Introduction: absorbing the four methodological disruptions in democratization research?

This article introduces the special issue on methodological trends in democratization research by taking stock of the overall development of methods practices and situating the findings of the individual article contributions within the broader developments. As has the broader discipline, democratization research has experienced four methodological "disruptions" over the past 60 years: the behavioural revolution of statistical methodology; the introduction of formal theory; the sophistication of qualitative, set-theoretic and multi-method research; and the increasing use of experimental methods. Surveying the methods practices in the past quarter century, we find that quantitative and multi-method research have been growth areas in recent years, but that the bulk of research is still done in comparative or single case studies. Formal theory as well as set-theoretic methods have gained a foothold in the field, but it is still a small one. In sum, democratization research is, methodologically speaking, still rather traditional. Moreover, the individual contributions to this special issue show that much of the empirical literature underutilizes the best available advice about how to develop and test theory, including standards on causal inference, case-selection, and generalization. We conclude with a plea for more transparency, humility, and collaboration within and across methodological traditions

V-Dem Comparisons and Contrasts with Other Measurement Projects

For policymakers, activists, academics, and citizens around the world the conceptualization and measurement of democracy matters. The needs of democracy promoters and social scientists are convergent. We all need better ways to measure democracy. In the first section of this document we critically review the field of democracy indices. It is important to emphasize that problems identified with extant indices are not easily solved, and some of the issues we raise vis-à-vis other projects might also be raised in the context of the V-Dem project. Measuring an abstract and contested concept such as democracy is hard and some problems of conceptualization and measurement may never be solved definitively. In the second section we discuss in general terms how the Varieties of Democracy (V-Dem) project differs from extant indices and how the novel approach taken by V-Dem might assist the work of activists, professionals, and scholars.This research project was supported by Riksbankens Jubileumsfond, Grant M13-0559:1, PI: Staffan I. Lindberg, V-Dem Institute, University of Gothenburg, Sweden; by Knut and Alice Wallenberg Foundation to Wallenberg Academy Fellow Staffan I. Lindberg, Grant 2013.0166, V-Dem Institute, University of Gothenburg, Sweden; as well as by internal grants from the Vice-Chancellor’s office, the Dean of the College of Social Sciences, and the Department of Political Science at University of Gothenburg. We performed simulations and other computational tasks using resources provided by the Notre Dame Center for Research Computing (CRC) through the High Performance Computing section and the Swedish National Infrastructure for Computing (SNIC) at the National Supercomputer Centre in Sweden, SNIC 2016/1-382 and 2017/1-68. We specifically acknowledge the assistance of In-Saeng Suh at CRC and Johan Raber at SNIC in facilitating our use of their respective systems

Conceptual and Measurement Issues in Assessing Democratic Backsliding

During the past decade, analyses drawing on several democracy measures have shown a global trend of democratic retrenchment. While these democracy measures use radically different methodologies, most partially or fully rely on subjective judgments to produce estimates of the level of democracy within states. Such projects continuously grapple with balancing conceptual coverage with the potential for bias (Munck and Verkuilen 2002; Przeworski et al. 2000). Little and Meng (L&M) (2023) reintroduce this debate, arguing that “objective” measures of democracy show little evidence of recent global democratic backsliding.1 By extension, they posit that time-varying expert bias drives the appearance of democratic retrenchment in measures that incorporate expert judgments. In this article, we engage with (1) broader debates on democracy measurement and democratic backsliding, and (2) L&M’s specific data and conclusions

Making embedded knowledge transparent: How the V-Dem dataset opens new vistas in civil society research

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

Concepts and Measurement in Multimethod Research

This article argues that concept misformation and conceptual stretching undermine efforts to combine qualitative and quantitative methods in multimethod research (MMR). Two related problems result from the mismatch of qualitatively and quantitatively construed concepts. Mechanism muddling occurs when differences in the connotation of qualitatively and quantitatively construed concepts embed different causal properties into conceptual definitions. Conceptual slippage occurs when qualitatively and quantitatively construed concepts use incompatible nominal, ordinal, or radial scales. Instead of gaining leverage from the synthesis of large- and small-N analysis, these problems can push MMR in two diametrically opposed directions, emphasizing one methodological facet at the cost of the other.Yeshttps://us.sagepub.com/en-us/nam/manuscript-submission-guideline