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A framework for the systematic study of election quality

Elklit, Jørgen, Reynolds, Andrew·2005·Democratization

Abstract

This article offers the beginnings of a methodology for assessing the quality of a national election, its freeness, fairness and administrative efficacy. The historical lack of a comprehensive framework of analysis has compelled election observers to make pronouncements on the basis of incomplete evidence, usually gathered on the day of the vote and count. It has allowed international observation missions to ‘call’ the results of elections on the basis of political expediency rather than the facts of the case. The intent in this article is not to offer a foolproof method for categorizing election quality but rather to lay out a framework which we believe is more comprehensive and meaningful than anything that has come before. To illustrate its workings the article scores six multi-party elections: two in established democracies – Australia and Denmark 2001– and four in fledgling democracies – South Africa 1994 and 2004, East Timor 2001 and Zimbabwe 2002. The framework outlined here will make it possible to identify patterns of success and failure in the fairness of elections. It should enable all kinds of observers from academics and election administrators to election observers to spotlight the weak areas of election administration, where a government might then choose to focus its efforts to improve the quality of subsequent elections.

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Metadata

Authors
Elklit, J., & Reynolds, A.
Venue
Democratization
Published
2005-04
Volume
12
Issue
2
Pages
147-162
ISSN
  • 1351-0347 (ISSN-L)
  • 1743-890X
OpenAlex
W2078403854
Cited by
167
References
0
FWCI
21.77
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: A framework for the systematic study of election quality. https://app.cochat.ai/papers/10.1080/13510340500069204
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Elklit, J., & Reynolds, A. (2005). A framework for the systematic study of election quality. Democratization. https://doi.org/10.1080/13510340500069204

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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.