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In a collection of essays from prominent music scholas both in the Czech Republic and abroad, this book provides a nuanced overview of major topics connected to the history of musical culture in the Czech lands (Bohemia, Moravia, and Silesia) from the Middle Ages to the present. Whereas most previous English-language musicological scholarship on the Czech lands focused solely on music that was understood as ethnically Czech, this book also considers musical cultures of non-Czech groups that lived, and sometimes still live, in the geographical area, most importantly people of German, Jewish, and Romani backgrounds. Spanning over a thousand years, this book combines innovative approaches to present nuanced perspectives on a complicated musical tradition. This is the first overview of music in the Czech lands to provide such an inclusive view of the region's musical developments.
In today's globalized world, a deep understanding of how culture affects international business phenomena is critical to scholarship and practice. Yet, armed with only superficial measures of national cultural differences proliferated by easy-to-use, statistically testable, generalized classifications, scholars and practitioners find themselves stereotype rich and operationally poor where culture meets real-world international business context. “Culture” is much more complex: made up of various multifaceted and interacting spheres of influence – national, regional, institutional, organizational and functional – and enacted by individuals, many who are multicultural themselves. International business settings are therefore rife with multilevel cultural interactions as individuals with differing cultural assumptions work together in real time (often virtually) across distance and differentiated contexts. Ethnography is the most effective approach for gaining insights into such microlevel embedded cultural phenomena. This coursebook provides detailed examples of three types of ethnography especially suited to researching and building theory in today's complex cultural environments.
How can societies effectively reduce crime without exacerbating adversarial relationships between the police and citizens? In recent decades, perhaps the most celebrated innovation in police reform has been the introduction of community policing, where citizens are involved in building channels of dialogue and improving police-citizen collaboration. Despite the widespread adoption of community policing in the United States and increasingly in the developing world, there is still limited credible evidence about whether it realistically increases trust in the police or reduces crime. Through simultaneously coordinated field experiments in a diversity of political contexts, this book presents the outcome of a major research initiative into the efficacy of community policing. Scholars from around the world uncover whether, and under what conditions, this highly influential strategy for tackling crime and insecurity is effective. With its highly innovative approach to cumulative learning, this project represents a new frontier in the study of police reform.
Digital methods in healthcare research have been steadily gaining ground but, until recently, were superseded by conventional face-to-face approaches wherever possible. However, the COVID-19 pandemic rendered in-person forms of data collection largely impossible, propelling digital approaches to the forefront. This book offers a digital lens in the participatory perspective of ethnography, a qualitative methodology. A series of chapters from internationally distinguished and rising authors present digital platforms and techniques and apply these to a wide range of healthcare studies. The authors highlight the different aspects of digital research approaches as well as reflecting on and proffering digital approaches to qualitative research for the future. Will these new digital health techniques be embraced, or will researchers be keen to revert to the traditional methods? With its unique approach, this is an invaluable resource for both prospective and experienced qualitative researchers in a broad array of medical and health disciplines.
A user-friendly introductory guide to the empirical study of social networks. Jennifer M. Larson presents the fundamentals of social networks in an intuition-forward way which guides theory-driven research design. Substantial attention is devoted to a framework for developing a network theory that will steer data collection to be maximally informative and minimally frustrating. Other features include: Coverage of a range of practical topics including selecting operationalizations, cutting survey costs, and cleaning data; A tutorial for getting started in analyzing networks in R; Technical sections full of examples, points to hone intuition, and practice problems with solutions. Designing Empirical Social Networks Research will be a valuable tool for advanced undergraduates, Ph.D. students in the social sciences, especially political science, and researchers across the social sciences who are new to the study of networks.
Linear regression analysis, with its many generalizations, is the predominant quantitative method used throughout the social sciences and beyond. The goal of the method is to study relations among variables. In this book, Schoon, Melamed and Breiger turn regression modeling inside out to put the emphasis on the cases (people, organizations, and nations) that comprise the variables. By re-analyzing influential published research, they reveal new insights and present a principled way to unlock a set of more nuanced interpretations than has previously been attainable. The emphasis is on intuition and examples that can be reproduced using the code and datasets provided. Relating their contributions to methodologies that operate under quite different philosophical assumptions, the authors advance multi-method social science and help to bridge the divide between quantitative and qualitative research. The result is a modern, accessible, and innovative take on extracting knowledge from data.
