During the last two decades, there have been various attempts at measuring and assessing the health of civil society. Some have focused almost exclusively on ‘counting’ the nonprofit, while others have assessed the strength of nongovernmental organizations. Yet, these sectors are just a small part of a much larger environment. Moreover, they are the result of Western conceptualizations of civil society, thus not very helpful for one to understand civic participation in non-Western settings. Taking stock of these fundamental issues, this article presents the conceptual framework and methodology of a new global index to measure the ‘enabling environment’ of civil society, rather than its forms and institutional contours. Given the inherent diversity of civil societies worldwide, which defies any attempt at developing predetermined definitions, understanding the conditions that support civic participation becomes the most important objective for those interested in promoting a strong civil society arena. The index was launched by CIVICUS in late 2013 with the name of enabling environment index and covers over 200 countries and territories, making it the most ambitious attempt ever made at measuring civil society worldwide.

Interest group research has focused extensively on political access. While access does not guarantee influence, it is customarily seen as a crucial step towards gaining political influence. It is argued that groups with access are, all else equal, more likely to be influential than groups without access. Biased access may thus result in biased influence. On the basis of a review of this literature, the article shows how the concept of access rests on an intuitive understanding rather than an explicit definition. This hampers methodological discussions of measurement. We propose to define access as instances where a group has entered a political arena (parliament, administration, or media) passing a threshold controlled by relevant gatekeepers (politicians, civil servants, or journalists). On the basis of this discussion, we compare operationalisations based on our proposed definition with some of the major alternatives found in the literature.

Expert surveys have been used to measure a wide variety of phenomena in political science, ranging from party positions, to corruption, to the quality of democracy and elections. However, expert judgments raise important validity concerns, both about the object being measured as well as the experts. It is argued in this article that the context of evaluation is also important to consider when assessing the validity of expert surveys. This is even more important for expert surveys with a comprehensive, worldwide scope, such as democracy or corruption indices. This article tests the validity of expert judgments about election integrity – a topic of increasing concern to both the international community and academics. Evaluating expert judgments of election integrity provides an important contribution to the literature evaluating the validity of expert surveys as instruments of measurement as: (1) the object under study is particularly complex to define and multifaceted; and (2) election integrity is measured in widely varying institutional contexts, ranging from electoral autocracies to liberal democracies. Three potential sources of bias are analysed (the object, the experts and the context), using a unique new dataset on election integrity entitled the ‘Perceptions of Electoral Integrity’ dataset. The data include over 800 experts in 66 parliamentary and presidential elections worldwide. It is found that validity of expert judgments about election integrity is increased if experts are asked to provide factual information (rather than evaluative judgments), and if they are asked to evaluate election day (rather than pre‐election) integrity. It is also found that ideologically polarised elections and elections of lower integrity increase expert disagreement about election integrity. The article concludes with suggestions for researchers using the expert survey data on election integrity on how to check the validity of their data and adjust their analyses accordingly, and outlines some remaining challenges for future data collection using expert surveys.

Despite a growing interest in migration questions, it is still not possible to systematically analyse immigration policies across time and a large number of countries. Most studies in this field have heretofore focussed on individual cases. Recently, there have been a series of studies that have proposed policy indices that allow for large-N analyses. It appears, however, that these studies have not always adequately addressed the main challenges of index building, that is, conceptualisation, measurement and aggregation. Moreover, they are for the most part limited to individual policy fields or there is a trade-off between the number of countries and years that are covered. The aim of this article is to present the Immigration Policies in Comparison (IMPIC) project, which proposes a new and comprehensive way to measure immigration regulations. The data set covers all major fields and dimensions of immigration policies for thirty-three OECD countries between 1980 and 2010. This article discusses the way immigration policies have been conceptualised, how policies have been measured and aggregated and demonstrates the potential of such a new data set.

International comparative research on civil society has subordinated Africa’s diversity and specificities to other geographies and histories. Results are prejudiced global conceptualisations, questionable enumeration, problematic theory formulation and ill-conceived approaches to development initiatives intended to make African civil society ‘stronger’ and states more democratic. This article sets out a case for an endogenous approach to civil society enquiry as a political category sensitive to the continent’s particularisms. In order to locate discussion about meanings, measures and measuring, a conceptual framework for research is described which avoids conflation with other epistemologies. Such a contribution will assist in sharpening thinking and discussion about the boundary characteristics of what is to be investigated.

