<i>Kakaя это дружба</i>/what kind of friendship is this? Russia’s “Crimean Syndrome”
Bibliographic record
Abstract
Russia’s 2014 annexation of Crimea without the consent of Ukraine was a rare case of a state taking territory from a state with whom it previously enjoyed friendly relations. The paper seeks to explain the causes and consequences of this annexation by examining theories of democratic peace, constructivism and irredentism. In 1971, political scientist Myron Weiner published an article “The Macedonian Syndrome” in the journal World Politics (vol. 23, no. 4, 665–683). In particular, the paper examines the applicability of Weiner’s theses to Russia’s 2014 attempt to annex Crimea from Ukraine. While Weiner’s theory helps to explain Russia’s moves, his theory can be updated to consider the consequences of those moves. Russia attempted to justify its annexation by transposing the concept of friendship from Ukraine itself to a piece of its territory – Crimea. This transposition rested on a false dichotomy between Ukraine and Crimea, and Russia’s failure to live up to its international commitments to respect Ukrainian borders brought swift consequences in the form of Western sanctions.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 0.004 |
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".