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The DOI matches its Crossref record; 36 of the 36 references it cites were found in a registry or an index.

Liberalizing Electoral Outcomes in Competitive Authoritarian Regimes

Open access
Howard, Marc Morjé, Roessler, Philip G.·2006·American Journal of Political Science

Abstract

In the wake of the third wave of democratization, competitive authoritarianism has emerged as a prominent regime type. These regimes feature regular, competitive elections between a government and an opposition, but the incumbent leader or party typically resorts to coercion, intimidation, and fraud to attempt to ensure electoral victory. Despite the incumbent's reliance on unfair practices to stay in power, such elections occasionally result in what we call a “liberalizing electoral outcome” (LEO), which often leads to a new government that is considerably less authoritarian than its predecessor. Using a “nested” research design that employs both cross‐national statistical analysis and a case study of Kenya, we seek to explain how and why LEOs occur. Our findings highlight in particular the importance of the choices made by opposition elites to form a strategic coalition for the purpose of mounting a credible challenge to the ruling party or candidate in national elections.

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Crossref · 10.1111/j.1540-5907.2006.00189.x

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Metadata

Authors
Howard, M. M., & Roessler, P. G.
Venue
American Journal of Political Science
Publisher
Wiley
Published
2006-03-29
Volume
50
Issue
2
Pages
365-381
ISSN
  • 0092-5853 (ISSN-L)
  • 1540-5907
OpenAlex
W2162818481
Cited by
732
References
36
FWCI
42.65
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: Liberalizing Electoral Outcomes in Competitive Authoritarian Regimes. https://app.cochat.ai/papers/10.1111/j.1540-5907.2006.00189.x
The paper
Howard, M. M., & Roessler, P. G. (2006). Liberalizing Electoral Outcomes in Competitive Authoritarian Regimes. American Journal of Political Science. https://doi.org/10.1111/j.1540-5907.2006.00189.x

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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.