Coherent Unpredictability
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Abstract
[Coherent Systems A.4.A.3.] Social science may be the closest area, if not coherent mathematics.
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Prigogine's theory of dissipative structures provides a general account of entropy-driven self-organized transitions through hierarchies of structures separated by discontinuities. The theory encompasses a wide range of evolving systems throughout nature and culture. Possibilities for operationalizing a new collective rationality spanning physics and psychology emerge from Prigogine's emphases on two distinct senses of probability, on the concept of the sufficient statistic, and on the role and limitations of the Poisson distribution in formulating a "nonlinear master equation." Unnoted by Prigogine are correspondences of all three of these issues in the mathematical foundations of statistics and measurement established in the works of Ronald Fisher and his student, Georg Rasch. The three areas of correspondence inform models enabling specifically metrological approaches to quality-assured quantification across the sciences. Prigogine's sense of "deterministic chaos" is re-expressed in measurement terms as stochastic invariance and the need for "a supplementary parameter" augmenting the Poisson distribution is related to a rating scale model of measurement. Considering these connections, this paper proposes that what Prigogine anticipates as a "new intelligibility" and a new science of "collective rationality" could be pragmatically operationalized in a new metrological infrastructure, one made coherent by the generality of entropydriven nonequilibrium processes.
This paper argues for the development of a metaphysics of indeterminism to complement the deterministic metaphysics of current science. Deterministic ideas are analysed to show the underlying assumptions and alternative assumptions are then proposed which allow an indeterministic view of aspects of nature.
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Prediction is difficult, especially of the future. NEILS BOHR This short article describes some of the features and history of chaos theory, with emphasis on its implications for predictability in general, and some thoughts on how these ideas might have an impact on medicine. In particular, it is suggested that inability to predict who will contract which diseases, or who will respond to which treatments, may be intrinsic, rather than simply due to incomplete knowledge of the particular patient. It follows that we patients should not expect too much of our doctors! When I am sick and consult my doctor, what I want to hear might go as follows: "Take these tablets three times a day for a week; you'll feel better after two days, and will be ready for work after four." I am expecting a great deal: not only to be cured, but to have the course of my cure predicted. Yet prediction is not trivial or easy. In fact chaos, the mainspring of this article, has shown us that predictability is the exception rather. than the rule, even for what seem like simple physical systems. A human being is immeasurably more complex than any demonstrably chaotic system-the question can be turned around: How can anything be predicted about a person? There is nonetheless a strong social pressure for answers to such questions as, Who will get cancer-or a heart attack? and, How long before a HIV positive subject develops AIDS?. At the risk of presumption, I will suggest analogies and lines of reasoning which imply that such questions make sense but can never be answered. The best that can be done, for an individual as well as a population, is to assess probabilities.

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