Those who seek change in civic life have much in common: they each bring valuable expertise to the table and need to strategize with others about what to do. That's why new collaborative relationships between diverse thinkers are essential. Yet they're difficult to form. Collaborate Now! presents a new argument about why that is, along with tools to foster them anew. As with any form of voluntary civic engagement, these relationships require time and motivation. Yet on top of that, collaborators often start off as strangers, and are uncertain about relationality: whether they'll relate to each other in ways that are meaningful and brimming with interaction. Using case studies, field experiments, interviews, and observational data, this book provides a rich understanding of the collaborative relationships needed to tackle civic challenges, how uncertainty about relationality can produce an unmet desire for them, and actionable tools to surface and meet this desire.
A state-of-the-art comprehensive exposition of combining Qualitative Comparative Analysis (QCA) and case studies, this book facilitates the efficient use and independent learning of this form of SMMR (set-theoretic multi-method research) with the best available software. It will reduce the time and effort required when performing both QCA and case studies within the same research project. This is achieved by spelling out the conceptual principles and practices in SMMR, and by introducing a tailor-made R software package. With an applied and practical focus, this is an intuitive resource for implementing the most complete protocol of SMMR. Features include Learning Goals, Core Points, and Empirical Examples, as well as boxed examples of R codes and the R output it produces. There is also a glossary for key SMMR terms. Additional online material is available, comprising machine-readable datasets and R scripts for replication and independent learning.
Taking a pragmatist approach to methods and methodology that fosters meaningful, impactful, and ethical research, this book rises to the challenge of today's data revolution. It shows how pragmatism can turn challenges, such as the abundance and accumulation of big qualitative data, into opportunities. The authors summarize the pragmatist approach to different aspects of research, from epistemology, theory, and questions to ethics, as well as data collection and analysis. The chapters outline and document a new type of mixed methods design called 'multi-resolution research,” which serves to overcome old divides between quantitative and qualitative methods. It is the ideal resource for students and researchers within the social and behavioural sciences seeking new ways to analyze large sets of qualitative data. This book is also available as Open Access on Cambridge Core.
There is a growing consensus in the social sciences on the virtues of research strategies that combine quantitative with qualitative tools of inference. Integrated Inferences develops a framework for using causal models and Bayesian updating for qualitative and mixed-methods research. By making, updating, and querying causal models, researchers are able to integrate information from different data sources while connecting theory and empirics in a far more systematic and transparent manner than standard qualitative and quantitative approaches allow. This book provides an introduction to fundamental principles of causal inference and Bayesian updating and shows how these tools can be used to implement and justify inferences using within-case (process tracing) evidence, correlational patterns across many cases, or a mix of the two. The authors also demonstrate how causal models can guide research design, informing choices about which cases, observations, and mixes of methods will be most useful for addressing any given question.
Big data and algorithmic decision-making have been touted as game-changing developments in management research, but they have their limitations. Qualitative approaches should not be cast aside in the age of digitalisation, since they facilitate understanding of quantitative data and the questioning of assumptions and conclusions that may otherwise lead to faulty implications being drawn, and - crucially - inaccurate strategies, decisions and actions. This handbook comprises three parts: Part I highlights many of the issues associated with 'unthinking digitalisation', particularly concerning the overreliance on algorithmic decision-making and the consequent need for qualitative research. Part II provides examples of the various qualitative methods that can be usefully employed in researching various digital phenomena and issues. Part III introduces a range of emergent issues concerning practice, knowing, datafication, technology design and implementation, data reliance and algorithms, digitalisation.
Case study research is a versatile approach that allows for different data sources to be combined, with its main purpose being theory development. This book goes a step further by combining different case study research designs, informed by the authors' extensive teaching and research experience. It provides an accessible introduction to case study research, familiarizes readers with different archetypical and sequenced designs, and describes these designs and their components using both real and fictional examples. It provides thought-provoking exercises, and in doing so, prepares the reader to design their own case study in a way that suits the research objective. Written for an academic audience, this book is useful for students, their supervisors and professors, and ultimately any researcher who intends to use, or is already using, the case study approach.
Social media has put mass communication in the hands of normal people on an unprecedented scale, and has also given social scientists the tools necessary to listen to the voices of everyday people around the world. This book gives social scientists the skills necessary to leverage that opportunity, and transform social media's vast stream of information into social science data. The book combines the big data techniques of computer science with social science methodology. Intended as a text for advanced undergraduates, graduate students, and researchers in the social sciences, this book provides a methodological pathway for scholars who want to make use of this new and evolving source of data. It provides a framework for building one's own data collection and analysis infrastructure, a toolkit of content analysis, geographic analysis, and network analysis, and meditations on the ethical implications of social media data.
