 | 0.004 |
| Scholarly communication | 0.003 | 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".