Development of Northern Sea Route: Prospects for International Cooperation
Bibliographic record
Abstract
Today due to global climate change the Northern Sea Route is being formed along the northern coast of Russia as a new international maritime passage in the Arctic. Due to the rapid increase in the interest of regional and non-Arctic states, the scientific community and business to this transportation route, there is a need to study the prospects for cooperation between Russia and other countries on the development of the Northern Sea Route. The paper provides a detailed analysis of the interests of external players in the NSR area, taking into account the latest changes and events, while the author uses swot-analysis and a comparative analytical approach to conduct the study. The results of the study have shown that cooperation with some Arctic countries on the development of the NSR could bring mutual benefits: Canada and Russia would exchange experience on the development of similar sea routes, and Norway and Iceland would receive advantages as hubs on new routes. Non-regional countries, such as China, South Korea, Japan, Singapore and India, are interested in the NSR. For them, the Northern Sea Route is potentially shorter and safer compared to traditional routes, and it also allows to participate in projects located near its water area in science, energy and transport sectors. In turn, the participation of foreign partners is important for Russia, since it is usually accompanied by the active use of the route, the creation of large projects throughout its entire length, the attraction of serious funds, modern technologies and knowledge to the Arctic zone of the country.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".