A review of the International Northern Sea Route Program (INSROP) – 10 years on
Bibliographic record
Abstract
The objective of the International Northern Sea Route Program was to create a knowledge bank covering commercial, international shipping on Russia's Northern Sea Route (NSR). Addressed were: considerations of the natural environment, ice navigation, and ship technology; the environment; economics of shipping; and military, political, legal, and indigenous cultural issues. Conclusions included improvements in vessel designs and associated activities represented the safe course for extending navigation. Scientific evidence generally did not exist that civilian navigation had resulted in significant environmental stress; the NSR thus could plan for environmental concerns and avoid devastating impacts. It was necessary for the Russian government to include the NSR in plans for its extractive industries. There were resource commodities well-suited for creating a sustainable cargo flow, but the necessary domestic and foreign investments would have to be provided. The NSR lacked strategic and military importance and held solely civilian, commercial potential. Except for the high seas, the USA would require its commercial vessels to follow the Russian regime, including fees if not discriminatory and for services rendered. For indigenous cultures NSR effects could be both positive and negative; primary was the need to be included in creating the NSR framework and indigenous perspectives viewed and treated equally.
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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 | 0.006 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.011 | 0.017 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".