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Area of Science:

  • Cognitive Science
  • Formal Semantics
  • Pragmatics

Background:

  • Understanding uncertainty is crucial for human communication.
  • Probability expressions like 'likely' are used to convey degrees of belief.
  • Higher-order uncertainty involves uncertainty about probabilities themselves.

Purpose of the Study:

  • To present novel experimental data on the interpretation of simple and complex probability expressions.
  • To critically assess a probabilistic pragmatics model within the Rational Speech Act framework.
  • To evaluate a compositional threshold-semantics for probability expressions.

Main Methods:

  • Experimental investigation of human interpretation of probability expressions.
  • Analysis of data concerning simple (e.g., 'possible') and complex (e.g., 'possibly likely') expressions.
  • Critique of a Rational Speech Act model using empirical findings.

Main Results:

  • Experimental data reveals nuanced interpretations of probability expressions.
  • The data provides a critical test for probabilistic pragmatics models.
  • Findings inform the understanding of compositional semantics for modal and probability terms.

Conclusions:

  • Existing probabilistic pragmatics models may require refinement.
  • The study contributes to the formal semantics and cognitive science of uncertainty.
  • Novel data offers insights into higher-order uncertainty and language interpretation.