Projection inferences with clause-embedding predicates in RSA models

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Abstract/Contents

Abstract
Projection inferences are inferences about speaker commitment to content embedded that project through an entailment-canceling operator. In this thesis, we investigate projection inferences in polar interrogatives with clause-embedding predicates (e.g., Does John know that Julian dances salsa?). Inferred speaker belief regarding whether Julian dances salsa is modulated by multiple factors, including the predicate used, interlocutors' prior beliefs about the content, and the content's at-issueness. In a behavioral study, we investigate the beliefs about contents embedded under the predicates “think” and “know” that listeners ascribe to the speaker and a potential attitude holder (John). We propose three different probabilistic models couched in the Rational Speech Act (RSA) framework, in an attempt to provide a unified computational account of projection inferences about content embedded under clause-embedding predicates. The empirical data are used to infer the parameters and evaluate the model predictions. The predictions of each model mirror some, but not all, of the qualitative empirical patterns. This is a step towards a systematic analysis of projection inferences using probabilistic pragmatic models.

Description

Type of resource text
Publication date December 8, 2023

Creators/Contributors

Author Pan, Dingyi ORCiD icon https://orcid.org/0000-0003-2661-357X (unverified)
Advisor Degen, Judith

Subjects

Subject Projection inerences
Subject Clause-embedding predicates
Subject Experimental pragmatics
Subject Probabilistic pragmatics
Genre Text
Genre Thesis

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This work is licensed under a Creative Commons Attribution Non Commercial 4.0 International license (CC BY-NC).

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Preferred citation
Pan, D. (2023). Projection inferences with clause-embedding predicates in RSA models. Stanford Digital Repository. Available at https://purl.stanford.edu/sx158jh3545. https://doi.org/10.25740/sx158jh3545.

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Master's Theses, Symbolic Systems Program, Stanford University

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