Although survey research is one of the most frequently used methods for studying charitable giving, the quality of the data is seldom stated or known. In particular, social desirability bias (SDB) has been found to distort data validity where respondents tend to over-report what is socially desirable and vice versa. We argue that this phenomenon has not been fully understood in the nonprofit context as existing social desirability scales are not appropriate to be used in giving surveys. Thus, this paper is the first to extend understanding of SDB to the nonprofit context and to explore its motivating factors. Based on a multidisciplinary literature review and qualitative interviews with various senior practitioners from the fundraising and marketing research sectors, it is suggested that SDB is a multidimensional construct yielding five dimensions, namely, impression management, self-deception, level of involvement, perceived benefits and social norms. The paper then discusses the implications for nonprofit researchers and concludes with directions for future research.

This article reports on the results of a broad crosslinguistic study on the semantics of quantity words such as many in the superlative (e.g. most). While some languages use such a form to express both a relative reading (as in Gloria has visited the most continents) and a proportional reading (as in Gloria has visited most continents), the vast majority do not allow the latter, though all allow the former. It is argued that a degree-quantifier analysis of quantity words is best suited to explain why proportional readings typically do not arise for quantity superlatives. Based on morphosyntactic evidence, two alternative diachronic pathways through which proportional quantifiers may develop from quantity superlatives are identified.

Over the last two decades, nonprofit organizations in the United Kingdom (UK) have faced increased pressure to measure their activities in order to demonstrate their competency, to achieve legitimacy, and to obtain funding. This paper draws from recent literature in the sociology of science to examine quantification in the British voluntary sector as a historically situated and socially constructed process. Using archival and secondary documents, I find that quantification is not a new practice for charities in the UK; moreover, while they have employed metrication in the past, what activities nonprofits have measured, and the importance of measurement for their organizational success, has altered over the course of the century.

How should small-n researchers aggregate the information collected during their research in an effort to measure the relevant theoretical concepts with high levels of validity and reliability? This article specifically focuses on the method of triangulation, which is frequently used in process-tracing approaches. We introduce and theorise different aggregation strategies commonly used in triangulation, such as weighted and simple averages or ‘the winner takes it all’ strategy. We then evaluate their performance with regard to their proneness to measurement error using computer simulations. Our simulation results show that averaging different information sources, in general, outperforms other aggregation strategies. However, this is not the case if poorly informed sources are biased in a similar direction; in these situations the ‘winner takes it all’ strategy shows a superior performance.

Different publics have been asked for their opinion about corruption through a variety of survey questions over the past five decades. Notwithstanding their relevance, these items have been developed with different (research) objectives in mind. This article introduces and discusses a new database on corruption surveys. The DATACORR database consists of national and cross-national survey items on perceptions, attitudes, and experiences of corruption and covers 3,050 items from 321 survey rounds, developed by 110 research projects of 83 different institutions around the world, from 1976 to 2019. Two public opinion-centred corruption research approaches have been identified: (a) one addressing conceptualisations of corruption and (b) another focusing on the evaluations individuals make of the impacts of corruption. Our study reveals that survey questions on corruption tend to be more generic and sociotropic. Although there have been attempts to move towards survey items capturing egotropic and specific aspects of corruption until the 2000s, this tendency has reversed more recently, making room for debate on how to advance knowledge in the field.

Using Suchman’s taxonomy, the generation of legitimacy in relation to both external parties/stakeholders and employees by four Swedish work integration social enterprises (WISEs) was investigated. Data were collected through focus group and individual interviews. When operating in fiercely competitive markets, a pragmatic exchange legitimacy was mainly used. When selling complex products, such as investigations of work capacity, normative, and cognitive forms of legitimacy were common. As regards internal relations, normative legitimacy established though robust internal procedures was of importance. In addition, relational legitimacy when dealing with clients, funders, and employees emerged as important. The study indicates that WISEs tend to imitate profit-generating organizations in generating legitimacy. Although short-term resource-generation can be facilitated, the replication of for-profit practices can create a tension with the concurrent aim of being an innovative and empowering enterprise for people who otherwise would be excluded from the labor market.

The extensive scholarship devoted to the congruence of mass-elite policy preferences lacks consensus about the meaning, comparison, and measurement across political settings. This makes comparisons difficult and raises obstacles to advancing the debates. This symposium aims to identify the diversity of methodological choices and to reflect systematically on several key choices of particular importance in understanding the congruence. The contributions to the symposium compare and contrast how several types of measurement fare in diverse political contexts in Eastern Europe, Latin America, North Africa, and East Asia, and what we can learn from those methodological choices.

