Kinds of Information in Scientific Use

There are many different mathematical definitions of information that have their various uses, but I will be concerned with notions of information used in applications in various branches of science that are distinguished by their topic, i.e., what they apply to. I describe the major uses informatio...

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Bibliographic Details
Main Author: John Collier
Format: Article
Language:English
Published: Paderborn University: Media Systems and Media Organisation Research Group 2011-10-01
Series:tripleC: Communication, Capitalism & Critique
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Online Access:https://www.triple-c.at/index.php/tripleC/article/view/278
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Summary:There are many different mathematical definitions of information that have their various uses, but I will be concerned with notions of information used in applications in various branches of science that are distinguished by their topic, i.e., what they apply to. I describe the major uses information, and show their relations to each other. I will argue that the various uses form a nested hierarchy, in which each is a restriction on the previous, inheriting the properties of its predecessor, but adding in new features that make it a special case. The lowest level is physical information determined by distinctions and the highest is explicit representation in linguistic social communication. Is there anything common to information at all these levels? I will argue that there is, and that information in each case is what Donald MacKay (1969) called a distinction that makes a difference. What distinguishes the use of information at each level is what distinctions make a causal difference at that level. At each successive level distinctions that make a difference at a previous level make no difference at that level. In order to create this sort of filter new levels have to be formed by cohesion peculiar to the identifying characteristics at that level. A consequence of this view is that information must have causal powers, and that there is a tight connection between information and causation
ISSN:1726-670X