Bibliographic record
Abstract
Neorealist and neoliberal institutionalist explanations for the state and future of the Arctic region dominate the Arctic debate in international relations. While both schools focus on different aspects concerning the current and future state of Arctic affairs – neorealism evokes a confrontational rush for the Arctic’s resources, whereas neoliberal institutionalism propagates the necessary reform of the institutional system governing Arctic issues – both share the underlying assumption of significant and rising stakes towards Arctic commodities. However, this article argues that this debate has hitherto failed to substantiate the actual stakes of the main actors involved. Consequently, many studies make grandiloquent statements about prospects of cooperation and conflict and the appropriate institutional framework for the Arctic region, based on only limited empirical support. This article aims to fill this gap by analysing the Arctic oil and gas interests of the five Arctic littoral states (Russia, USA, Canada, Norway and Denmark/Greenland). The analysis shows greatly different levels of interests towards the High North among the Arctic states. The findings make it possible to make more credible statements about the likelihood of confrontation over Arctic resources and necessary institutional adjustments. The evidence shows that the often-evoked issue of geopolitical rush for Arctic resources is unlikely to eventuate. Nonetheless, there remain institutional challenges for the protection of the fragile Arctic ecosystem.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.008 | 0.011 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".