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Use Of Models Soc Science
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Book Synopsis Formal Modeling in Social Science by : Carol Mershon
Download or read book Formal Modeling in Social Science written by Carol Mershon and published by University of Michigan Press. This book was released on 2019-09-03 with total page 257 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Models as Mediators by : Mary S. Morgan
Download or read book Models as Mediators written by Mary S. Morgan and published by Cambridge University Press. This book was released on 1999-10-21 with total page 420 pages. Available in PDF, EPUB and Kindle. Book excerpt: Edited collection examining the ways in which models are used in modern science.
Book Synopsis An Introduction to Models in the Social Sciences by : Charles A. Lave
Download or read book An Introduction to Models in the Social Sciences written by Charles A. Lave and published by University Press of America. This book was released on 1993 with total page 436 pages. Available in PDF, EPUB and Kindle. Book excerpt: What is a model? How do you construct one? What are some common models in the social sciences? How can models be applied in new situations? What makes a model good? Focusing on answers to these and related questions, this multidisciplinary introduction to model building in the social sciences formulates interesting problems that involve students in creative model building and the process of invention. The book describes models of individual choice, exchange, adaptation, and diffusion. Throughout, student participation in analytical thinking is encouraged. Originally published in 1975 by HarperCollins Publishers.
Book Synopsis The Use of Models in the Social Sciences by : Lyndhurst Collins
Download or read book The Use of Models in the Social Sciences written by Lyndhurst Collins and published by Routledge. This book was released on 2013-11-05 with total page 264 pages. Available in PDF, EPUB and Kindle. Book excerpt: Tavistock Press was established as a co-operative venture between the Tavistock Institute and Routledge & Kegan Paul (RKP) in the 1950s to produce a series of major contributions across the social sciences. This volume is part of a 2001 reissue of a selection of those important works which have since gone out of print, or are difficult to locate. Published by Routledge, 112 volumes in total are being brought together under the name The International Behavioural and Social Sciences Library: Classics from the Tavistock Press. Reproduced here in facsimile, this volume was originally published in 1976 and is available individually. The collection is also available in a number of themed mini-sets of between 5 and 13 volumes, or as a complete collection.
Book Synopsis Modelling and Simulation in the Social Sciences from the Philosophy of Science Point of View by : R. Hegselmann
Download or read book Modelling and Simulation in the Social Sciences from the Philosophy of Science Point of View written by R. Hegselmann and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 332 pages. Available in PDF, EPUB and Kindle. Book excerpt: Model building in the social sciences can increasingly rely on well elaborated formal theories. At the same time inexpensive large computational capacities are now available. Both make computer-based model building and simulation possible in social science, whose central aim is in particular an understanding of social dynamics. Such social dynamics refer to public opinion formation, partner choice, strategy decisions in social dilemma situations and much more. In the context of such modelling approaches, novel problems in philosophy of science arise which must be analysed - the main aim of this book. Interest in social simulation has recently been growing rapidly world- wide, mainly as a result of the increasing availability of powerful personal computers. The field has also been greatly influenced by developments in cellular automata theory (from mathematics) and in distributed artificial intelligence which provided tools readily applicable to social simulation. This book presents a number of modelling and simulation approaches and their relations to problems in philosophy of science. It addresses sociologists and other social scientists interested in formal modelling, mathematical sociology, and computer simulation as well as computer scientists interested in social science applications, and philosophers of social science.
Book Synopsis How to Build Social Science Theories by : Pamela J. Shoemaker
Download or read book How to Build Social Science Theories written by Pamela J. Shoemaker and published by SAGE Publications. This book was released on 2003-12-10 with total page 241 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Statistical Modeling and Inference for Social Science by : Sean Gailmard
Download or read book Statistical Modeling and Inference for Social Science written by Sean Gailmard and published by Cambridge University Press. This book was released on 2014-06-09 with total page 393 pages. Available in PDF, EPUB and Kindle. Book excerpt: Written specifically for graduate students and practitioners beginning social science research, Statistical Modeling and Inference for Social Science covers the essential statistical tools, models and theories that make up the social scientist's toolkit. Assuming no prior knowledge of statistics, this textbook introduces students to probability theory, statistical inference and statistical modeling, and emphasizes the connection between statistical procedures and social science theory. Sean Gailmard develops core statistical theory as a set of tools to model and assess relationships between variables - the primary aim of social scientists - and demonstrates the ways in which social scientists express and test substantive theoretical arguments in various models. Chapter exercises guide students in applying concepts to data, extending their grasp of core theoretical concepts. Students will also gain the ability to create, read and critique statistical applications in their fields of interest.
