Theory is the essential foundation on which an empirical network study is built. A network theory stipulates a certain, carefully defined network and offers a reason why it relates to other variables. Pinning down what the precise network of theoretical interest is and fleshing out a reason why it matters is what makes up the key preliminary work in empirical networks research design. It can be tempting to rush through this preliminary step, especially when data are readily available. Note that doing so comes with risks. Design blunders are more debilitating in networks research than in other data collection endeavors. Thinking through all aspects of a theoretical setup takes time, but is part of the real work of research design. Taking the time early is an investment in avoiding wasted effort later. This chapter presents a framework to help construct a theory that is maximally useful for guiding empirical research design.

Chapter 2 covers the basics of research design.It is written so that students without any research design experience or coursework can learn common research designs to enable them to conduct statistical analyses in the text.Hypotheses development with variable construction (dependent and independent variables) are covered and applied to experimental and non-experimental designs.Survey methods including question construction and implementation of surveys is presented.

Over the years, the Serengeti has been a model ecosystem for answering basic ecological questions about the distribution and abundance of organisms, populations, and species, and about how different species interact with each other and with their environment. Tony Sinclair and many other researchers have addressed some of these questions, and continue to work on understanding important biotic and abiotic linkages that influence ecosystem functioning. In common with all types of scientific inquiry, ecologists use predictions to test hypotheses about ecological processes; this approach is highlighted by Sinclair’s research that explored why buffalo and wildebeest populations were rapidly expanding. Like other scientists, ecologists use observation, modeling, and experimentation to generate and test hypotheses. However, in contrast with much biological inquiry, ecologists ask questions that link numerous levels of the biological hierarchy, from molecular to global ecology.

The introduction asks the question of why social scientists should study virtues empirically. It offers five reasons: (1) humans are moral animals, (2) moral behavior can be understood as an expression of acquired traits, (3) it is psychologically realistic to think that ordinary humans can acquire and express virtue traits, (4) moral education is valuable, and (5) virtues are often taken to be essential to a good life. The Introduction then addresses three challenges that virtue scientists must face: (1) the absence of empirically oriented virtue theory, (2) the overreliance of simple survey design in psychology, and (3) virtue skeptics. The Introduction concludes with an outline of the chapters of the book and how these chapters comprise the sections of the book.

This chapter considers the appropriate roles that philosophy can play in virtue science. It develops three categories of philosophical work: (1) work that is not especially relevant to virtue science and can be set aside; (2) work that is relevant to virtue science, but is conceptual rather than empirical; and (3) philosophical topics that can be translated into testable hypotheses. Group 1 comprises the kind of philosophical work that seeks maximum generality, often transcending humans. This work can be set aside in virtue science, which is focused on human virtue. Group 2 includes philosophical work that is primarily conceptual and cannot be resolved empirically. This work includes many contentious premises on which virtue scientists may well have to take a position. We recommend that virtue scientists briefly discuss the issue and simply take a position without trying to resolve the issue. Group 3 includes philosophical positions that are amenable to empirical testing. Our recommendation is for virtue scientists to formulate and test such philosophical premises. For example, there is much philosophical debate about whether knowledge is important to virtue, and this debate can and should be tested empirically.

Some neo-Aristotelians see a strong link between virtues and eudaimonia or flourishing, but others do not. After acknowledging this difference, the chapter explores some of the possible implications of this link. The view explored in this chapter is that virtues contribute to success in goal and good pursuit, which, in turn, contributes to a flourishing life. The neo-Aristotelian view examined holds that there are things that are good for humans qua humans (e.g., close personal relationships, group belonging). Success in pursuing these goods is hypothesized to be correlated with eudaimonia. It explores several challenges in studying eudaimonia, but concludes that eudaimonia research should continue and be updated as conceptualization and measurement improves. The chapter concludes with a discussion of three well-documented human goods (close personal relationships, group belonging, and meaning) and their hypothesized relationships with specific virtues (e.g., loyalty, forgiveness, honesty).

Good research ideas and hypotheses do not just magically exist, begging to be tested; they must be discovered and nurtured. Systematic methods can help. Drawing on relevant scholarly literatures (e.g., research on creativity) and on the published personal reflections of successful scientists, this chapter provides an overview of strategies that can help researchers to (1) gather research ideas in the first place, (2) figure out whether an idea is worth working on, and (3) transform a promising idea into a rigorous scientific hypothesis. In doing so, it provides pragmatic advice about how to get good ideas and make the most of them.

After summarising our findings in the preceding chapters, the Conclusion assesses the relative merits of experimental philosophy and empiricism as historiographical categories, and in the process we respond to some of our critics. We examine the historicity of both notions, their disciplinary and chronological scope, their contrast classes, namely, speculative philosophy and rationalism, and their explanatory power. Through an examination of the anti-hypotheticalism so prevalent in the early modern period and Margaret Cavendish’s published critique of experimental philosophy, we argue that experimental philosophy, together with the experimental/speculative distinction, have more explanatory power than the rationalism/empiricism distinction.

Chapter 2 presents the (formal) theoretical framework and advances four arguments. First, whether or not majority support for public provision of insurance exists depends on the distribution of information. Second, some insurance is best provided via pay-as-you-go systems, but these involve a difficult time-inconsistency problem that private markets cannot solve. Some social insurance is therefore bound to remain almost entirely within the purview of the state. Third, people’s preferences regarding social insurance are also a function of the availability of private options. If social insurance is the only game in town, even those subsidizing the system will support it, leading to broad cross-class majorities. With private alternatives, the better-off will lower their support for public spending, which erodes the broad support public social policy programs traditionally enjoy. Fourth, parties continue to matter because they represent different risk groups, and we expect that partisan conflicts will extend into new areas, most importantly the regulation of information and how it may be used.

