Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 462

The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.

Rebuilding Leviathan: Party Competition and State Exploitation in Post-Communist Democracies

Grzymala-Busse, Anna·2007·Cambridge University Press eBooks

Abstract

Why do some governing parties limit their opportunistic behaviour and constrain the extraction of private gains from the state? This analysis of post-communist state reconstruction provides surprising answers to this fundamental question of party politics. Across the post-communist democracies, governing parties have opportunistically reconstructed the state - simultaneously exploiting it by extracting state resources and building new institutions that further such extraction. They enfeebled or delayed formal state institutions of monitoring and oversight, established new discretionary structures of state administration, and extracted enormous informal profits from the privatization of the communist economy. By examining how post-communist political parties rebuilt the state in Bulgaria, the Czech Republic, Estonia, Hungary, Latvia, Lithuania, Poland, Slovakia, and Slovenia, Grzymala-Busse explains how even opportunistic political parties will limit their corrupt behaviour and abuse of state resources when faced with strong political competition.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1017/cbo9780511618819

Cites

3 of 3 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 3 references

Cited by

See all 462

Metadata

Authors
Grzymala-Busse, A.
Venue
Cambridge University Press eBooks
Published
2007-04-09
OpenAlex
W4302575906
Cited by
462
References
3
FWCI
19.35
Type
book
Language
en
Open access
closed

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Rebuilding Leviathan: Party Competition and State Exploitation in Post-Communist Democracies. https://app.cochat.ai/papers/10.1017/cbo9780511618819
The paper
Grzymala-Busse, A. (2007). Rebuilding Leviathan: Party Competition and State Exploitation in Post-Communist Democracies. Cambridge University Press eBooks. https://doi.org/10.1017/cbo9780511618819

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.