Harmonization of Cross-National Survey Projects on Political Behavior: Developing the Analytic Framework of Survey Data Recycling

This article describes challenges and solutions to ex post harmonization of survey data in the social sciences based on the big data project "Democratic Values and Protest Behavior: Data Harmonization, Measurement Comparability, and Multi-Level Modeling." This project engages with the rela...

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Bibliographic Details
Published in:International journal of sociology 2016-01, Vol.46 (1), p.58-72
Main Authors: Tomescu-Dubrow, Irina, Slomczynski, Kazimierz M.
Format: Article
Language:English
Subjects:
Big Data
cross-national
data harmonization
Democracy
Political attitudes
Political behavior
Polls & surveys
Protest movements
Social attitudes
survey data recycling
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Summary:This article describes challenges and solutions to ex post harmonization of survey data in the social sciences based on the big data project "Democratic Values and Protest Behavior: Data Harmonization, Measurement Comparability, and Multi-Level Modeling." This project engages with the relationship between democracy and protest behavior in comparative perspective by proposing a theoretical model that explains variation in political protest through individual-level characteristics, country-level determinants, and interactions between the two. Testing it requires data with information at both the individual and country levels that vary across space and over time. The project's team pooled information from 22 well-known international survey projects into a data set of 2.3 million respondents, covering a total of 142 countries and territories, and spanning almost 50 years, to construct common measures of political behavior, social attitudes, and demographics. The integrated data set is appended with country variables from nonsurvey sources. Mapping the methodological complexities this work raised and their solutions became the springboard for the analytic framework of Survey Data Recycling (SDR). SDR facilitates reprocessing information from extant cross-national projects in ways that minimize the "messiness" of data built into original surveys, expand the range of possible comparisons over time and across countries, and improve confidence in substantive results.
ISSN:0020-7659
1557-9336
DOI:10.1080/00207659.2016.1130424