Book Synopsis Formal Modeling in Social Science by : Carol Mershon
Download or read book Formal Modeling in Social Science written by Carol Mershon and published by University of Michigan Press. This book was released on 2019-09-03 with total page 257 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Social Science Research by : Anol Bhattacherjee
Download or read book Social Science Research written by Anol Bhattacherjee and published by CreateSpace. This book was released on 2012-04-01 with total page 156 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Hypothesis Testing and Model Selection in the Social Sciences by : David L. Weakliem
Download or read book Hypothesis Testing and Model Selection in the Social Sciences written by David L. Weakliem and published by Guilford Publications. This book was released on 2016-04-25 with total page 217 pages. Available in PDF, EPUB and Kindle. Book excerpt: Examining the major approaches to hypothesis testing and model selection, this book blends statistical theory with recommendations for practice, illustrated with real-world social science examples. It systematically compares classical (frequentist) and Bayesian approaches, showing how they are applied, exploring ways to reconcile the differences between them, and evaluating key controversies and criticisms. The book also addresses the role of hypothesis testing in the evaluation of theories, the relationship between hypothesis tests and confidence intervals, and the role of prior knowledge in Bayesian estimation and Bayesian hypothesis testing. Two easily calculated alternatives to standard hypothesis tests are discussed in depth: the Akaike information criterion (AIC) and Bayesian information criterion (BIC). The companion website ([ital]www.guilford.com/weakliem-materials[/ital]) supplies data and syntax files for the book's examples.
Book Synopsis Computational Social Science by : R. Michael Alvarez
Download or read book Computational Social Science written by R. Michael Alvarez and published by Cambridge University Press. This book was released on 2016-03-07 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Quantitative research in social science research is changing rapidly. Researchers have vast and complex arrays of data with which to work: we have incredible tools to sift through the data and recognize patterns in that data; there are now many sophisticated models that we can use to make sense of those patterns; and we have extremely powerful computational systems that help us accomplish these tasks quickly. This book focuses on some of the extraordinary work being conducted in computational social science - in academia, government, and the private sector - while highlighting current trends, challenges, and new directions. Thus, Computational Social Science showcases the innovative methodological tools being developed and applied by leading researchers in this new field. The book shows how academics and the private sector are using many of these tools to solve problems in social science and public policy.
Book Synopsis Pathways Between Social Science and Computational Social Science by : Tamás Rudas
Download or read book Pathways Between Social Science and Computational Social Science written by Tamás Rudas and published by Springer Nature. This book was released on 2021-01-22 with total page 284 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume shows that the emergence of computational social science (CSS) is an endogenous response to problems from within the social sciences and not exogeneous. The three parts of the volume address various pathways along which CSS has been developing from and interacting with existing research frameworks. The first part exemplifies how new theoretical models and approaches on which CSS research is based arise from theories of social science. The second part is about methodological advances facilitated by CSS-related techniques. The third part illustrates the contribution of CSS to traditional social science topics, further attesting to the embedded nature of CSS. The expected readership of the volume includes researchers with a traditional social science background who wish to approach CSS, experts in CSS looking for substantive links to more traditional social science theories, methods and topics, and finally, students working in both fields.
Book Synopsis Models and Modeling in the Sciences by : Stephen M. Downes
Download or read book Models and Modeling in the Sciences written by Stephen M. Downes and published by Routledge. This book was released on 2020-07-09 with total page 115 pages. Available in PDF, EPUB and Kindle. Book excerpt: Biologists, climate scientists, and economists all rely on models to move their work forward. In this book, Stephen M. Downes explores the use of models in these and other fields to introduce readers to the various philosophical issues that arise in scientific modeling. Readers learn that paying attention to models plays a crucial role in appraising scientific work. This book first presents a wide range of models from a number of different scientific disciplines. After assembling some illustrative examples, Downes demonstrates how models shed light on many perennial issues in philosophy of science and in philosophy in general. Reviewing the range of views on how models represent their targets introduces readers to the key issues in debates on representation, not only in science but in the arts as well. Also, standard epistemological questions are cast in new and interesting ways when readers confront the question, "What makes for a good (or bad) model?" All examples from the sciences and positions in the philosophy of science are presented in an accessible manner. The book is suitable for undergraduates with minimal experience in philosophy and an introductory undergraduate experience in science. Key features: The book serves as a highly accessible philosophical introduction to models and modeling in the sciences, presenting all philosophical and scientific issues in a nontechnical manner. Students and other readers learn to practice philosophy of science by starting with clear examples taken directly from the sciences. While not comprehensive, this book introduces the reader to a wide range of views on key issues in the philosophy of science.