The most important step in social science research is the first step – finding a topic. Unfortunately, little guidance on this crucial and difficult challenge is available. Methodological studies and courses tend to focus on theory testing rather than theory generation. This book aims to redress that imbalance. The first part of the book offers an overview of the book's central concerns. How do social scientists arrive at ideas for their work? What are the different ways in which a study can contribute to knowledge in a field? The second part of the book offers suggestions about how to think creatively, including general strategies for finding a topic and heuristics for discovery. The third part of the book shows how data exploration may assist in generating theories and hypotheses. The fourth part of the book offers suggestions about how to fashion disparate ideas into a theory.
Experiments are a central methodology in the social sciences. Scholars from every discipline regularly turn to experiments. Practitioners rely on experimental evidence in evaluating social programs, policies, and institutions. This book is about how to “think” about experiments. It argues that designing a good experiment is a slow moving process (given the host of considerations) which is counter to the current fast moving temptations available in the social sciences. The book includes discussion of the place of experiments in the social science process, the assumptions underlying different types of experiments, the validity of experiments, the application of different designs, how to arrive at experimental questions, the role of replications in experimental research, and the steps involved in designing and conducting “good” experiments. The goal is to ensure social science research remains driven by important substantive questions and fully exploits the potential of experiments in a thoughtful manner.
This book seeks to narrow two gaps: first, between the widespread use of case studies and their frequently 'loose' methodological moorings; and second, between the scholarly community advancing methodological frontiers in case study research and the users of case studies in development policy and practice. It draws on the contributors' collective experience at this nexus, but the underlying issues are more broadly relevant to case study researchers and practitioners in all fields. How does one prepare a rigorous case study? When can causal inferences reasonably be drawn from a single case? When and how can policy-makers reasonably presume that a demonstrably successful intervention in one context might generate similarly impressive outcomes elsewhere, or if massively 'scaled up'? No matter their different starting points – disciplinary base, epistemological orientation, sectoral specialization, or practical concerns – readers will find issues of significance for their own field, and others across the social sciences. This title is also available Open Access.
Good Science is an account of psychological research emphasizing the moral foundations of inquiry. This volume brings together existing disciplinary critiques of scientism, objectivism, and instrumentalism, and then discusses how these contribute to institutionalized privilege and to less morally responsive research practices. The author draws on historical, critical, feminist, and science studies traditions to provide an alternative account of psychological science and to highlight the irreducibly moral foundations of everyday scientific practice. This work outlines a theoretical framework for thinking about and practicing psychology in ways that center moral responsibility, collective commitment, and justice. The book then applies this framework, describing psychological research practices in terms of the their moral dilemmas. Also included are materials meant to aid in methods instruction and mentoring.
A comprehensive introduction and teaching resource for state-of-the-art Qualitative Comparative Analysis (QCA) using R software. This guide facilitates the efficient teaching, independent learning, and use of QCA with the best available software, reducing the time and effort required when encountering not just the logic of a new method, but also new software. With its applied and practical focus, the book offers a genuinely simple and intuitive resource for implementing the most complete protocol of QCA. To make the lives of students, teachers, researchers, and practitioners as easy as possible, the book includes learning goals, core points, empirical examples, and tips for good practices. The freely available online material provides a rich body of additional resources to aid users in their learning process. Beyond performing core analyses with the R package QCA, the book also facilitates a close integration with the R package SetMethods allowing for a host of additional protocols for building a more solid and well-rounded QCA.
Qualitative comparative methods – and specifically controlled qualitative comparisons – are central to the study of politics. They are not the only kind of comparison, though, that can help us better understand political processes and outcomes. Yet there are few guides for how to conduct non-controlled comparative research. This volume brings together chapters from more than a dozen leading methods scholars from across the discipline of political science, including positivist and interpretivist scholars, qualitative methodologists, mixed-methods researchers, ethnographers, historians, and statisticians. Their work revolutionizes qualitative research design by diversifying the repertoire of comparative methods available to students of politics, offering readers clear suggestions for what kinds of comparisons might be possible, why they are useful, and how to execute them. By systematically thinking through how we engage in qualitative comparisons and the kinds of insights those comparisons produce, these collected essays create new possibilities to advance what we know about politics.