While ethnography produces highly contextualized understandings of fields of practice, it is hard to assess whether the phenomena revealed through ethnographic study are typical on a regional level. To overcome this shortcoming, I introduce a research design, ethnographic upscaling, that combines in-depth ethnography with larger-N regional comparisons. While the in-depth ethnography provides valid hypotheses, comparison allows the testing of whether an observed phenomenon can be generalized. To illustrate ethnographic upscaling, I present research on the social engineering of water governance in Namibia. In the course of political “decentralization,” and inspired by community-based natural resource management policies, pastoralists have developed new rules stipulating how to share water and distribute the costs of providing it. While all communities were exposed to similar blueprints, local social practices concerning water governance differ. I show that these variations can be explained if we combine an ethnographic understanding of the dynamics within communities with an understanding of both networks that impinge on the individual cases and influences of external authorities.

This introductory chapter provides an overview of comparative ethnographic research in anthropology as an explicit methodological strategy and organizing framework for the different chapters of this book. The chapter opens with a discussion of the enduring promise of comparative ethnographic research as well as its main challenges given late-twentieth-century disciplinary criticisms. It then provides a summary of the process and kinds of comparative ethnographic research. We argue that ethnographic comparisons in recent decades increasingly bridge the divide between particularistic approaches and more generalizing strategies used in the past. These configurational comparisons focus on understanding and explaining the diversity of social configurations across cases and scales and interpreting their cultural and historical significance. This introduction then discusses the contributions each chapter makes to the development of this comparative paradigm by providing examples of successful comparative ethnographic research in the contemporary milieu.

The notion that comparison is not the search for similarities but the systematization of differences leads to the question of which shared set of concepts and assumptions might be employed to explore this notion. Comparative analysis should at once reduce the complexity of data in the service of comparison and yet still reference the uniqueness and specificity of local values and ideas. Three types of comparison potentially fulfill these criteria. Claude Lévi-Strauss traces the transformations of oppositions and codes across cultural boundaries without claiming to compare societies as such. Louis Dumont contrasts systems of values that represent societies-as-wholes by analyzing their structuring into hierarchical levels. Niklas Luhmann’s theory of autopoietic systems enables the comparison of relationships between social systems and their environments, without assuming societies as units of comparison – examples being the making of ethnic identities and boundaries. A synthesis of the three approaches provides avenues of comparison in a globalized world, as is exemplified by the author’s own work in upland Southeast Asia.

Comparison figured centrally in the GLOBALSPORT project, which investigated the migration of athletes and aspiring athletes in various sports, along several geographical and aspirational trajectories. In its initial design, the project was framed by broad generalizations. Not surprisingly, field researchers encountered specificities during their fieldwork, which contradicted some of the original insights. The team had to grapple with the tension between comparisons across sites and the unique contexts found in each site. The common thread in all subprojects was the presence of global sport industries in people’s lived experiences. These industries have undergone major reconfigurations through corporatization, mediatization, and commercialization, which have engendered a dramatic increase in athletes’ transnational mobility. This mobility and the industries that create and sustain it have restructured individual lives and cultural expectations as preconditions for success. The comparisons reveal common themes in the transformation of key aspects of experience. But comparison also reveals how different scalar processes configure these themes in the contexts of specific field sites.

How do anthropologists think with comparison? This is the core question addressed in this chapter. I draw on examples from my own research to show how comparison, as an epistemological stance, suggests not only questions to be explored during research but also avenues of interpretation and insight during analysis. I argue that comparison (1) helps to illuminate the significance of context in explanation; (2) makes similarities and differences more visible and hence deepens and extends our understanding of critical social and cultural processes; and (3) addresses the tension between the general and the particular, a tension fundamental to anthropology throughout its history. The chapter focuses on three projects where I used comparison to study migrant populations. These projects highlight the role of comparative thinking in relation to distinct scales or units of analysis: different national contexts (Portugal and Ireland), different regions of immigration settlement (French Canadian immigrants in the eastern and midwestern United States), and between immigrant populations of different national origins (Indians and Vietnamese) who have settled in one US city.