Book Synopsis The Logic of Social Science by : James Mahoney
Download or read book The Logic of Social Science written by James Mahoney and published by Princeton University Press. This book was released on 2021-08-17 with total page 416 pages. Available in PDF, EPUB and Kindle. Book excerpt: "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"--
Book Synopsis Causal Models in the Social Sciences by : Jr. Blalock
Download or read book Causal Models in the Social Sciences written by Jr. Blalock and published by Routledge. This book was released on 2017-07-28 with total page 227 pages. Available in PDF, EPUB and Kindle. Book excerpt: Causal models are formal theories stating the relationships between precisely defined variables, and have become an indispensable tool of the social scientist. This collection of articles is a course book on the causal modeling approach to theory construction and data analysis. H. M. Blalock, Jr. summarizes the then-current developments in causal model utilization in sociology, political science, economics, and other disciplines. This book provides a comprehensive multidisciplinary picture of the work on causal models. It seeks to address the problem of measurement in the social sciences and to link theory and research through the development of causal models.Organized into five sections (Simple Recursive Models, Path Analysis, Simultaneous Equations Techniques, The Causal Approach to Measurement Error, and Other Complications), this volume contains twenty-seven articles (eight of which were specially commissioned). Each section begins with an introduction explaining the concepts to be covered in the section and links them to the larger subject. It provides a general overview of the theory and application of causal modeling.Blalock argues for the development of theoretical models that can be operationalized and provide verifiable predictions. Many of the discussions of this subject that occur in other literature are too technical for most social scientists and other scholars who lack a strong background in mathematics. This book attempts to integrate a few of the less technical papers written by econometricians such as Koopmans, Wold, Strotz, and Fisher with discussions of causal approaches in the social and biological sciences. This classic text by Blalock is a valuable source of material for those interested in the issue of measurement in the social sciences and the construction of mathematical models.
Book Synopsis The Palgrave Handbook of Quantum Models in Social Science by : Emmanuel Haven
Download or read book The Palgrave Handbook of Quantum Models in Social Science written by Emmanuel Haven and published by Springer. This book was released on 2017-02-06 with total page 377 pages. Available in PDF, EPUB and Kindle. Book excerpt: It is not intuitive to accept that there exists a link between quantum physical systems and cognitive systems. However, recent research has shown that cognitive systems and collective (social) systems, including biology, exhibit uncertainty which can be successfully modelled with quantum probability. The use of such probability allows for the modelling of situations which typically violate the laws of classical probability. The Palgrave Handbook of Quantum Models in Social Science is is a unique volume that brings together contributions from leading experts on key topics in this new and emerging field. Completely self-contained, it begins with an introductory section which gathers all the fundamental notions required to be able to understand later chapters. The handbook then moves on to address some of the latest research and applications for quantum methods in social science disciplines, including economics, politics and psychology. It begins with the issue of how the quantum mechanical framework can be applied to economics. Chapters devoted to this topic range from how Fisher information can be argued to play a role in economics, to the foundations and application of quantum game theory. The handbook then progresses in considering how belief states can be updated with the theory of quantum measurements (and also with more general methods). The practical use of the Hilbert space (and Fock space) in decision theory is then introduced, and open quantum systems are also considered. The handbook also treats a model of neural oscillators that reproduces some of the features of quantum cognition. Other contributions delve into causal reasoning using quantum Bayes nets and the role of quantum probability in modelling so called affective evaluation. The handbook is rounded off with two chapters which discuss the grand challenges which lie ahead of us. How can the quantum formalism be justified in social science and is the traditional quantum formalism too restrictive? Finally, a question is posed: whether there is a necessary role for quantum mathematical models to go beyond physics. This book will bring the latest and most cutting edge research on quantum theory to social science disciplines. Students and researchers across the discipline, as well as those in the fields of physics and mathematics will welcome this important addition to the literature.
Book Synopsis Introduction to Computational Social Science by : Claudio Cioffi-Revilla
Download or read book Introduction to Computational Social Science written by Claudio Cioffi-Revilla and published by Springer. This book was released on 2017-06-29 with total page 636 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook provides a comprehensive and reader-friendly introduction to the field of computational social science (CSS). Presenting a unified treatment, the text examines in detail the four key methodological approaches of automated social information extraction, social network analysis, social complexity theory, and social simulation modeling. This updated new edition has been enhanced with numerous review questions and exercises to test what has been learned, deepen understanding through problem-solving, and to practice writing code to implement ideas. Topics and features: contains more than a thousand questions and exercises, together with a list of acronyms and a glossary; examines the similarities and differences between computers and social systems; presents a focus on automated information extraction; discusses the measurement, scientific laws, and generative theories of social complexity in CSS; reviews the methodology of social simulations, covering both variable- and object-oriented models.
