Stalin’s Faminogenic Policies in Ukraine: The Imperial Discourse
Bibliographic record
Abstract
Because Stalin’s policy of famine creation in the early 1930s has been viewed through the prism of communist theory and practices, scholars have paid less attention to the imperial/colonial discourse of the period. This essay attempts to show the suitability of applying theoretical models of dependence and imperialism to analyze the dynamics and consequences of the collectivization of agriculture and the Holodomor (the mass deaths through starvation in Ukraine). The pressure applied to all regions of the USSR, resulting from the “communist experiment,” was in Soviet Ukraine supplemented and intensified, and, at some points, determined by a system of centre-periphery relations, characterized by political domination, control, the subordination of regional political elites to the centre, and the exploitation of economic resources. The appropriation of sovereignty over the Ukrainian republic by the central government in Moscow included establishing full control over Ukraine’s food resources, such as determining grain harvesting and distribution. The ongoing exploitation of Ukrainian economic resources and the anti-Ukrainian terror caused the Ukrainian famine of 1928-29. These also became significant factors in the onset of the 1932-33 Holodomor.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.013 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| 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".