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Record W381582087 · doi:10.1017/cbo9780511781353

Competitive Authoritarianism: Hybrid Regimes after the Cold War

2001· book· en· W381582087 on OpenAlexaff
Steven Levitsky, Lucan A. Way

Bibliographic record

Venuenot available
Typebook
Languageen
FieldSocial Sciences
TopicPolitical Conflict and Governance
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsAuthoritarianismTechnocracyDemocratizationPolitical economyOpposition (politics)Political scienceLatin AmericansInstitutionalisationPower sharingPower (physics)Economic systemDevelopment economicsDemocracyPoliticsEconomicsLaw

Abstract

fetched live from OpenAlex

Based on a detailed study of 35 cases in Africa, Asia, Latin America, and post-communist Eurasia, this book explores the fate of competitive authoritarian regimes between 1990 and 2008. It finds that where social, economic, and technocratic ties to the West were extensive, as in Eastern Europe and the Americas, the external cost of abuse led incumbents to cede power rather than crack down, which led to democratization. Where ties to the West were limited, external democratizing pressure was weaker and countries rarely democratized. In these cases, regime outcomes hinged on the character of state and ruling party organizations. Where incumbents possessed developed and cohesive coercive party structures, they could thwart opposition challenges, and competitive authoritarian regimes survived; where incumbents lacked such organizational tools, regimes were unstable but rarely democratized.

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)0.003
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.055

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0080.015
Scholarly communication0.0070.004
Open science0.0010.005
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0020.000

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 head0.017
GPT teacher head0.273
Teacher spread0.256 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations2,190
Published2001
Admission routes1
Has abstractyes

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