US and Canadian Sanctions Against the Russian Federation in the Field of International Scientific Cooperation: Political and Legal Analysis
Bibliographic record
Abstract
The article provides a political and legal analysis of the US and Canadian sanctions against the Russian Federation in the field of international scientific cooperation. The classification of sanctions in the field of S&T cooperation is given. It is noted that by their nature, such sanctions threaten not only the national security and the level of technological development of Russia, but also significantly limit the universal tasks of solving global problems. Obviously, in the concept of open science and global interdependence, any scientific sanctions have a boomerang effect, since they limit not only Russia, but also other states, scientists, academic and educational organizations in cooperation to solve common problems. The authors draw the following conclusions: these sanctions do not have sufficient legal grounds; the consequences of their application are not normatively defined, so the gap in this part can be resolved on the basis of both the general principles of international law and by fixing in international agreements the consequences of a unilateral refusal to fulfill obligations (compensation for losses caused, distribution of risks and financial obligations); sanctions of this kind should not apply to individual scientists, since the channels of scientific communication act as an element of soft power and contribute to the removal of political differences (scientific diplomacy); the desire of the Russian authorities under the sanctions to diversify scientific and technical ties with other states of Asia, Africa, and Latin America is completely justified.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.019 | 0.006 |
| Scholarly communication | 0.008 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".