Political complexity: nonlinear models of politics
Gespeichert in:
| Format: | Elektronisch E-Book |
|---|---|
| Sprache: | English |
| Veröffentlicht: |
Ann Arbor
University of Michigan Press
c2000
|
| Schlagworte: | |
| Online-Zugang: | FAW01 FAW02 Volltext |
| Beschreibung: | Master and use copy. Digital master created according to Benchmark for Faithful Digital Reproductions of Monographs and Serials, Version 1. Digital Library Federation, December 2002 Includes bibliographical references and index pt. 1. Spatial nonlinearity : optimization and search -- pt. 2. Temporal nonlinearity : complexity over time -- pt. 3. Functional nonlinearity : networks and patterns -- pt. 4. Conclusion This collection illustrates how nonlinear methods can provide new insight into existing political questions. Politics is often characterized by unexpected consequences, sensitivity to small changes, non-equilibrium dynamics, the emergence of patterns, and sudden changes in outcomes. These are all attributes of nonlinear processes. Bringing together a variety of recent nonlinear modeling approaches, Political Complexity explores what happens when political actors operate in a dynamic and complex social environment. The contributions to this collection are organized in terms of three branches within non-linear theory: spatial nonlinearity, temporal nonlinearity, and functional nonlinearity. The chapters advance beyond analogy towards developing rigorous nonlinear models capable of empirical verification. Contributions to this volume cover the areas of landscape theory, computational modeling, time series analysis, cross-sectional analysis, dynamic game theory, duration models, neural networks, and hidden Markov models. They address such questions as: Is international cooperation necessary for effective economic sanctions? Is it possible to predict alliance configurations in the international system? Is a bureaucratic agency harder to remove as time goes on? Is it possible to predict which international crises will result in war and which will avoid conflict? Is decentralization in a federal system always beneficial? The contributors are David Bearce, Scott Bennett, Chris Brooks, Daniel Carpenter, Melvin Hinich, Ken Kollman, Susanne Lohmann, Walter Mebane, John Miller, Robert E. Molyneaux, Scott Page, Philip Schrodt, and Langche Zeng. This book will be of interest to a broad group of political scientists, ranging from those who employ nonlinear methods to those curious to see what it is about. Scholars in other social science disciplines will find the new methodologies insightful for their own substantive work. Diana Richards is Associate Professor of Political Science, University of Minnesota |
| Beschreibung: | 1 Online-Ressource (vi, 353 p.) |
| ISBN: | 0472026992 9780472026999 |
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| 500 | |a Includes bibliographical references and index | ||
| 500 | |a pt. 1. Spatial nonlinearity : optimization and search -- pt. 2. Temporal nonlinearity : complexity over time -- pt. 3. Functional nonlinearity : networks and patterns -- pt. 4. Conclusion | ||
| 500 | |a This collection illustrates how nonlinear methods can provide new insight into existing political questions. Politics is often characterized by unexpected consequences, sensitivity to small changes, non-equilibrium dynamics, the emergence of patterns, and sudden changes in outcomes. These are all attributes of nonlinear processes. Bringing together a variety of recent nonlinear modeling approaches, Political Complexity explores what happens when political actors operate in a dynamic and complex social environment. The contributions to this collection are organized in terms of three branches within non-linear theory: spatial nonlinearity, temporal nonlinearity, and functional nonlinearity. The chapters advance beyond analogy towards developing rigorous nonlinear models capable of empirical verification. | ||
| 500 | |a Contributions to this volume cover the areas of landscape theory, computational modeling, time series analysis, cross-sectional analysis, dynamic game theory, duration models, neural networks, and hidden Markov models. They address such questions as: Is international cooperation necessary for effective economic sanctions? Is it possible to predict alliance configurations in the international system? Is a bureaucratic agency harder to remove as time goes on? Is it possible to predict which international crises will result in war and which will avoid conflict? Is decentralization in a federal system always beneficial? The contributors are David Bearce, Scott Bennett, Chris Brooks, Daniel Carpenter, Melvin Hinich, Ken Kollman, Susanne Lohmann, Walter Mebane, John Miller, Robert E. Molyneaux, Scott Page, Philip Schrodt, and Langche Zeng. | ||
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Datensatz im Suchindex
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| dewey-ones | 320 - Political science (Politics and government) |
