Arts, Humanities, and World Languages

Political science research, particularly in international relations and comparative politics,has increasingly become dominated by statistical and formal approaches. The promise of these approaches shifted the methodological emphasis away from case study research. In response, supporters of case study research argue that case studies provide evidence for causal claims that is not available through statistical and formal research methods, and many have advocated multimethod research. I propose a way of understanding the integration of multiple methodologies in which the causes sought in case studies are treated as singular causation and contingent on a theoretical framework.

Natural experiments are an increasingly popular research design in political science. This popularity raises a number of questions. First, what are natural experiments and why are they appealing? Second, what makes a good natural experiment? And finally, are natural experiments able to provide resources for knowledge production that other methodologies cannot or do not provide? Using Mary Morgan’s and Thad Dunning’s recent work on natural experiments, I offer answers to the first two questions and use the analysis to argue that natural experiments highlight features of knowledge production that support methodological pluralism and the multiple aims of research.

Coding, a widespread practice in the social sciences, is a way of representing abstract or latent concepts in order to produce a dataset in which such concepts figure. While coding is often associated with the quantification of what otherwise might be thought of as qualitative data, the data need not be represented in a quantitative form. Dichotomous coding or coding on a
qualitative scale is also used in political science. If we think of measurement as involving three elements -- identification of the concept to be measurement, identification of a metric to which
that concept will be matched and rules or procedures through which the matching is to be done -- the question of whether such qualitative representation counts as measurement becomes a question of whether a metric must be numerical. Since this is disputed, there may be some question about whether coding in political science always qualifies as measurement. However, political methodologists standardly treat coding as measurement and I will do so here.
      Questions of measurement are intertwined with questions of standardization and accuracy. But standardization, a kind of uniformity, and accuracy both suggest a single end point of measurement and a single goal that measurement will serve. I argue that in the social sciences measurement of a concept like democracy using one standard may not be desirable and the sort of accuracy such a measure implies may not be appropriate. Consequently, an examination of
measurement in the sphere of political science points to pluralism both in the aims of measurement and in the goals of research and knowledge production in which measurement
figures.
    Briefly, plural measures may be desirable since decisions about how best to code, or measure, social concepts may affect the conclusions that can be drawn from the resulting data.
Minimally, transparency about such decisions is needed. We also may want to retain multiple
datasets resulting from different coding (measurement) practices given that choices about coding are partially driven by multiple epistemic and pragmatic considerations. In addition, while measurement frequently is a step in testing hypotheses, the practices involved in developing a measure and the questions about the appropriate means to do so fulfil other research goals that sometimes are overlooked when we focus on testing as the main aim of research.
    I use Hasok Chang’s idea of epistemic iteration developed in his historical/philosophical work on measuring temperature as a resource to explore how measurement in political science
involves pluralism both in relation to the goals of research and in relation to the plurality of
activities that play a role in knowledge production.2 In doing so I challenge the widely held presuppositions that we are seeking one answer to the question ‘What is the best measure of
democracy?’ and that the goal of developing that measure is testing hypotheses.

In A Tale of Two Cultures: Qualitative and Quantitative Research in the Social Sciences, Gary Goertz and James Mahoney argue that there are fundamental differences quantitative and qualitative research traditions in political science.  These differences include different sets of values, beliefs, and norms that result in different research procedures and practices and thus the different traditions might be characterized as constituting different cultures. The result is that while within tradition conversations are often rich and productive, across traditions conversations are typically “difficult and marked by misunderstanding”(2012, 1).

One area in which these differences are particularly apparent is in the approaches taken to the investigation of causes.  While quantitative researchers typically seek effects-of-causes through methods that identify average effects, qualitative researchers are often more focused on causes-of-effects, questions of how a particular hypothesized causal factor might give rise to a particular effect within an examined case. Quantitative researchers are thus concerned with causal relations at a population level whereas qualitative researchers are focused on events at the level of individuals.

Such pluralism within disciplines has recently been examined by Sandra Mitchell (2009), who argues for “integrative pluralism,” and Helen Longino (2013), who suggests that in at least some cases different approaches are fundamentally incommensurable. I consider the question of how to think about different approaches to causality in political science using the work of Mitchell and Longino as a framework. I sketch a procedure for thinking about whether and when approaches can be integrated by identifying two dimensions to consider: how the objects of inquiry are conceived and the inferences that different concepts of causality can support. Questions of integration or incommensurability will depend on these factors and communication between the “two cultures” of political science may be facilitated through their consideration.

Despite the growing appeal of multi-method designs, there have been few efforts to address the particular problems that arise from combining studies of populations, rooted in a probabilistic conception of causality, and studies of cases rooted in a mechanisms approach. This paper draws on recent philosophy of science to address the requisites of successful integration and proposes a specific multi-method approach to the study of rare events. The distinctive feature of the approach is causal process observation of all of the events in the corresponding panel design. Rather than focusing on strategies that confirm average treatment effects findings, this approach draws particular attention to confirming/disconfirming cases and how they might be used to generate new populations of cases or types. These in turn help specify scope conditions of the theory.

