Bibliographic record
Abstract
Chapter 6 is the second part of our analytic narrative. We describe coordination failure by Russian-speaking elites trying to decide whether or not they wanted to try to emulate Crimea. The chapter contrasts the orderly spectacle of irredentist annexation in Crimea with the chaotic “Russian Spring” across Eastern and Southern Ukraine. The existential question was whether the interstate border would change again. The Party of Regions had imploded, so there was no mechanism of transregional cooperation. Dozens of Russian-speaking communities each had to decide locally whether sedition or loyalty to Kyiv would prevail. Russia attempted, but failed, to use a television narrative to encourage established elites in the East to back secessionist uprisings. Sedition did not really get off the ground in most Russian-speaking communities, as pro-Ukraine militias became dominant in the streets. By early May, anti-Kyiv protests died down most everywhere – except in the Donbas.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".