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Processing scalar implicature: a constraint-based approach.

Judith Degen1, Michael K Tanenhaus

  • 1Department of Psychology, Stanford University.

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Summary
This summary is machine-generated.

This study reveals how people interpret "some," finding it less natural for very small or all quantities. Exact number descriptions further impact the perceived naturalness of "some" in language processing.

Keywords:
AlternativesPragmaticsQuantifiersScalar implicature

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Area of Science:

  • Psycholinguistics
  • Cognitive Science
  • Semantics

Background:

  • Scalar implicatures, like the meaning of 'some,' are crucial for efficient communication.
  • Understanding how quantity affects the interpretation of scalar terms is key to psycholinguistic models.
  • Previous models struggle to fully explain the nuanced use of 'some' across different quantities.

Purpose of the Study:

  • To investigate the processing of scalar implicature associated with the word 'some.'
  • To determine how quantity (small, intermediate, unpartitioned sets) influences the naturalness of 'some.'
  • To test predictions of different scalar implicature processing models.

Main Methods:

  • Utilized a 'gumball paradigm' with controlled set sizes (1-13 gumballs).
  • Collected naturalness ratings for statements using 'some' and 'some of' across varying quantities.
  • Measured response times to assess processing efficiency and compared them with naturalness ratings.

Main Results:

  • 'Some' was rated less natural for small (1-3) and unpartitioned (all 13) gumball sets compared to intermediate sets (6-8).
  • Partitive 'some of' was less natural than simple 'some' for unpartitioned sets.
  • Exact number descriptions decreased naturalness for 'some' with small sets, but not intermediate or unpartitioned sets.

Conclusions:

  • Findings support a Constraint-Based account of scalar implicature processing.
  • Results challenge Literal-First and pragmatic Default models of language comprehension.
  • The study highlights the context-dependent and quantity-sensitive nature of scalar implicature processing.