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| spelling | Political complexity nonlinear models of politics edited by Diana Richards Ann Arbor University of Michigan Press c2000 1 Online-Ressource (vi, 353 p.) txt rdacontent c rdamedia cr rdacarrier Master and use copy. Digital master created according to Benchmark for Faithful Digital Reproductions of Monographs and Serials, Version 1. Digital Library Federation, December 2002 Includes bibliographical references and index pt. 1. Spatial nonlinearity : optimization and search -- pt. 2. Temporal nonlinearity : complexity over time -- pt. 3. Functional nonlinearity : networks and patterns -- pt. 4. Conclusion This collection illustrates how nonlinear methods can provide new insight into existing political questions. Politics is often characterized by unexpected consequences, sensitivity to small changes, non-equilibrium dynamics, the emergence of patterns, and sudden changes in outcomes. These are all attributes of nonlinear processes. Bringing together a variety of recent nonlinear modeling approaches, Political Complexity explores what happens when political actors operate in a dynamic and complex social environment. The contributions to this collection are organized in terms of three branches within non-linear theory: spatial nonlinearity, temporal nonlinearity, and functional nonlinearity. The chapters advance beyond analogy towards developing rigorous nonlinear models capable of empirical verification. Contributions to this volume cover the areas of landscape theory, computational modeling, time series analysis, cross-sectional analysis, dynamic game theory, duration models, neural networks, and hidden Markov models. They address such questions as: Is international cooperation necessary for effective economic sanctions? Is it possible to predict alliance configurations in the international system? Is a bureaucratic agency harder to remove as time goes on? Is it possible to predict which international crises will result in war and which will avoid conflict? Is decentralization in a federal system always beneficial? The contributors are David Bearce, Scott Bennett, Chris Brooks, Daniel Carpenter, Melvin Hinich, Ken Kollman, Susanne Lohmann, Walter Mebane, John Miller, Robert E. Molyneaux, Scott Page, Philip Schrodt, and Langche Zeng. This book will be of interest to a broad group of political scientists, ranging from those who employ nonlinear methods to those curious to see what it is about. Scholars in other social science disciplines will find the new methodologies insightful for their own substantive work. Diana Richards is Associate Professor of Political Science, University of Minnesota PHILOSOPHY / Political bisacsh Nonlinear theories fast Political science / Mathematical models fast Mathematisches Modell Politische Wissenschaft Political science Mathematical models Nonlinear theories Politische Wissenschaft (DE-588)4076229-4 gnd rswk-swf Mathematisches Modell (DE-588)4114528-8 gnd rswk-swf 1\p (DE-588)4143413-4 Aufsatzsammlung gnd-content Politische Wissenschaft (DE-588)4076229-4 s Mathematisches Modell (DE-588)4114528-8 s 2\p DE-604 Doyle, Diana Richards Sonstige oth Erscheint auch als Druck-Ausgabe, Hardcover 0-472-10964-2 Erscheint auch als Druck-Ausgabe, Hardcover 978-0-472-10964-7 http://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&db=nlabk&AN=328948 Aggregator Volltext 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk 2\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Political complexity nonlinear models of politics PHILOSOPHY / Political bisacsh Nonlinear theories fast Political science / Mathematical models fast Mathematisches Modell Politische Wissenschaft Political science Mathematical models Nonlinear theories Politische Wissenschaft (DE-588)4076229-4 gnd Mathematisches Modell (DE-588)4114528-8 gnd |
| subject_GND | (DE-588)4076229-4 (DE-588)4114528-8 (DE-588)4143413-4 |
| title | Political complexity nonlinear models of politics |
| title_auth | Political complexity nonlinear models of politics |
| title_exact_search | Political complexity nonlinear models of politics |
| title_full | Political complexity nonlinear models of politics edited by Diana Richards |
| title_fullStr | Political complexity nonlinear models of politics edited by Diana Richards |
| title_full_unstemmed | Political complexity nonlinear models of politics edited by Diana Richards |
| title_short | Political complexity |
| title_sort | political complexity nonlinear models of politics |
| title_sub | nonlinear models of politics |
| topic | PHILOSOPHY / Political bisacsh Nonlinear theories fast Political science / Mathematical models fast Mathematisches Modell Politische Wissenschaft Political science Mathematical models Nonlinear theories Politische Wissenschaft (DE-588)4076229-4 gnd Mathematisches Modell (DE-588)4114528-8 gnd |
| topic_facet | PHILOSOPHY / Political Nonlinear theories Political science / Mathematical models Mathematisches Modell Politische Wissenschaft Political science Mathematical models Aufsatzsammlung |
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