Kenneth D. Bailey – författare

Social Entropy Theory illuminates the fundamental problems of societal analysis with a nonequilibrium approach, a new frame of reference built upon contemporary macrological principles, including general systems theory and information theory. Social entropy theory, using Shannon's H and the entropy concept, avoids the common (and often artificial) separation of theory and method in sociology. The hallmark of the volume is integration, as seen in the author's interdisciplinary discussions of equilibrium, entropy, and homeostasis. Unique features of the book are the introduction of the three-level model of social measurement, the theory of allocation, the concepts of global-mutable-immutable, discussion of order and power, and a large set of testable hypotheses.

This book provides current information about the many recent contributions of social systems theory. While some sociologists feel that the systems age ended with functionalism, in reality a number of recent developments have occurred within the field. The author makes these developments accessible to sociologists and other non-systems scholars, and begins a synthesis of the burgeoning systems field and mainstream sociological theory. The analysis shows not only that important points of rapprochement exist between systems theory and sociological theory, but also that systems theory has in some cases anticipated developments needed in mainstream theory.

How do we group different subjects on a variety of variables? Should we use a classification procedure in which only the concepts are classified (typology), one in which only empirical entities are classified (taxonomy), or some combination of both? In this clearly written book, Bailey addresses these questions and shows how classification methods can be used to improve research. Beginning with an exploration of the advantages and disadvantages of classification procedures including those typologies that can be constructed without the use of a computer, the book covers such topics as clustering procedures (including agglomerative and divisive methods), the relationship among various classification techniques (including the relationship of monothetic, qualitative typologies to polythetic, quantitative taxonomies), a comparison of clustering methods and how these methods compare with related statistical techniques such as factor analysis, multidimensional scaling and systems analysis, and lists classification resources. This volume also discusses software packages for use in clustering techniques.