Explaining vague language

TL;DR

This paper compares game-theoretic and Bayesian explanations of vagueness in language, arguing that semantic content is essential for understanding why vague language can be more informative than precise language.

Contribution

It clarifies the differences between two prominent accounts of vagueness and advocates for the importance of semantic content in explaining vagueness.

Findings

Semantic account of vagueness is more adequate.

Vagueness can be more informative than precision.

The two accounts are not mutually exclusive.

Abstract

Why is language vague? Vagueness may be explained and rationalized if it can be shown that vague language is more useful to speaker and hearer than precise language. In a well-known paper, Lipman proposes a game-theoretic account of vagueness in terms of mixed strategy that leads to a puzzle: vagueness cannot be strictly better than precision at equilibrium. More recently, \'Egr\'e, Spector, Mortier and Verheyen have put forward a Bayesian account of vagueness establishing that using vague words can be strictly more informative than using precise words. This paper proposes to compare both results and to explain why they are not in contradiction. Lipman's definition of vagueness relies exclusively on a property of signaling strategies, without making any assumptions about the lexicon, whereas \'Egr\'e et al.'s involves a layer of semantic content. We argue that the semantic account of vagueness is needed, and more adequate and explanatory of vagueness.