Moscow’s Diplomatic Moves in Montreal: Voting Dilemmas for the ICAO Council
Bibliographic record
Abstract
This article analyses the recent application by the Russian Federation under Article 84 of the Chicago Convention on International Civil Aviation against thirty-seven states for their imposition of airspace restrictions and aviation sanctions on Moscow due to its 2022 invasion of Ukraine. The Kremlin is likely using its application to achieve concessions on the sanctions, however, Russia’s application may test the Council’s ability to approve a decision under Article 84. The dispute highlights the effect of the International Civil Aviation Organization (ICAO) Council’s voting rules which exclude Council members that are a party to a dispute. Examining the history and structure of its voting rules, one that requires a statutory majority for Council decisions, this article proposes several options to alter the ICAO Council’s voting procedures. While the voting procedure can be changed internally through the Council or by amendment to the Chicago Convention, the article concludes with the recommendation that the ICAO Council maintain the current status quo for voting on Article 84 disputes.
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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 | 0.012 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.025 | 0.011 |
| Scholarly communication | 0.014 | 0.004 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.010 | 0.007 |
| Insufficient payload (model declined to judge) | 0.009 | 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".