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Making Embedded Knowledge Transparent: How the V-Dem Dataset Opens New Vistas in Civil Society Research

Making Embedded Knowledge Transparent: How the V-Dem Dataset Opens New Vistas in Civil Society Research

by Michael Bernhard, University of Florida, Dong-Joon Jung, Seoul National University, South Korea, Eitan Tzelgov, University of East Anglia, Michael Coppedge, University of Notre Dame, and Staffan I. Lindberg, University of Gothenburg

We show how the V-Dem data opens new possibilities for studying civil society in comparative politics. We explain how V-Dem was able to extract embedded expert knowledge to create a novel set of civil society indicators for 173 countries from 1900 to the present. This data overcomes shortcomings in the basis on which inference has been made about civil society in the past by avoiding problems of sample bias that make generalization difficult or tentative. We begin with a discussion of the reemergence of civil society as a central concept in comparative politics. We then turn to the shortcomings of the existing data and discusses how the V-Dem data can overcome them. We introduce the new data, highlighting two new indices—the core civil society index (CCSI) and the civil society participation index (CSPI)—and explain how the individual indicators and the indices were created. We then demonstrate how the CCSI uses embedded expert knowledge to capture the development of civil society on the national level in Venezuela, Ghana, and Russia. We close by using the new indices to examine the dispute over whether post-communist civil society is “weak.” Time-series cross-sectional analysis using 2,999 country-year observations between 1989 and 2012 fails to find that post-communist civil society is substantially different from other regions, but that there are major differences between the post-Soviet subsample and other post-communist countries both in relation to other regions and each other.

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Perspectives on Politics / Volume 15, Issue 2June 2017, pp. 342-360