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Click ′Additional Materials′ to read the foreword by Jerald Hage As straightforward as its title, How to Build Social Science Theories sidesteps the well-traveled road of theoretical examination by demonstrating how new theories originate and how they are elaborated. Essential reading for students of social science research, this book traces theories from their most rudimentary building blocks (terminology and definitions) through multivariable theoretical statements, models, the role of creativity in theory building, and how theories are used and evaluated. Authors Pamela J. Shoemaker, James William Tankard, Jr., and Dominic L. Lasorsa intend to improve research in many areas of the social sciences by making research more theory-based and theory-oriented. The book begins with a discussion of concepts and their theoretical and operational definitions. It then proceeds to theoretical statements, including hypotheses, assumptions, and propositions. Theoretical statements need theoretical linkages and operational linkages; this discussion begins with bivariate relationships, as well as three-variable, four-variable, and further multivariate relationships. The authors also devote chapters to the creative component of theory-building and how to evaluate theories. How to Build Social Science Theories is a sophisticated yet readable analysis presented by internationally known experts in social science methodology. It is designed primarily as a core text for graduate and advanced undergraduate courses in communication theory. It will also be a perfect addition to any course dealing with theory and research methodology across the social sciences. Additionally, professional researchers will find it an indispensable guide to the genesis, dissemination, and evaluation of social science theories.
New approach demonstrating how social science can be successful, focusing on context, values, and power.
This book is designed to introduce doctoral and graduate students to the process of conducting scientific research in the social sciences, business, education, public health, and related disciplines. It is a one-stop, comprehensive, and compact source for foundational concepts in behavioral research, and can serve as a stand-alone text or as a supplement to research readings in any doctoral seminar or research methods class. This book is currently used as a research text at universities on six continents and will shortly be available in nine different languages.
The use of case studies to build and test theories in political science and the other social sciences has increased in recent years. Many scholars have argued that the social sciences rely too heavily on quantitative research and formal models and have attempted to develop and refine rigorous methods for using case studies. This text presents a comprehensive analysis of research methods using case studies and examines the place of case studies in social science methodology. It argues that case studies, statistical methods, and formal models are complementary rather than competitive. The book explains how to design case study research that will produce results useful to policymakers and emphasizes the importance of developing policy-relevant theories. It offers three major contributions to case study methodology: an emphasis on the importance of within-case analysis, a detailed discussion of process tracing, and development of the concept of typological theories. Case Studies and Theory Development in the Social Sciences will be particularly useful to graduate students and scholars in social science methodology and the philosophy of science, as well as to those designing new research projects, and will contribute greatly to the broader debate about scientific methods.
It seems like most of what we read about the academic social sciences in the mainstream media is negative. The field is facing mounting criticism, as canonical studies fail to replicate, questionable research practices abound, and researcher social and political biases come under fire. In response to these criticisms, Matt Grossmann, in How Social Science Got Better, provides a robust defense of the current state of the social sciences. Applying insights from the philosophy, history, and sociology of science and providing new data on research trends and scholarly views, he argues that, far from crisis, social science is undergoing an unparalleled renaissance of ever-broader understanding and application. According to Grossmann, social science research today has never been more relevant, rigorous, or self-reflective because scholars have a much better idea of their blind spots and biases. He highlights how scholars now closely analyze the impact of racial, gender, geographic, methodological, political, and ideological differences on research questions; how the incentives of academia influence our research practices; and how universal human desires to avoid uncomfortable truths and easily solve problems affect our conclusions. Though misaligned incentive structures of course remain, a messy, collective deliberation across the research community has shifted us into an unprecedented age of theoretical diversity, open and connected data, and public scholarship. Grossmann's wide-ranging account of current trends will necessarily force the academy's many critics to rethink their lazy critiques and instead acknowledge the path-breaking advances occurring in the social sciences today.
This innovative text demonstrates how social science theory and research can be applied to successful collaborative work with community groups. The 27 instructive case studies, framed by two introductory chapters and a concluding chapter, draw out the principles and perspectives underlying the case materials. Each case also concludes with extensive editorial commentary.
The Industrial Revolution offered promises of material abundance. In nineteenth century Britain, a series of major cooperative thinkers seized on these possibilities. In effect, they turned the mainstream economics of scarcity on its head and together shaped a humane social science. This book moves toward a reconstruction of nineteenth century British cooperative thought. The analysis is rich in insights still relevant to the present--insights concerning employment relations, persistent inequality, and low levels of human development.
A formal model in the social sciences builds explanations when it structures the reasoning underlying a theoretical argument, opens venues for controlled experimentation, and can lead to hypotheses. Yet more importantly, models evaluate theory, build theory, and enhance conjectures. Formal Modeling in Social Science addresses the varied helpful roles of formal models and goes further to take up more fundamental considerations of epistemology and methodology. The authors integrate the exposition of the epistemology and the methodology of modeling and argue that these two reinforce each other. They illustrate the process of designing an original model suited to the puzzle at hand, using multiple methods in diverse substantive areas of inquiry. The authors also emphasize the crucial, though underappreciated, role of a narrative in the progression from theory to model. Transparency of assumptions and steps in a model means that any analyst will reach equivalent predictions whenever she replicates the argument. Hence, models enable theoretical replication, essential in the accumulation of knowledge. Formal Modeling in Social Science speaks to scholars in different career stages and disciplines and with varying expertise in modeling.
This book gathers an expert group of social scientists to showcase emerging forms of analysis and evaluation for public policy analysis. Each chapter highlights a different method or approach, putting it in context and highlighting its key features before illustrating its application and potential value to policy makers. Aimed at upper-level undergraduates in public policy and social work, it also has much to offer policy makers and practitioners themselves.
"Mahoney's starting point is the problem of essentialism in social science. Essentialism--the belief that the members of a category possess hidden properties ("essences") that make them members of the category and that endow them with a certain nature--is appropriate for scientific categories ("atoms", for instance) but not for human ones ("revolutions," for instance). Despite this, much social science research takes place from within an essentialist orientation; those who reject this assumption goes so far in the other direction as to reject the idea of an external reality, independent of human beings, altogether. Mahoney proposes an alternative approach that aspires to bridge this enduring rift in the social sciences between those who take a scientific approach and assume that social science categories correspond to external reality (and thus believe that the methods used in the natural sciences are generally appropriate for the social sciences) and those who take a constructivist approach and believe that because the categories used to understand the social world are humanly-constructed, they cannot possibly follow the science of the natural world. As the name suggests, scientific constructivism brings in aspects of both views and attempts to unite them. Drawing from cognitive science, it focuses on using the rational parts of our brain machinery to overcome the limitations and deeply seated biases (such as essentialism) of our evolved minds. Specifically, Mahoney puts forth a "set-theoretic analysis" that focuses on "sets" of categories as they exist in the mind that are also subject to the mathematical logic of set-theory. He spends the first four chapters of the book establishing the foundations and methods for set-theoretic analysis, the next four chapters looking and how this analysis fits with the existing tools of social science, and the final four chapters focusing on how this approach can be used to study and understand cases"--