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Record W2380745781

Confronting the Past: Corruption in Post-Communist Hungary and Romania

2016· article· en· W2380745781 on OpenAlexvenueno aff
Michellie Hess

Bibliographic record

VenueSound Ideas (University of Puget Sound) · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicCorruption and Economic Development
Canadian institutionsnot available
Fundersnot available
KeywordsCommunismDemocracyPoliticsPolitical scienceLanguage changePolitical economyEuropean unionCommunist stateDevelopment economicsLawSociologyEconomicsEconomic policy
DOInot available

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.024
Threshold uncertainty score0.048

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.004
Scholarly communication0.0030.001
Open science0.0000.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.018
GPT teacher head0.232
Teacher spread0.215 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2016
Admission routes1
Has abstractyes

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