Journal
LANGUAGE COGNITION AND NEUROSCIENCE
Volume 29, Issue 8, Pages 912-927Publisher
ROUTLEDGE JOURNALS, TAYLOR & FRANCIS LTD
DOI: 10.1080/01690965.2013.854918
Keywords
pronoun production; implicit causality; information structure
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Funding
- Andrew W. Mellon post-doctoral fellowship
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A standard assumption in psycholinguistic research on pronoun interpretation is that production and interpretation are guided by the same set of contextual factors. A line of recent research has suggested otherwise, however, arguing instead that pronoun production is insensitive to a class of semantically driven contextual biases that have been shown to influence pronoun interpretation. The work reported in this paper addresses three fundamental questions that have been left unresolved by this research. First, research demonstrating the insensitivity of production to semantic biases has relied on referentially unambiguous settings in which the comprehender's ability to resolve the pronoun is not actually at stake. Experiment 1, a story continuation study, demonstrates that pronoun production is also insensitive to semantic biases in settings in which a pronoun would be referentially ambiguous. Second, previous research has not distinguished between accounts in which production biases are driven by grammatical properties of intended referents (e. g., subject position) or by information-structural factors (specifically, topichood) that are inherently pragmatic in nature. Experiment 2 examines this question with a story continuation study that manipulates the likelihood of potential referents being the topic while keeping grammatical role constant. A significant effect of the manipulation on rate of pronominalisation supports the claim that pronoun production is influenced by the likelihood that the referent is the current topic. Lastly, the predictions of Kehler et al.'s Bayesian analysis of the relationship between production and interpretation have never been quantitatively examined. The results of both experiments are shown to support the analysis over two competing models.
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