“There is a growing impetus to examine pragmatic phenomena experimentally. Potentially complicating these investigations is the way in which the experimental environment itself shapes participants’ models of extra‐linguistic context. A spate of recent results collectively suggest that the computation of scalar implicature may be sensitive to a host of factors: task structure, social norms, and type of response elicited. However, these results provide only a few points in a vast space of potential task parameters, thereby limiting our ability to systematically model the interaction between linguistic forms, context and pragmatic inference. This talk reports ongoing work to systematically investigate the parametric space of task design. We find that implicature calculation rates are sensitive to both the structure of the response elicited (e.g., scalar vs. unordered) as well as the task prompt (whether the participant judges “accuracy”, “informativity”, or “goodness”), and discuss the methodological lessons of this kind of work.”

Pranav Anand is Assistant Professor of Linguistics at UC Santa Cruz. Professor Anand’s research focuses largely on two matters: how context intrudes into or guides the interpretive process and how perspective is grammatically represented. These are manifested by my interest in the de re/de se/de dicto contrasts, the nature of subjectivity in evaluative and epistemic predication, and the structure of indexical shift.

His current projects include the fine lexical semantics of attitude verbs; real-time processing of implicatures and plurality; computational modeling of multi-party discourse; and computational modeling of high-level discourse plans, especially those involved in argumentation and persuasion.

This talk is presented by the Department of Linguistics. For more information please contact Nathan Arnett, nvarnett@ucsc.edu.