Dnipropetrovsk Oligarchs: Lynchpins of Sovereignty or Sources of Instability?
Bibliographic record
Abstract
The choices made by oligarchs and citizens in Dnipropetrovsk during and after the Euromaidan rebellion of 2013–14 were not just event-driven manifestations in response to domestic and internal pressures. They were responses shaped by historically-composed social structures and interrelationships forged over decades within the region, across southeastern Ukraine, and in relation to competing centers of power—in Kyiv, Moscow, Washington, Brussels and beyond. This paper argues that Dnipropetrovsk—and its leaders—played a crucial intermediary role in not only deescalating tensions in southeastern Ukraine more broadly, but also by buttressing the Ukrainian state in a time of existential crisis. In this analysis, oligarchic self-interest is taken as a given and one factor among many, including the signaling of interventionist intent from an external patron and also deeper, regionally specific, economic and structural forces. This piece brings into the analysis a historian’s understanding of contingency, arguing that analyses of developments in southeastern Ukraine (in the past and present) should strive to better situate regional actors not only in space but also time, so as to better understand the complex set of forces and heterogenous social temporalities shaping their choices.
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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 | 0.001 |
| 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 | 0.005 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".