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Model Steps

Douglas Crawford-Brown

The Modeling of Nature: Philosophy of Science and Philosophy of Nature in Synthesis. William A. Wallace. 450 pp. The Catholic University of America Press, 1996. $49.95 cloth, $34.95 paper.

The goal of this book is to revive an Aristotelian view of science and knowledge. William Wallace brings the methods of reasoning and much of the metaphysics championed by Aristotle and by many of the medieval scholars to the task of guiding modern science. He hopes to explain how some classes of scientific knowledge are not only probably true, meaning the evidence makes them more or less likely, but necessarily true. The key to the book is the claim that scientific inquiry can be guided to perfect (necessary) knowledge by being rooted in a series of models constructed around "natures" present in different aspects of the world. These natures are inorganic (protomatter), plants, animals and humans.

As in Aristotle's writings, the author argues that the causes of events in the world can be found in objects that reveal their natures and express the potential inherent in those natures. If those natures are understood, the explanations for events in which they participate follow almost deductively, or at least tautologically. Understanding why science works, if indeed it does work, requires understanding how science has managed to reveal and build theories on some of the basic natures of matter. This theme is explored through a series of historical case studies in optics, astronomy, kinematics, biology, dynamics, chemistry and biochemistry, each of which shows how a given approach to modeling nature based on "natures" first clarified, and then helped resolve, disputes in science.

This reviewer found the book interesting, primarily because of a personal interest in views of science during the Middle Ages. There is likely to be less interest for most readers from science or analytical philosophy, particularly those hoping to find a discussion of the links between philosophical analysis and modern scientific models. The reason for this is twofold, although the author does disarm some of the criticism by confronting these complaints head-on in the beginning of the book. First, the book really is not about scientific modeling in the sense of the computational and predictive models, which form the basis of most scientific activity. Instead, it is concerned with the deepest, metaphysical, levels of the conceptual models that are used to guide more specific theories on which predictive models ultimately are built. Readers searching for insights into how modern predictive models are constructed, tested, validated and verified will find little of interest in the book.

Second, the author's claim that the insights his approach gives do not depend on buying into Aristotelian theories of nature, but rather only into general Aristotelian modes of reasoning from experience, is not met satisfactorily. Most practicing scientists will find the conception of science and philosophy of science much too a priori, building quite reasonably from the four natures described in the early chapters, but with little justification to adopt those natures as givens in the models provided.

Still, the goal of the book is good, spurring philosophers of science to look more closely at the metaphysics of specific theories rather than solely at issues of method. It reminds us that epistemology and ontology are not so distant and separable as they seem at times in modern philosophy. There are interesting discussions of cognitive and emotive aspects of knowledge, and of typologies of models and concepts. The historical case studies, although too brief, do provide some good examples of the application of an Aristotelian method of reasoning that deserves greater consideration in education. For those of us interested in how far premodern ideas can be pushed into modern science, the book can be recommended. It may be contrasted with a book such as Philip Kitcher's Advancement of Science (Oxford University Press, 1993), which includes a description of the more traditional debates in the philosophy of sciences and takes a realist's—but still probabilistic—approach to judging scientific models.—Douglas J. Crawford-Brown, Institute for Environmental Studies, University of North Carolina at Chapel Hill

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