Retelling Old Stories with New Media: National Identity and Transnationalism in the “Russian Spring” Popular Uprisings
Bibliographic record
Abstract
The ongoing armed conflict in Ukraine was preceded by pro-Russian uprisings in major cities in the east and south of the country. These uprisings, sometimes referred to as the “Russian Spring,” were a reaction to the success of the Euromaidan, which ousted President Viktor Ianukovych. The downfall of his pro-Russian regime, coupled with aggressive propaganda, created an outrage that culminated in thousands of protesters taking to the streets. Their demands were justified by distinct “imaginings” of Ukraine’s and Russia’s national identities. The Anti-Maidan—a pro-Russian movement—actively utilized social media in order to promote its vision of Ukraine’s future, past, and present. This paper investigates articulations of national belonging by the Anti-Maidan. Its findings reveal that the Anti-Maidan’s national “imagination” is represented by a bricolage of Soviet and Slavic symbols and advocates non-progressive changes.
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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 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.008 |
| Scholarly communication | 0.010 | 0.009 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".