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Record W2624421610 · doi:10.1016/j.euras.2017.05.001

Sand or grease? Corruption-institutional trust nexus in post-Soviet countries

2017· article· en· W2624421610 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Eurasian Studies · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicCorruption and Economic Development
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsNexus (standard)Language changePoliticsInstrumental variableEconomicsChinaCivil servantEndogeneityOrdinary least squaresGovernment (linguistics)Political scienceLaw

Abstract

fetched live from OpenAlex

This paper empirically tests several hypotheses about the nexus of corruption-institutional trust in Post-Soviet transitional countries of the former Soviet Union and Mongolia. We use two different indices of institutional trust to check the robustness of our analysis and estimate OLS and instrumental variable models with and without interaction terms. All things considered, our findings reject “greases the wheels” and “trust begets an honest political system” hypotheses. Instead, our findings support the “sand the wheels” hypothesis. Furthermore, a multiplicative interaction model suggests that the negative marginal effects of experienced corruption are higher in the environments where satisfaction with services is low. In addition, we found that increases in corruption erode trust at all levels of the societal institutions including political parties, government and financial institutions, international investors, non-profit organizations, and trade unions. This finding is important since it highlights the negative consequences of corruption on the development of broader level economic institutions and on civil society.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.231
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.097
GPT teacher head0.397
Teacher spread0.300 · 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