Securing sustainability: the case for critical environmental security in the Arctic
Bibliographic record
Abstract
ABSTRACT The politics, economies, and ecology of the Arctic region are experiencing fundamental transformation driven largely by human-caused environmental change. Drawing on the work of Robert Cox, this article presents a critical account of environmental security that allows security issues in the Arctic to be reconceptualised. It outlines the environmental changes transforming the Arctic, and theorises the Arctic as a regional environmental security complex in which conditions of security for state and non-state referent objects are predicated on a particular ecological context. It then surveys state- and human security issues in the Arctic, and argues that environmental change has destabilised the ecological base on which the contemporary Arctic as a cooperative region supportive of human activity has been built. The article concludes by outlining alternative ways of conceiving of Arctic security that are more compatible with maintaining the region's ecological base, and suggests that dominant approaches to Arctic security are pathological because they remain premised on the control, extraction and consumption of hydrocarbon resources. It argues that, in the context of the geological Anthropocene, security cannot be sustainable if it fails to address the relationship between human wellbeing and human-caused environmental change, or informs practices that further contribute to environmental change.
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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 | 0.011 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.049 |
| Scholarly communication | 0.011 | 0.008 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.004 | 0.005 |
| 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".