Sustainable Development Strategies of North American Countries, China and India as a Factor of Security of the Arctic Region
Bibliographic record
Abstract
The Arctic, as an object of modern attention, is a center of attraction not only for Arctic and near-Arctic countries, but also for countries that are located at a fairly remote distance from the Northern Hemisphere. The high interest in the development of the Arctic is caused by geopolitical, economic and other factors. In these conditions, the Arctic becomes a zone of intersection of interests of many countries. The activation and expansion of the economic activity of previously existing and new players in the Arctic can pose both real and potential threats, as well as potential, a new round on the way to improving the level of national security of the Russian Federation in the Arctic region. In this regard, the analysis of foreign Arctic strategies and the study of foreign experience in the development of the Arctic is relevant. The purpose of the work is to analyze the Arctic strategies of the United States, Canada, China, and India for compliance of their national interests with the regional (Arctic) and search for opportunities to use their best practices to ensure sustainable development in Russia. The subject of the study is the mechanisms of management of the development of Arctic and near-Arctic territories. The methodological basis of this study is a systematic, comparative analysis, methods of synthesis, induction and deduction. It is revealed that the models of the policy of supporting the sustainable development of the Arctic of the countries of the North American continent demonstrate ambiguous effectiveness of their implementation. It is shown that the great prospects for supporting the sustainable development of the Arctic contain the emerging and developing models of the state Arctic policy of China and India.
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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 | 0.005 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| 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".