Since the objective of our research is to examine the influence of the creative potential of language speakers on their creative performance in the formation and interpretation of new/potential complex words, there are several fundamental methodological principles that have to be taken into consideration. First of all is the method of measuring the creative potential of language speakers and the methods of testing their creative performance Therefore, this chapter introduces the Torrance Test of Creative Thinking, accounts for the basic characteristics of creativity indicators and subscores, and justifies its relevance to our research. Furthermore, it presents a word-formation test and a word-interpretation test and accounts for their objectives and principles of evaluation. A sample of respondents, comprising a group of secondary school students and a group of university students, is introduced. A method of evaluating the data is explained, based on the comparison of two cohorts with opposite scores. Finally, this chapter presents the hypotheses underlying our research.

The last two decades have seen remarkable developments in our understanding of early modern natural history. Historians have closely scrutinized its research methods, experimental practices, and methodological and epistemological commitments. Building on this recent scholarship, this chapter focuses on a particularly important type of natural history deriving from Francis Bacon, namely, experimental natural history. We show that this new form of natural history provided many branches of natural philosophy with a method for organizing the study of nature—of determining their desiderata, applying experiment, and structuring and exploiting their evidential and observational bases. The most important contributions of experimental natural history to the Scientific Revolution were the elaboration of a new philosophy of experimentation and the introduction of new, practice-based systems of classification.

Chapter 2 develops the principal claim of the book, which posits that foreign aid delivery is endogenous to national structures. The chapter begins with a brief historical account of how patterns of foreign aid delivery have evolved since the end of World War II. It then fleshes out three theoretical and empirically informed observations about aid decision-making: (1) that aid officials, as key decision-makers, seek to minimize risk in aid delivery, that (2) their response to risk is conditional on the rules and practices that make up the national aid organizations in which they operate, and (3) that these rules and practices have ideological origins that inform us about the substance of aid delivery: why it is that aid officials choose to bypass or engage with the recipient government.

It significantly strengthens the inferences drawn based on QCA results if we connect these results to theoretical knowledge and within-case evidence before, during, and after the analysis. In this chapter, we discuss two prominent tools of doing so after the analytic moment – set-theoretic theory evaluation and set-theoretic multi-method research (SMMR) – and demonstrate their implementation within R. Theory evaluation is a form of re-assessing theoretical hunches based on the results generated by QCA. While it can also be used for the identification of interesting cases for follow-up case studies, this task is better achieved with set-theoretic multi-method research. The latter is a tool for identifying typical and deviant cases for comparative or single within-case analysis.

Learning goals:

- Basic understanding of what theory-evaluation and set-theoretic multimethod research are.

- Familiarity with how to apply formal set-theoretic theory evaluation for re-assessing theoretical hunches based on the results generated by QCA.

- Familiarity with how to use set-theoretic multi-method research (SMMR) for the identification of cases for follow-up case studies after QCA.

- Ability to implement theory evaluation and SMMR in R.

Chapter 1 provides introductory information on empiricism, the stages and elements of the research process; quality criteria; basic types of research questions and methodological approaches, data collection, documentation and analysis, interpretation, reflection and presentation of the findings; and research ethics. Chapter 1 also contains detailed instructions for keeping research diaries and making poster presentations as forms of documentation and presentation which we recommend for student projects, as well as short exercises and recommendations for further reading.

The main aim of Part 2 is to explain how the form of the good gives rise to knowledge of forms, the forms in question being of virtues and virtue-related things. This ramifies into discussions of dialectic and mathematics, the ambiguous property 'clearness' (saphēneia), hypotheses, and the non-hypothetical principle. It is proposed that the form of the good is interrogative. This position is defended against philosophical and textual objections, and argued to be preferable to alternatives. There is discussion of why Plato excludes the use of diagrams from dialectic and whether he can allow input from experience. The role of context in the rulers' dialectic is explained, and becomes the basis for explaining why Plato's treatment of dialectic in the Republic remains at the level of a sketch. There is an exploration of the difference between true philosophers and sight-lovers, and of the criteria and scope of 'good' in dialectic. This last discussion encounters the classic problem of the connection between Plato's 'justice in the soul' and just conduct as ordinarily recognized, and a solution to this problem is proposed.

In this concluding chapter I first summarize the key findings across the three case studies, and offer an overall conclusion to the research question posed in the introduction. I also discuss some hypotheses, generated from the case study findings, which may explain the variations between cases and the variations between different types of accountability mechanisms. Finally, I sketch out some aspects of a reform agenda.

This overview of the book introduces the Human System as an open, historical, and adaptive system, formed 70,000 years ago by a founding human community as its members created syntactic language. The system grew to the point where it is now in trouble because of excessive growth and painful social inequality. Analysis relies on Darwinian assumptions of evolutionary growth – biological, cultural, and social – as these processes coevolve with each other and with Gaia, a model of the natural world of living things. The discipline of world history is introduced to provide the framework for the narrative and the underlying analysis: world history combines concepts, data, and perspectives from multiple disciplines in natural and social sciences. It gives special attention to behavior of human groups as well as individuals. The chapter concludes by reviewing the book’s argument, presenting two or three historical and analytical hypotheses for each chapter: these hypotheses are to be documented, tested, and debated in the details of each chapter.

A clearly defined research question allows us to formulate hypotheses that propose possible answers to that question. From these hypotheses, we can then derive specific, unambiguous predictions that allow us to test their validity with empirical data. Hypotheses and predictions serve to narrow down the infinite possibilities for data collection and determine the data we need to collect. In this chapter I cover formulating hypotheses and predictions, then explain that we often use proxies to test predictions and how practical constraints influence our thinking.