Bibliographic record
Abstract
Do Eastern European courts effectively constrain politicians and uphold the rule of law? Criminal prosecution of grand (high-level) corruption can further the central principle of equal responsibility under the law by demonstrating that even powerful political actors have to submit to the laws of the land. This article introduces the Eastern European Corruption Prosecution Database, which contains entries for all cabinet ministers (927 in total) who served in a government that held office in one of seven post-Communist Eastern European countries since the late 1990s. The systematic data collection reveals that Bulgaria, Romania and Macedonia consistently indict more ministers than Croatia, the Czech Republic, and Poland; Slovakia has barely indicted anyone. We aim to start a research agenda by formulating hypotheses about which countries will see more corruption prosecutions and which ministers’ characteristics would make them more likely to face the court. We use the database to begin testing these hypotheses and find some evidence for several associations. We find no strong evidence that EU conditionality or membership raises the profile of the grand corruption issue or leads to more indictments. Party politics seems to affect the frequency of corruption indictments more than the structure and behavior of legal institutions. Indictment rates are lower when a former Communist party controls the government and individual ministers from junior coalition partners are more vulnerable to indictment than other ministers. The existence of a specialized anti-corruption prosecution or a more independent judiciary do not seem to lead to the indictment of more ministers on corruption charges. Finally, we discuss avenues of future research that our database opens, both for the analysis of country-level and individual-level variation.
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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 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".