Mathematics of Collective ActionTransaction Publishers - Počet stran: 191 "Philosophers, social scientists, and laymen have used two perspectives in analyzing social action. One sees man's action as the result of causal forces, and the other sees action as purposive and goal directed. Mathematical treatment of social action has shown this same dichotomy. Some models of behavior describe a causal process, in which there is no place for intention or purpose. Most stochastic models of behavior, whether individual or group, are like this. Another body of work, however, employs purpose, anticipation of some future state, and action designed to maximize the proximity to some goal. Classical microeconomic theory, statistical decision theory, and game theory exemplify this direction. This book examines these two directions of work, and makes original contributions to the second. An introductory chapter outlines these two bodies of work, and casts them in a common frame, to display their similarities and differences. Chapter 2 reviews at length recent work in stochastic processes that makes up the first body of work, which sees social action as the resultant of causal forces. The remaining chapters develop a mathematical framework for the study of systems of social action using a purposive theoretical base. These chapters are designed particularly to contribute to the study of collective decisions, a form of social action that has proved particularly challenging to theoretical analysis. First published in 1973, this became a significant work both in problem solving and in the future career of the author. It is of continuing importance to researchers and students interested in statistical analysis."--Provided by publisher. |
Obsah
Preface | liii |
Concepts of Rational Action | 32 |
Collective Actions | 61 |
Further Concepts and Applications | 90 |
Examples of applicationsThe problem of data | 128 |
The Dynamic System and Other Elaborations | 131 |
the probabilistic decision ruleSequential introduction | 154 |
References | 161 |
Computer Program and Output | 167 |
| 187 | |
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A₁ analysis assumed assumption B₁ behaviour Bernoulli trials best reply calculated causal Chapter Coleman collective action collective decisions committee concept of rationality conditional probabilities consequences constitutional control continuous-time continuous-time Markov process CONTROL BY ACTOR control of events control over event demand dependent described distribution equal equation equilibrium estimate example exchange expected realization expected utility expected value external favour final control FINAL DIRECTED CONTROL fraction game theory given increment independent individual interest in event interest matrix INTEREST OF ACTOR issue legislator legislature linear marginal utility Markov chain Markov process MAT PRINT mathematical Mathematical Sociology maximization mixed strategy parameters Poisson process positive outcome prisoner's dilemma probabilistic decision rule proportional allocation pure conflict purposive action purposive theories realization of interests representing social Sociological statistical structure Table theory tion transition probabilities transition rates utility differences v₁ variables X₁ x₁₁
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Strana xiv - To develop statistical methods that quantify such causes his general approach is: "(1) to begin with the idea of a process, (2) to attempt to lay out a mathematical model that mirrors this process, and then (3) given particular kinds of data, to transform the mathematical model into a statistical model for estimating parameters of the process