Exploratory research is an attempt to discover something new and interesting by working through a research topic and is the soul of good research. Exploratory studies, a type of exploratory research, tend to fall into two categories: those that make a tentative first analysis of a new topic and those that propose new ideas or generate new hypotheses on an old topic. This chapter examines the history of exploratory studies, offers a typology of exploratory studies, and proposes a new type of exploratory study that is especially helpful for theorizing empirical material at an early stage. It argues that exploratory studies are an important part of a social scientist’s toolkit.

This chapter reviews a broad emerging literature on research transparency and reproducibility. This recent literature finds that problems with publication bias, specification searching, and an inability to reproduce empirical findings create clear deviations from the scientific pillars of openness and transparency of research. These failings can also result in incorrect inferences.

Measurement replication is the ability to replicate a study’s recorded measurements, using the original study’s same measurement parameters or coding rules, the same research design, and the original sample of the same population. Measurement replication is an important element of replication writ large and is essential for knowledge accumulation, since failure to replicate measurement casts doubt on the internal validity of a studies based on those data. Measurement replication is equally important for both quantitative and qualitative scholarly research, having revealed measurement errors in both types of research. This chapter argues for the continued need for measurement replication for exposing errors in fact, interpretation and context, and consistency of application.

Studies have shown that US college and university professors are disproportionately left-leaning and Democratic and these tendencies are especially pronounced in the social sciences. Critics of this ideological homogeneity have leveled a wide range of charges in light of these findings: that these political orientations seep into research and teaching, that it affects accumulated knowledge, policymaking, student attitudes, American political culture, and that it promotes motivated reasoning, bias, and groupthink. This chapter reviews the most credible of the arguments for greater ideological diversity and attempts to move beyond applied concerns by asking whether and how discussion of political diversity and bias in academia might be reconceptualized to form the basis for meaningful empirical studies.

Social science research is increasingly moving toward a model of open and accessible data. Accessibility opens possibilities of allowing secondary analysis, enhancing pedagogy, and supporting research transparency. This chapter argues that these benefits will accrue more quickly, and will be more significant and more enduing, if researchers make their data "meaningfully accessible," that is, when the data can be interpreted and analyzed by scholars far beyond those who generated them. Making data meaningfully accessible requires researchers to prepare data for sharing and to take advantage of a growing range of tools for publishing and preserving data.

Evaluating the impact of a work, scholar, or department is a longstanding practice in the academy. Recent advances in computation and database access have increased the ease of quantifying many impact measures. These advances hold the potential to approach systematically questions that have previously been treated in an ad hoc or individual manner. Extant systems, however, contain a variety of shortcomings and have the potential to exacerbate existing inequalities and biases. This chapter assesses the current state of impact metrics and considers the limitations on this information.

Replication, the application of the same methods to new data, is a practice that applies to orthodox statistical analysis and experimental research. Reliability of inference is a broader concept that encompasses replication and reproducibility, but is a broadly shared goal of all scientific inquiry, both quantitative and qualitative. This chapter presents a Bayesian framework for same-data scrutiny in quantitative research. This approach provides clear framework for scrutinizing arguments and evidence and contributes to knowledge accumulation.

The extant individualized appraisal system consisting of literature reviews in single studies, review articles, and the academic journal and press review system is insufficient for generating a comprehensive appraisal of what is (and is not) known on a given topic. This chapter presents a proposal for a new approach to comprehensive appraisal based on a lengthy paper or report that evaluates a scientific question in an encompassing fashion, assigning a degree of (un)certainty to each hypothesis under review and encompassing all work that has been conducted on a subject, published or unpublished. This type of appraisal would not overtake the primacy of discovery studies, nor would it completely supplant individual appraisal. Rather, it would complement both by allowing exploratory work to be properly vetted.