Terrorists or national heroes? Politics and perceptions of the OUN and the UPA in Ukraine
Bibliographic record
Abstract
This study analyzes controversies and public attitudes concerning the Bandera faction of the Organization of Ukrainian Nationalists (OUN-B), the Ukrainian Insurgent Army (UPA) and Stepan Bandera in Ukraine. The research question is: Which factors affect attitudes toward the OUN-B, the UPA and Bandera in contemporary Ukraine? This article employs comparative and regression analyses of surveys commissioned by the author and conducted by the Kyiv International Institute of Sociology (KIIS) in 2009 and 2013 to determine the effects of regional and other factors on attitudes toward these organizations and the OUN-B leader. The study shows that regional factors and perceptions of these organizations’ involvement in mass murder were the strongest predictors of the views concerning the OUN-B, the UPA and Bandera. Their public support is strongest in Galicia and weakest in the East and the South, in particular, in Donbas and Crimea, two major conflict areas since the “Euromaidan.”
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".