Stalinist Perpetrators on Trial: Scenes from the Great Terror in Soviet Ukraine, by Lynne Viola
Bibliographic record
Abstract
In February of 1938 in Chernigov, Ukrainian Soviet Socialist Republic, a concerned regional official approached Nikolai Ivanovich Ezhov, the People’s Commissar of the Soviet Union’s fearsome Narodnyi Komissariat Vnutrennikh Del (NKVD). In a recent roundup of local “potential enemies” of Soviet power, the man was unsure of what to do with the “invalids” and elderly peoples who happened to fall among the arrested. Seemingly irritated by this inquiry, Ezhov shot back at him blithely: “Ekh, you are a Chekist! Take them all to the woods and shoot them.” This haunting exchange provides a real glimpse at some of the callous indifference driving the infamous Great Terror—the widespread Soviet imprisonment and execution of perceived “Fifth Columnists”—across the Soviet Union between 1936–38, and is one of many illustrated in Lynne Viola’s Stalinist Perpetrators on Trial: Scenes from the Great Terror in Soviet Ukraine. This work studies in detail an under-explored dimension of the Great Terror: the secret trials and purges of the very NKVD operatives that carried out the Great Terror, who found themselves, in a stunning reverse of fortune in late 1938, on the other side of the interrogation table. This reversal turned out to be a successful tactical ploy by Stalin, enabling the leader to both celebrate and take credit for the successes of the Terror while scapegoating the NKVD for the increasingly public atrocities that were committed under his direction. Because of the secrecy of this “purge of the purgers,” the real stories behind the perpetrators of the Great Terror remained shrouded in mystery for much of the twentieth century.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.030 | 0.009 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.005 | 0.012 |
| Insufficient payload (model declined to judge) | 0.003 | 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".