Empirical Modeling and Information Semantics

Mind & Society 7 (2):157 (2008)
Abstract
This paper investigates the relationship between reality and model, information and truth. It will argue that meaningful data need not be true in order to constitute information. Information to which truth-value cannot be ascribed, partially true information or even false information can lead to an interesting outcome such as technological innovation or scientific breakthrough. In the research process, during the transition between two theoretical frameworks, there is a dynamic mixture of old and new concepts in which truth is not well defined. Instead of veridicity, correctness of a model and its appropriateness within a context are commonly required. Despite empirical models being in general only truthlike, they are nevertheless capable of producing results from which conclusions can be drawn and adequate decisions made.
Keywords Modeling  Information Semantics  Validation and Verification
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References found in this work BETA
Jon Barwise & John Perry (1981). Situations and Attitudes. Journal of Philosophy 78 (11):668-691.
Luciano Floridi (2005). Is Semantic Information Meaningful Data? Philosophy and Phenomenological Research 70 (2):351-370.

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