A Statistical Referential Theory of Content: Using Information Theory to Account for Misrepresentation

Mind and Language 16 (3):311-334 (2001)
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Abstract

A naturalistic scheme of primitive conceptual representations is proposed using the statistical measure of mutual information. It is argued that a concept represents, not the class of objects that caused its tokening, but the class of objects that is most likely to have caused it (had it been tokened), as specified by the statistical measure of mutual information. This solves the problem of misrepresentation which plagues causal accounts, by taking the representation relation to be determined via ordinal relationships between conditional probabilities. The scheme can deal with statistical biases and does not rely on arbitrary criteria. Implications for the theory of meaning and semantic content are addressed.

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Marius Usher
Tel Aviv University

Citations of this work

Naturalising Representational Content.Nicholas Shea - 2013 - Philosophy Compass 8 (5):496-509.
Informational Theories of Content and Mental Representation.Marc Artiga & Miguel Ángel Sebastián - 2020 - Review of Philosophy and Psychology 11 (3):613-627.
Operationalising Representation in Natural Language Processing.Jacqueline Harding - 2023 - British Journal for the Philosophy of Science.
Teleosemantic modeling of cognitive representations.Marc Artiga - 2016 - Biology and Philosophy 31 (4):483-505.

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