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This chapter examines the emergence of accountability as a culturally significant concept that both reflects and shapes changes taking place in our understanding of contemporary governance. Dubnick explores how its emergence as a “cultural keyword” has transformed both the form and function of accountability, and the challenges this development poses for the study of accountable governance. 

This chapter focuses on methods for analyzing data from Internet surveys with complex survey designs in order to draw inferences that can be generalized to a target population of interest. We first review the central design issues and approaches for dealing with representativeness challenges that researchers commonly face when using online polling for persuasion research. Then, using data from a survey experiment on support for immigration reform, we demonstrate the importance of the careful choice of auxiliary information used when constructing weights for ensuring the generalizability of findings from non-representative Internet surveys.

This chapter discusses contemporary directions of agenda-setting research. It reviews the basic concept of agenda setting, the transfer of salience from the media agenda to the public agenda as a key step in the formation of public opinion, the concept of need for orientation as a determinant of issue salience, the ways people learn the media agenda, attribute agenda setting, and the consequences of agenda setting that result from priming and attribute priming. Across the theoretical areas found in the agenda-setting tradition, future studies can contribute to the role of news in media effects by showing how agenda setting evolves in the new and expanding media landscape as well as continuing to refine agenda setting’s core concepts.

This article provides a discussion on agent-based modeling. Two examples that show the ability of computational methods to extend game-theoretic results are presented. It then discusses modeling agents, modeling agent interactions, and system behaviour. In addition, it describes how agent-based models differ from and complement mathematical models and concludes with some suggestions for how one might best leverage the strengths of agent-based models to advance political science. Most mathematical analyses of game-theoretic models do not look into the stability and attainability of their equilibria and would be made richer by complementing them with agent-based models that explored those properties. The ability of computational models to test the robustness of formal results would be reason alone to add them to tool kits. As a methodology, agent-based modeling should be considered as in its infancy, its enormous potential limited only by the scientific and creative talents of its practitioners.

Public opinion’s role in shaping governmental actions is a central concern of democracy, yet the absence of systematic state-level survey data has inhibited analyses of public opinion at the subnational level. This essay traces the evolution of studies of public opinion at that level, first reviewing studies using surrogates derived from demographic variables. It next considers methodologies that develop state-level opinion from aggregated national samples. Finally, it discusses recent efforts to develop state-level opinion measures using post-sample stratification integrating limited survey data with demographic variables. There is evidence of significant cross-sectional and temporal variation in public opinion and policy across and within the states. Research on subnational public opinion once hinged on assumptions about opinion surrogates, but is now based on abundant and progressively rigorous opinion data. These studies reveal that public opinion plays an enormous role in subnational politics, with effects varying across issues, contexts, and conditions.

From an anthropological perspective, political leadership is a system of social relationships involving authority, charisma and other forms of personal or institutional power, whose rules are specific to, and embedded within, particular cultural contexts. More specifically, it is the art of controlling followers through the strategic mobilization of morality, rituals, and symbols. This article critically reviews anthropology’s contribution to the study of political leadership from the 1960s to the present. The article is in four parts. The first considers what political leadership is and why it matters. The second assesses pioneering works on leadership from 1960–1980 and the implications of the shift from small-scale, third-world communities towards more complex societies. The third considers studies since 1980, including seminal work on the relationship between political leadership, ritual and power, drawing on examples from Madagascar, Europe and the USA. The author also shows how post-1980, anthropological studies of leadership were subsumed within broader debates over ideology, hegemony, resistance, nation and state-formation, post-colonialism, and performance. Finally, the author considers some promising recent work that indicates new analytical directions. Anthropology’s key contribution lies in its attention to local social/cultural contexts, its understandings of how power is practised, and its concern with understanding the meanings of political leadership rather than simply its forms.

Network analyses of global and regional arms flows (including small arms and light weapons, major conventional weapons, and weapons of mass destruction) and related international insecurity and criminality have so far been limited. Yet the literature contains hypotheses that could be explored or tested using network analysis. This chapter discusses supply and demand effects, structural tradeoffs between security and efficiency, pressures to become more or less centralized, and the effects of geography and other network layers. It concludes by reviewing existing data sets and analyses and gauges the potential for network analysis to inform the study of arms transfer networks. Given the general import of these networks for both security studies and policy, there should be a renaissance in the study of arms supply and proliferation networks.

This chapter reviews the state of the art in at-a-distance analysis. This methodology originated in attempts by psychologists and students of policy-making and international relations to understand and predict a national or government’s policy choices by studying the verbal behaviour of key government leaders. It has since widened into an array of methods that have also found use in areas such as candidate assessment. Several key methods are presented, as are some of the key critiques and rebuttals around the issue of inferring personality characteristics from speeches and then using those to explain government policies and state behaviours. The chapter ends by critically assessing the state of the art in the field and by presenting some possible and needed advances.

This article surveys modern Bayesian methods of estimating statistical models. It first provides an introduction to the Bayesian approach for statistical inference, contrasting it with more conventional approaches. It then explains the Monte Carlo principle and reviews commonly used Markov Chain Monte Carlo (MCMC) methods. This is followed by a practical justification for the use of Bayesian methods in the social sciences, and a number of examples from the literature where Bayesian methods have proven useful are shown. The article finally provides a review of modern software for Bayesian inference, and a discussion of the future of Bayesian methods in political science. One area ripe for research is the use of prior information in statistical analyses. Mixture models and those with discrete parameters (such as change point models in the time-series context) are completely underutilized in political science.

