Suchergebnisse

"A comprehensive introduction to combining Qualitative Comparative Analysis (QCA) and case studies using R software. With its practical focus, this book facilitates the efficient and independent learning of SMMR (set-theoretic multi-method research) for students, researchers, and practitioners in the social sciences"--

This book investigates the successes and failures in consolidating those democratic regimes that emerged in Europe and Latin America in the last quarter of the 20th century. The theoretical approach developed combines the most prominent political-institutional and socio-structural approaches to explaining the Consolidation of Democracy (CoD). Reinterpreting conventional claims, Schneider's comparative analyses of 32 countries indicates that the driving force behind CoD is the fit between the institutional type of democracy and the societal context in terms of power dispers.

The sole purpose of the enhanced standard analysis (ESA) is to prevent so-called untenable assumptions in Qualitative Comparative Analysis (QCA). One source of such assumptions can be statements of necessity. QCA realists, the majority of QCA researchers, have elaborated a set of criteria for meaningful claims of necessity: empirical consistency, empirical relevance, and conceptual meaningfulness. I show that once Thiem's (2017) data mining approach to detecting supersets is constrained by adhering to those standards, no CONSOL effect of Schneider and Wagemann's ESA exists. QCA idealists, challenging most of QCA realists' conventions, argue that separate searches for necessary conditions are futile because the most parsimonious solution formula reveals the minimally necessary disjunction of minimally sufficient conjunctions. Engaging with this perspective, I address several unresolved empirical and theoretical issues that seem to prevent the QCA idealist position from becoming mainstream.

Jack Paine (JP) and Alrik Thiem, Michael Baumgartner, and Damien Bol (TBB) provide diametrically opposed answers to the hotly debated question as to whether set-theory-based methods constitute a family of methods sui generis or whether not only set methods can be subsumed under the existing statistical framework, but also, if so, should be abandoned. I find TBB's argument convincing that due to their different mathematical foundations, these two families of methods cannot be directly translated, let alone unified into one. Notwithstanding this, it seems clear to me that work must continue on identifying conceptual similarities and differences, and to elaborate on each method's respective strengths and weaknesses. Because I mostly agree with TBB, I only briefly comment on some of their claims and then dedicate the rest of the text to JP.