Confronting the Past: Corruption in Post-Communist Hungary and Romania
Bibliographic record
Abstract
Why are some states more corrupt than others? More specifically, why is post-communist Romania significantly more corrupt than post-communist Hungary even though both transitioned to democracy from USSR satellite states in 1989 and both went on to enter the European Union? This paper argues that though the implementation of communism in political institutions at the time of transition cannot serve as an explanatory factor, Romania’s patrimonial pre-communist history developed a foundation of corruption and the lack of turnover in political leadership during the transition from communism to democracy played a critical role in continuing this corrupt pre-communist foundation. Conversely, Hungary featured a theme of political turnover throughout its pre-communist past, communist past and also in its leadership into democracy, which allowed it to avoid a cultural foundation of corruption. Moreover, international institutions such as the European Union had the opportunity to promote an anti-corruption platform in Romania, yet the EU had is own problematic institutions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".