How the NSF became an important yet controversial patron for the social sciences, influencing debates over their scientific status and social relevance. In the early Cold War years, the U.S. government established the National Science Foundation (NSF), a civilian agency that soon became widely known for its dedication to supporting first-rate science. The agency's 1950 enabling legislation made no mention of the social sciences, although it included a vague reference to "other sciences." Nevertheless, as Mark Solovey shows in this book, the NSF also soon became a major--albeit controversial--source of public funding for them.

The culmination of a lifetime spent in a variety of fields - sociology, anthropology, economics, psychology, and philosophy of science - How Does Social Science Work? takes an innovative, sometimes iconoclastic look at social scientists at work in many disciplines. It describes how they investigate and the kinds of truth they produce, illuminating the weaknesses and dangers inherent in their research.At once an analysis, a critique, and a synthesis, this major study begins by surveying philosophical approaches to hermeneutics, to examine the question of how social science ought to work. It illustrates many of its arguments with untraditional examples, such as the reception of the work of the political biographer Robert Caro to show the hermeneutical problems of ethnographers. The major part of the book surveys sociological, political, and psychological studies of social science to get a rounded picture of how social science works,Paul Diesling warns that "social science exists between two opposite kinds of degeneration, a value-free professionalism that lives only for publications that show off the latest techniques, and a deep social concern that uses science for propaganda." He argues for greater self-awareness and humility among social scientists, although he notes that "some social scientists . . . will angrily reject the thought that their personality affects their research in any way."This profound and sometimes witty book will appeal to students and practitioners in the social sciences who are ready to take a fresh look at their field. An extensive bibliography provides a wealth of references across an array of social science disciplines.

Robert K. Merton is unarguably one of the most influential sociologists of his time. A figure whose wide-ranging theoretical and methodological contributions have become fundamental to the field, Merton is best known for introducing such concepts and procedures as unanticipated consequences, self-fulfilling prophecies, focused group interviews, middle-range theory, opportunity structure, and analytic paradigms. This definitive compilation encompasses the breadth and brilliance of his works, from the earliest to the most recent. Merton's foundational writings on social structure and process, on the sociology of science and knowledge, and on the discipline and trajectory of sociology itself are all powerfully represented, as are his autobiographical insights in a fascinating coda. Anchored by Piotr Sztompka's contextualizing introduction, Merton's vast oeuvre emerges as a dynamic and profoundly coherent system of thought, a constant source of vitality and renewal for present and future sociology.

Offering pragmatic guidance for planning and conducting a meta-analytic review, this book is written in an engaging, nontechnical style that makes it ideal for graduate course use or self-study. The author shows how to identify questions that can be answered using meta-analysis, retrieve both published and unpublished studies, create a coding manual, use traditional and unique effect size indices, and write a meta-analytic review. An ongoing example illustrates meta-analytic techniques. In addition to the fundamentals, the book discusses more advanced topics, such as artifact correction, random- and mixed-effects models, structural equation representations, and multivariate procedures. User-friendly features include annotated equations; discussions of alternative approaches; and "Practical Matters" sections that give advice on topics not often discussed in other books, such as linking meta-analytic results with theory and the utility of meta-analysis software programs. ÿ

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.

Time series, or longitudinal, data are ubiquitous in the social sciences. Unfortunately, analysts often treat the time series properties of their data as a nuisance rather than a substantively meaningful dynamic process to be modeled and interpreted. Time Series Analysis for the Social Sciences provides accessible, up-to-date instruction and examples of the core methods in time series econometrics. Janet M. Box-Steffensmeier, John R. Freeman, Jon C. Pevehouse and Matthew P. Hitt cover a wide range of topics including ARIMA models, time series regression, unit-root diagnosis, vector autoregressive models, error-correction models, intervention models, fractional integration, ARCH models, structural breaks, and forecasting. This book is aimed at researchers and graduate students who have taken at least one course in multivariate regression. Examples are drawn from several areas of social science, including political behavior, elections, international conflict, criminology, and comparative political economy.