Nerdiness, pedantry and credibility. How social stereotypes help us navigate imprecision.
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​Pragmatic reasoning has been shown to be shaped by different sources of social information -- e.g., politeness considerations (Bonnefon et al. 2009, Yoon et al. 2020, Mazzarella et al. 2018); affect (Bergen 2016); speaker-specific properties (Fairchild 2018; Mahler 2022), group membership (Kuperwasser et al. 2022). In this talk -- and in my work more broadly -- I take this line of work further by asking the following: how does the social stereotype that a speaker embodies shape different dimensions of meaning interpretation? Based on findings from two experiments, I'll present evidence that comprehenders interpret round numbers (e.g., $200) more strictly (Exp 1) – i.e., as referring to a more narrow range of values – when these are uttered by Nerdy characters, a type of speaker who is expected to describe things more precisely – as opposed to Chill ones – a type of speaker who is expected to describe things less precisely. At the same time, comprehenders judge imprecise descriptions uttered by Nerdy characters more leniently -- i.e, they take them to be correct more often than imprecise descriptions uttered by Chill speakers (Exp 2). These results suggest that stereotype-based social information affects two distinct levels of pragmatic reasoning: the computation of the circumstances that a description can be taken to represent; and the calibration of the degree of epistemic authority granted to someone who is potentially misrepresenting the relevant facts. Taken together, these results open a novel perspective on how the social and descriptive dimensions of meaning interact, highlighting the need to continue investigating the role of sociolinguistic information in semantic interpretation.​
Date: Friday, November 3rd 2023
Time: 3pm-4:30pm
Location: Room 107
Zoom: https://udel.zoom.us/my/ahafri​
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Nerdiness, pedantry and credibility. How social stereotypes help us navigate imprecision.
Linguistics and Cognitive Science
11/2/2023
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