By comparing and analysing four cross-national measures of democracy, this article provides novel information regarding the statistical properties, convergence, and interchangeability of some of the most frequently used measures of democracy. The author points out limitations related to the statistical properties of these measures and finds that even if measures of democracy are highly convergent, their interchangeability is weak. This means that the choice of the measure of democracy has considerable consequences for the conclusions of a given study. Especially so in studies covering the last few decades, because the author finds that in general the interchangeability of democracy measures has decreased since the 1980s. In choosing one measure over another, scholars should be aware of the limitations identified in this article. To overcome problems related to weak interchangeability, if a single measure cannot be credibly chosen on theoretical grounds, the author recommends users of the measures to validate their findings with multiple measures of democracy.

To complement contemporary nonprofit literature, which mainly offers theory-driven recommendations for measuring nonprofit effectiveness, performance, or related concepts; this article presents seven trade-offs for researchers and practitioners to consider before engaging in a nonprofit effectiveness measurement project. For each trade-off, we offer examples and suggestions to clarify the advantages and disadvantages of methodological choices that take various contextual elements into account. In particular, we address the differences between formative and reflective approaches, as well as the differences between unit of interest, unit of data collection, and unit of analysis. These topics require more in-depth attention in the nonprofit effectiveness literature to avoid misinterpretations and measurement biases. Finally, this article concludes with five avenues for further research to help address key challenges that remain in this research area.

One of the most innovative measures of the political financing regulatory reforms of the past 2 decades was the creation or designation of new political financing supervisory bodies, entrusted to monitor and enforce political financing regulations. These bodies have been growing in numbers in the last 2 decades, partly in response to public opinion pressure and partly to international commitments. Drawing on regulatory and organisational capacity theories, this article seeks to develop a new index to measure the enforcement capacity of these bodies.

Since its introduction by Tuckman and Chang (Nonprofit Volunt Sector Q 20(4):445–460, 1991), the Hirschman–Herfindahl Index (HHI) has been widely adopted into the nonprofit literature as a precise measure of revenue concentration. This widespread adoption has been characterized by diverse composition, with the HHI’s calculation being largely determined by the nature of the available data and the degree to which it contained disaggregated measures of revenue. Using the NCCS 990 Digitized Data, we perform an acid test on whether different HHI measures yield significantly different results. Four measures of revenue concentration—an aggregated measure based on three revenue streams, an aggregated measure separating government grants from other contributions, a more nuanced measure based on seven revenue streams, and a fully disaggregated measure based on thirteen revenue streams—are used to predict two dominant nonprofit financial health dimensions: financial volatility and financial capacity. Overall, our results show that aggregation in HHI measurement matters; aggregation often downplays relationships by influencing the significance levels and magnitudes of estimates in a non-trivial way.

Social enterprise has become a key phenomenon in providing public services in many developed countries. The debate on the evaluation of the socio-economic impact generated by this kind of organization has gone hand in hand with the growth of social entrepreneurship. This study provides an exploratory analysis of the emerging practice of measuring the socio-economic impact of social enterprises using the theoretic construct called “Blended Value Accounting” (BVA). Among the models and tools proposed by BVA, we examine in particular the Social Return on Investment (SROI)—an instrument of causal contribution analysis—conducting a literature review on its application to the evaluation of socio-economic impact of social enterprises and on its implications for BVA. Finally, we reach a conclusion as to the role that these tools of mixed accounting and assessment might play—particularly the one examined—with respect to the positivist, critical, and interpretative theories of accounting, thus identifying the areas for further research.

While there is an abundant use of macro data in the social sciences, little attention is given to the sources or the construction of these data. Owing to the restricted amount of indices or items, researchers most often apply the ‘available data at hand’. Since the opportunities to analyse data are constantly increasing and the availability of macro indicators is improving as well, one may be enticed to incorporate even qualitatively inferior indicators for the sake of statistically significant results. The pitfalls of applying biased indicators or using instruments with unknown methodological characteristics are biased estimates, false statistical inferences and, as one potential consequence, the derivation of misleading policy recommendations. This Special Issue assembles contributions that attempt to stimulate the missing debate about the criteria of assessing aggregate data and their measurement properties for comparative analyses.

Contemporary political scientists have observed a democratic paradox that has crystallized around the disconnection between how citizens imagine their democracy and how politics is practiced. Citizens continue to believe in the values of liberal democracy but are increasingly disillusioned with how their political systems work and the politics that are practiced in the name of democracy. This article revisits the root causes of political alienation to better understand this democratic paradox. It provides both a conceptual understanding of political alienation and its domain of action and insights into how the concept can be operationalized and measured in empirical research. It argues that while democracy itself may not be in crisis, the politics on which its operation rests is in peril.