Vagueness, communication, and semantic information

Student thesis: Doctoral ThesisDoctor of Philosophy

Abstract

To be learnable, words must contribute something that is pretty
stable across contexts. But equally, words must also be flexible
enough to be able to stretch, in a principled way, to cover new
cases. Similarly, to be effective for communication, the information
that words encode must be robust enough and flexible
enough to help us achieve a wide variety of goals. It is argued that
truth conditions, and information understood in terms of truth
conditions, cannot satisfy these requirements. A replacement for
the truth conditional model is suggested based on a statistically
grounded conception of semantic information. Informally, this
can be understood in terms of reasonable expectations (what it is
reasonable to believe, given the words that were used). Formally,
this semantic information is captured using probabilistic and
information theoretic tools. Vagueness, understood in terms of
borderline cases, is argued to be a byproduct of making the above
learning and communication requirements central. Vagueness,
understood as our ability to be vague with words, is given an information
theoretic explanation. Finally, the account is defended
with respect to some of the philosophical problems and puzzles
found in the vagueness literature.
Date of Award2013
Original languageEnglish
Awarding Institution
  • King's College London
SupervisorShalom Lappin (Supervisor) & Mark Textor (Supervisor)

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