CANADIAN-RUSSIAN COOPERATION IN THE FIELD OF ARCTIC EXPLORATION IN THE 1990S AND 2000S
Bibliographic record
Abstract
This article describes the interaction between Russia and Canada on the development of the Arctic space. The role of the Arctic in the conditions of an actively changing climate is very important both for the Arctic states that have direct borders with the region and for the whole world in general. The author analyzes the actions of the two countries in the period from the 1990s to the early 2000s. Gorbachev’s reforms, along with the active position of the Canadian government, made it possible to start cooperation on humanitarian issues even before the collapse of the USSR. The 1990s were marked by the active formation of a number of legal agreements on cooperation between Russia and Canada, as well as other Arctic states. In 1996, the Arctic Council was founded, an organization designed to ensure the sustainable development of the region. The progressive improvement of the relations between the two largest Nordic countries began to stagnate after 2006, with the coming to power of the Conservative Party led by S. Harper. The purpose of this article is to analyze the intergovernmental process between the Russian Federation and Canada aimed at the development of the Arctic region. The novelty of this work lies in the fact that, despite the presence in the domestic historiography of the studies on the topic, the article is the first attempt of a generalized scientific research of the Canadian-Russian cooperation in the development of the Arctic.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.010 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".