From Copernicus to Ptolemy: Inconsistency and Method

Part of the Origins book series (ORIN, volume 2)


In recent years several philosophers and other science studies experts have adopted a somewhat more Ptolemaic than Copernican view of theories, models, and scientific research, namely, the “semantic” conception of theories and their applications. On the old, “Copernican” view, theories are deductively integrated, interpreted logical calculi, in standard symbolic logic, and science is a theory-centered enterprise that aims for a comprehensive, single picture of the universe. Accordingly, consistency becomes a hard constraint, a sine qua non of useful, rational inquiry. Proponents of the semantic conception are somewhat more “Ptolemaic” in treating theories as collections of models and in placing the solution of local problems in restricted domains ahead of grand, spectator theories of the universe. They focus as much on the process of inquiry as upon the logical structure of its products. Remarkably, in scientific practice we find inconsistencies and near-inconsistencies of various kinds apparently popping up everywhere, suggesting that one cannot lay a tight grid of standard logic over scientific practice. However, deflating unitary theories into collections of models makes inconsistency harder to define and locate precisely—but also less serious. Consistency often becomes a soft, negotiable constraint—one constraint among others. In practice, inconsistency rarely leads to complete disaster, for there are various ways to tame it. I urge paraconsistency and inconsistency-tolerant logicians to pay attention to real scientific examples of scientists’ responses to inconsistency and quasi-inconsistency, e.g., conceptual incongruities such as conceptual “blowups” and pragmatic inconsistencies such as the simultaneous use of mutually inconsistent models.


Scientific Practice Semantic Conception Family Resemblance Semantic View Logical Calculus 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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© Springer Science+Business Media Dordrecht 2002

Authors and Affiliations

  1. 1.Philosophy DepartmentUniversity of NevadaRenoUSA

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