Bibliographic record
Abstract
Abstract This chapter analyzes the role of Russia, Crimean separatists, the Ukrainian government, the far right, and the West in the Russian annexation of Crimea in spring 2014. It examines interviews, videos, public opinion polls, and media reports in Ukrainian, English, and Russian. The analysis shows that the conflict in Crimea involved both secession and Russian annexation with help of covert Russian military intervention of this predominantly ethnic Russian region of Ukraine and the Russian Black Sea fleet base. Polls suggest that most Crimean residents supported this, and there was strong separatism in the Crimean autonomy. However, the Russian annexation with help of the military intervention played a greater role and represented conflict spiral escalation, primarily, in response to the violent overthrow of the pro-Russian government during Euromaidan in Ukraine with the US involvement. Many Russians and Russian politicians regarded this region of Ukraine as historically Russian. The overwhelming majority of countries did not recognize the unilateral secession and the illegal Russian annexation of Crimea. Narratives propagated by the Russian, Ukrainian, and Western governments and the media and, especially, Wikipedia misrepresented different elements of the 2014 Crimean conflict. The Russia-Ukraine war affected Crimea, but it is virtually impossible that Ukraine can take back this region.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".