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Record W4409037628 · doi:10.1057/s41599-025-04736-9

State and social power in post-communist countries: 1996–2022

2025· article· en· W4409037628 on OpenAlexaff
Monika Çule, Murray Fulton

Bibliographic record

VenueHumanities and Social Sciences Communications · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicPolitical Conflict and Governance
Canadian institutionsUniversity of SaskatchewanUniversity of Regina
Fundersnot available
KeywordsCommunismPower (physics)State (computer science)Political scienceEconomic systemEconomicsPoliticsPhysicsLawComputer science

Abstract

fetched live from OpenAlex

The purpose of this paper is to provide a procedure for examining the extent to which the changes observed among post-communist countries are consistent with a dynamic determined by the relative power of the state versus the relative power of society as captured in Acemoglu and Robinson’s “narrow corridor” framework. A direct test of Acemoglu and Robinson’s theory is not possible because the available data measures the quality of government and not the underlying state and society power. However, estimates of these latent variables can be obtained with factor analysis and the calculation of factor scores, which are then used in a cluster analysis to group countries according to their estimated state and society power. The results of the cluster analysis show three distinct groups of post-communist countries; these groups are argued to have the characteristics of the Despotic Leviathan, the Paper Leviathan and the Shackled Leviathan. While we find support for Acemoglu and Robinson’s prediction that the Despotic Leviathan acts as an attractor, the other predicted attractor – the Absent Leviathan – is not found in the data. Instead, countries with low state and society power appear to be trapped in the Paper Leviathan group, thus suggesting that it may also be an attractor. As predicted, membership in the Shackled Leviathan is stable only if state and society power are both large and relatively balanced. A closer analysis of three countries – Russia (Despotic Leviathan), Albania (Paper Leviathan), and Hungary (unable to secure a place in the “narrow corridor”) – provides additional evidence that largely supports the use of factor and cluster analysis to categorize countries.

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 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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.869
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0070.007
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.074
GPT teacher head0.361
Teacher spread0.287 · 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; both teacher heads agree on what is shown here.

Study designTheoretical or conceptual
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
Published2025
Admission routes1
Has abstractyes

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