Publication Type
Journal Article
Version
publishedVersion
Publication Date
12-2012
Abstract
The Comparative Manifesto Project (CMP) provides the only time series of estimated party policy positions in political science and has been extensively used in a wide variety of applications. Recent work (e.g., Benoit, Laver, and Mikhaylov 2009; Klingemann et al. 2006) focuses on nonsystematic sources of error in these estimates that arise from the text generation process. Our concern here, by contrast, is with error that arises during the text coding process since nearly all manifestos are coded only once by a single coder. First, we discuss reliability and misclassification in the context of hand-coded content analysis methods. Second, we report results of a coding experiment that used trained human coders to code sample manifestos provided by the CMP, allowing us to estimate the reliability of both coders and coding categories. Third, we compare our test codings to the published CMP "gold standard" codings of the test documents to assess accuracy and produce empirical estimates of a misclassification matrix for each coding category. Finally, we demonstrate the effect of coding misclassification on the CMP's most widely used index, its left-right scale. Our findings indicate that misclassification is a serious and systemic problem with the current CMP data set and coding process, suggesting the CMP scheme should be significantly simplified to address reliability issues.
Keywords
Policy positions, nominal scales, agreement, words, texts
Discipline
Models and Methods | Political Science
Research Areas
Political Science
Publication
Political Analysis
Volume
20
Issue
1
First Page
78
Last Page
91
ISSN
1047-1987
Identifier
10.1093/pan/mpr047
Publisher
Political Methodology Section
Citation
MIKHAYLOV, Slava, LAVER, Michael, & BENOIT, Kenneth.(2012). Coder reliability and misclassification in the human coding of party manifestos. Political Analysis, 20(1), 78-91.
Available at: https://ink.library.smu.edu.sg/soss_research/3983
Copyright Owner and License
Authors CC-BY
Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 License.
Additional URL
https://doi.org/10.1093/pan/mpr047