Through a discussion of the way science has been used to address intersexuality, I explore an idea about how to understand science as objective and yet influenced by social, historical, and cultural factors. I propose that the Semantic View of theories provides a means of understanding how science describes reality, and I look a t the way science has been used to distinguish the sexes to provide an illustration.

There are a variety of ways that one could examine feminist contributions to anthropology and sociology within the context of a handbook on philosophy of science. The first and most obvious is to simply catalogue the various contributions that feminism has made to each of these disciplines, in part through the increasing presence of women in these fields. Sandra Harding refers to this approach as the "women worthies" or the "women's contributions" projects in a feminist science [1986]. These projects are respectively, rediscovering and honoring women who were forgotten contributors and cataloguing their efforts. As Harding notes, these projects, while worthwhile, do not fundamentally alter the nature of the disciplines in question and do not offer much from the perspective of philosophy of social science. A second possibility would be to note the changes in content that feminism has worked in these two fields, and, indeed, there have been many such changes. Again using Harding's terminology, the "victimology" project of chronicling the various forms of neglect caused by androcentric science falls into this category. This approach is more germane to the question of how feminism affected the development of anthropology and sociology. Feminism filled gaps both in what was studied and the categories with which the disciplines organized the objects of study. 1 While interesting and transformative of these disciplines in many ways, the fundamental nature of the scientific enterprise in these fields was nonetheless not challenged through these critiques either. These two approaches to the role of feminism in shaping anthropology and sociology deal only with the addition of women and women's concerns to an existing discipline, both when women are the scientists and when they and their lives become the object of study. Feminism offers something unique, revolutionary, or transforming for these social sciences only if it tackles the theoretical frameworks and methodologies that define these sciences. Judith Stacey and Barrie Thorne offer the following analysis in their "The Missing Feminist Revolution in Sociology". "The initial period is one of filling in gaps-correcting sexist biases and creating 1 For instance, gender was introduced as a relevant social category.

Feminist philosophy of science has been criticized on several counts. On the one hand, it is claimed that it results in relativism of the worst sort since the political commitment to feminism is prima facie incompatible with scientific objectivity. On the other hand, when critics acknowledge that there may be some value in work that feminists have done, they comment that there is nothing particularly feminist about their accounts. I argue that both criticisms can be addressed through a better understanding of the current work in feminist epistemology. I offer an examination of standpoint theory as an illustration. Harding and Wylie have suggested ways in which the objectivity question can be addressed. These two accounts together with a third approach, 'model-based objectivity', indicate there is a clear sense in which we can understand how a standpoint theory both contributes to a better understanding of scientific knowledge and can provide a feminist epistemology.

Empirical research on democracy depends upon data. The need for such data has led to the development of measures of democracy. Measurement models are evaluated in terms of their reliability and validity, both of which may be thought of as related to the objectivity of the measure. Using the Varieties of Democracy Project (V-Dem) as an example, I consider how assessing reliability and validity of measurement models is challenging and argue that democracy might be understood as measured objectively when it is subject to theoretical, empirical, and pragmatic constraints. I call this coherence objectivity .

Most contemporary political science researchers are advocates of multimethod research, however, the value and proper role of qualitative methodologies, like case study analysis, is disputed. A pluralistic philosophy of science can shed light on this debate. Methodological pluralism is indeed valuable, but does not entail causal pluralism. Pluralism about the goals of science is relevant to the debate and suggests a focus on the difference between evidence for warrant and evidence for use. I propose that case study research provides evidence for use through providing information that bears on the applicability of causal generalizations and risk assessment.

Feminist philosophy of science appears to present problems for the ideal of value‐free science. These difficulties also challenge a traditional understanding of the objectivity of science. However, feminist philosophers of science have good reasons for desiring to retain some concept of objectivity. The present essay considers several recent and influential feminist approaches to the role of social and political values in science, with particular focus on feminist empiricism and feminist standpoint theory. The similarities and difference, as well as the strengths and weaknesses of these approaches are explored. The essay concludes with suggestions for future research in the area of feminist epistemology and philosophy of science.

Natural experiments are an increasingly popular research design in political science. This popularity raises a number of questions. First, what are natural experiments and why are they appealing? Second, what makes a good natural experiment? And finally, are natural experiments able to provide resources for knowledge production that other methodologies cannot or do not provide? Using Mary Morgan’s and Thad Dunning’s recent work on natural experiments, I offer answers to the first two questions and use the analysis to argue that natural experiments highlight features of knowledge production that support methodological pluralism and the multiple aims of research.

Process tracing is a familiar analytical tool in a number of sciences. Successful process tracing pulls together what is already known, believed or assumed and the various events, activities and entities in a case study in order to construct a narrative of the case. Several chapters in this volume offer accounts of narrative science that are explored through process tracing. These examples are analysed to reveal how various aspects of process tracing inform narrative and how narrative, in turn, aids process tracing in an iterative process of interpretation and reinterpretation of evidence, testing, development and revision of hypotheses, and the explanation of singular events.