This chapter reviews the historical development of the genre of biography in relation to the social sciences, and discusses the debates about its utility in the study of leadership. Taking key examples, it explores the contrast between the ‘common-sense, humane tradition’ said to be the bedrock of biography, and more theoretically informed approaches (especially leadership typologies, psychobiographies, and the ‘interpretive turn’) in the ways that questions of leadership are addressed. Developments in biographical methodology are a core concern. Biography, it is argued, need not be driven by an ‘individual journey’ but can be oriented to questions germane to political enquiry, especially questions of leader efficacy, achievement, or dysfunction.

Levels of interpersonal and political trust undoubtedly ebb and flow in response to external stimuli. Despite the variability in one’s environment, there is good reason to believe that interpersonal and political trust also originate from individual characteristics. In this chapter, we focus on the impact of biology and personality on trust. Biological factors and personality traits constitute relatively stable individual differences that influence perceptions, evaluations, and orientations toward the social and political world. Research on trust has examined both of these influences, and we review this literature below. The first section considers the role of biology in shaping trust, and the second examines trust as a dimension of personality and as an individual orientation that can be shaped by personality. We then present a brief statistical analysis of the impact of personality traits on interpersonal and political trust. The last section summarizes the discussion and suggests avenues for future research.

This article presents some guidance by cataloging nine different techniques for case selection: typical, diverse, extreme, deviant, influential, crucial, pathway, most similar, and most different. It also indicates that if the researcher is starting from a quantitative database, then methods for finding influential outliers can be used. In particular, the article clarifies the general principles that might guide the process of case selection in case-study research. Cases are more or less representative of some broader phenomenon and, on that score, may be considered better or worse subjects for intensive analysis. The article then draws attention to two ambiguities in case-selection strategies in case-study research. The first concerns the admixture of several case-selection strategies. The second concerns the changing status of a case as a study proceeds. Some case studies follow only one strategy of case selection.

This article focuses on a third generation of qualitative methods research. Third-generation qualitative methods provide a unique bridge between the single-logic-of-inference and interpretivist communities. Accepting comparison and intuitive regression as part of its underlying justification, the third-generation case study approach is readily compatible with large-n studies, as well as being accepting of many of the claims of the comparative advantages offered by quantitative methods. The article considers some of the ways in which the third generation has developed and suggest potentially fruitful directions for future research. It focuses on some key innovations in third-generation qualitative methods over the last decade regarding within-case analysis, comparative case studies, case selection, concepts and measurement, counterfactual analysis, typological theorizing, and Fuzzy Set analysis. It concludes with a discussion of promising avenues for future developments in qualitative methods.

This article presents a reconstructed definition of the case study approach to research. This definition emphasizes comparative politics, which has been closely linked to this method since its creation. The article uses this definition as a basis to explore a series of contrasts between cross-case study and case study research. This article attempts to provide better understanding of this persisting methodological debate as a matter of tradeoffs, which may also contribute to destroying the boundaries that have separated these rival genres within the subfield of comparative politics.

This article investigates the tradition of case-oriented configurational research, focusing specifically on qualitative comparative analysis (QCA) as a tool for causal inference. It first presents two analytic procedures commonly used by comparative researchers. A short description of the state-of-the-art of QCA applications is offered, in terms of discipline, types of cases, models, combinations with other methods, and software development. It then reviews different uses of QCA, as well as generic ‘best practices’. Some key recent evolutions are illustrated: on the one hand the development, beyond dichotomous ‘crisp set’ QCA (csQCA), of multi-value QCA (mvQCA), fuzzy sets, and fuzzy-set QCA (fsQCA), and on the other hand technical advances and refinements in the use of the techniques. Finally, the article gives some concluding reflections as to expected developments, upcoming innovations, remaining challenges, expansion of fields of application, and cross-fertilization with other approaches.

Though scholars have developed an increasingly rich set of research findings regarding the structure of political networks, identifying causal associations between these networks and political outcomes of interest presents a variety of challenges. Addressing these challenges is especially important given the prominence of networks in theories of individual and collective behavior. This chapter uses the framework of the Neyman-Rubin causal model (potential outcomes framework) to discuss challenges to identification researchers face when studying how networks affect political outcomes. It then describes a set of strategies researchers can employ to address these challenges, including suggestions for best practices in the context of both observational and experimental research designs.

This article discusses methods that combine survey weighting and propensity score matching to estimate population average treatment effects. Beginning with an overview of causal inference techniques that incorporate data from complex surveys and the usefulness of survey weights, it then considers approaches for incorporating survey weights into three matching algorithms, along with their respective methodologies: nearest-neighbor matching, subclassification matching, and propensity score weighting. It also presents the results of a Monte Carlo simulation study that illustrates the benefits of incorporating survey weights into propensity score matching procedures, as well as the problems that arise when survey weights are ignored. Finally, it explores the differences between population-based inferences and sample-based inferences using real-world data from the 2012 panel of The American Panel Survey (TAPS). The article highlights the impact of social media usage on political participation, when such impact is not actually apparent in the target population.

This chapter explores the dual concern with causality and time in historical-institutionalism using a graphical approach. Conceptualizing causes as filters, the chapter analyses three concepts that are central to this field: critical junctures, gradual change, and path dependence. The analysis makes explicit and formal the logic underlying studies that use these “causal-temporal” concepts. The chapter shows visually how causality and temporality are linked to one another in varying ways depending on the particular pattern of change. Through this unifying visual grammar, the chapter also outlines an approach that can accommodate and reconcile both models of critical junctures and gradual change. The chapter provides new tools for describing and understanding change in historical institutional analyses.