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Governments routinely justify why the regime over which they preside is entitled to rule. These claims to legitimacy are both an expression of and shape of how a rule is being exercised. In this paper, we introduce new expert-coded measures of regime legitimation strategies (RLS) for 183 countries in the world from 1900 to 2019. Country experts rated the extent to which governments justify their rule based on performance, the person of the leader, rational-legal procedures, and ideology. They were also asked to qualify the ideology of the regime. The main purposes of this paper are to present the conceptual basis for the measure, describe the data, and provide convergent, content, and construct validity tests for new measures. Our measure of regime legitimation performs well in all these three validation tests, most notably, the construct validity exercise which explores commonly held beliefs about leadership under populist rule.
The consistent association between therapeutic alliance and outcome underlines the importance of identifying factors which predict the development of a positive alliance. However, only few studies have examined the association between pretreatment characteristics and alliance formation in patients with schizophrenia.
The study examined whether symptoms and insight would predict the therapeutic alliance in psychotherapy of schizophrenia. Further, the associations and differences between patient and therapist alliance ratings were studied.
Eighty patients with schizophrenia spectrum disorders received manual-based psychotherapy. Assessment of symptoms and insight was conducted at baseline, and questionnaire-based alliance ratings were obtained three weeks into treatment. Patient and therapist alliance ratings were examined separately.
Patient and therapist alliance ratings were not significantly correlated (r = 0.17). Patient ratings of the alliance were significantly higher than the ratings of their therapists (d = 0.73). More insight in psychosis significantly predicted higher patient ratings of the alliance. Less positive and negative symptoms were significant predictors of higher therapist alliance ratings.
The findings indicate that symptoms and insight have an influence on the therapeutic alliance in the treatment of schizophrenia spectrum disorders. Patients' and therapists' perceptions of the alliance do not seem to demonstrate much convergence.
Scholars and policy makers need systematic assessments of the validity of the measures produced by V-Dem. In Chapter 6, we present our approach to comparative data validation – the set of steps we take to evaluate the precision, accuracy, and reliability of our measures, both in isolation and compared to extant measures of the same concepts. Our approach assesses the degree to which measures align with shared concepts (content validation), shared rules of translation (data generation assessment), and shared realities (convergent validation). Within convergent validity, we execute two convergent validity tests. First, we examine convergent validity as it is typically conceived – examining convergence between V-Dem measures and extant measures. Second, we evaluate the level of convergence across coders, considering the individual coder and country traits that predict coder convergence. Throughout the chapter, we focus on three indices included in the V-Dem data set: polyarchy, corruption, and core civil society. These three concepts collectively provide a “hard test” for the validity of our data, representing a range of existing measurement approaches, challenges, and solutions.
This chapter sets forth the conceptual scheme for the V–Dem project. We begin by discussing the concept of democracy. Next, we lay out seven principles by which this key concept may be understood – electoral, liberal, majoritarian, consensual, participatory, deliberative, and egalitarian. Each defines a “variety“ of democracy, and together they offer a fairly comprehensive accounting of the concept as used in the world today. Next, we show how this seven-part framework fits into our overall thinking about democracy, including multiple levels of disaggregation – to components, subcomponents, and indicators. The final section of the chapter discusses several important caveats and clarifications pertaining to this ambitious taxonomic exercise.
This chapter recounts how a project of this scale came together and why it has succeeded. Five main factors were responsible for V–Dem’s success: timing, inclusion, deliberation, administrative centralization, and fund–raising. First, planning for V-Dem began at a time when both social scientists and practitioners were realizing that they needed better democracy measures. This made it possible to recruit collaborators and find funding. Second, the leaders of the project were always eager to expand the team to acquire whatever expertise they lacked and share credit with everyone who contributed. Third, the project leaders practiced an intensely deliberative decision–making style to ensure that all points of view were consulted and only decisions that won wide acceptance were adopted. Fourth, centralizing the execution of the agreed–upon tasks helped tremendously by streamlining processes and promoting standardization, documentation, professionalization, and coordination of a large number of intricate steps. Finally, successful fund–raising from a mix of both research foundations and bilateral and multilateral organizations has been critical.
In this chapter we focus on the measurement of five key principles of democracy – electoral, liberal, participatory, deliberative, and egalitarian. For each principle, we discuss (1) the theoretical rationale for the selected indicators, (2) whether these indicators are correlated strongly enough to warrant being collapsed into an index, and (3) the justification of aggregation rules for moving from indicators to components and from components to higher–level indices. In each section we also (4) highlight the top– and bottom–five countries on each principle of democracy in early (1812 or 1912) and late (2012) years of our sample period, as well as the aggregate trend over the whole time period 1789–2017 (where applicable). Finally, we (5) look at how the different principles are intercorrelated in order to assess the trade–offs involved between the conceptual parsimony achieved by aggregating to a few general concepts and the retention of useful variation permitted by aggregating less.
Four characteristics of V-Dem data present distinct opportunities and challenges for explanatory analysis: (1) the large number of democracy indicators (i.e., variables), (2) the measurement of concepts by multiple coders filtered through the V-Dem measurement model, (3) the large number of years in the data set, and 4) the ex ante potential for dependence across countries (generically referred to as spatial dependence). This chapter discusses 3 challenges and 10 opportunities that are implied by these characteristics. At the end of this chapter, we also discuss three assumptions that are implicit in most analyses of observational indicators of macro-features at the national level, which aim to draw conclusions about causal relationships.