Chaos Theory in the Social Sciences: Foundations and Applications L. Douglas Kiel, Euel W. Elliott Chaos Theory in the Social Sciences: Foundations and Applications offers the most recent thinking in applying the chaos paradigm to the social sciences. The book explores the methodological techniques--and their difficulties--for determining whether chaotic processes may in fact exist in a particular instance and examines implications of chaos theory when applied specifically to political science, economics, and sociology. The contributors to the book show that no single technique can be used to diagnose and describe all chaotic processes and identify the strengths and limitations of a variety of approaches. The essays in this volume consider the application of chaos theory to such diverse phenomena as public opinion, the behavior of states in the international arena, the development of rational economic expectations, and long waves. Contributors include Brian J. L. Berry, Thad Brown, Kenyon B. DeGreene, Dimitrios Dendrinos, Euel Elliott, David Harvey, L. Ted Jaditz, Douglas Kiel, Heja Kim, Michael McBurnett, Michael Reed, Diana Richards, J. Barkley Rosser, Jr., and Alvin M. Saperstein. L. Douglas Kiel and Euel W. Elliott are both Associate Professors of Government, Politics, and Political Economy, University of Texas at Dallas. |
Contents
Exploring Nonlinear Dynamics with a Spreadsheet A Graphical View of Chaos for Beginners | 19 |
Probing the Underlying Structure in Dynamical Systems An Introduction to Spectral Analysis | 31 |
Measuring Chaos Using the Lyapunov Exponent | 53 |
The Prediction Test for Nonlinear Determinism | 67 |
From Individuals to Groups The Aggregation of Votes and Chaotic Dynamics | 89 |
Chaos Theory and Political Science | 117 |
Nonlinear Politics | 119 |
The Prediction of Unpredictability Applications of the New Paradigm of Chaos in Dynamical Systems to the Old Problem of the Stability of a System... | 139 |
Chaos Theory and Rationality in Economics | 199 |
Long Waves 17901990 Intermittency Chaos and Control | 215 |
Cities as Spatial Chaotic Attractors | 237 |
Implications for Social Systems Management and Social Science | 271 |
FieldTheoretic Framework for the Interpretation of the Evolution Instability Structural Change and Management of Complex Systems | 273 |
Social Science as the Study of Complex Systems | 295 |
| 325 | |
Contributors | 347 |
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Common terms and phrases
aggregation Annual Rate bifurcation chaos researchers chaos theory chaotic behavior chaotic dynamics chaotic systems chapter coefficient complex configuration correlation dimension correlation integral defined Democratic dependence on initial deterministic chaos dimension dissipative social systems dissipative systems dynamical system economic entropy equilibrium error estimate evolution example exists figure fluctuations forecast frequencies given graph Hence individual preferences initial conditions instability interactions iterative Kondratiev limit cycle linear logistic function logistic map Lorenz Lyapunov exponent mathematical means measure method Mondale nations neighbor noise nonlinear dynamics nonlinear systems observed ontological order parameter oscillations outcomes paradigm pattern phase portrait phase space physical political possible prediction present Prigogine problem random Rate of Change rational expectations regime region RMSE scientists sensitive dependence sequence social choice function social sciences spectral analysis spectrum stability statistical stochastic strange attractor structure tion trajectories triangle underlying variables voters x₁ x₁(t
References to this book
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 | Models of the Family in Modern Societies: Ideals and Realities Catherine Hakim No preview available - 2003 |