Pragmatics is about language use in context. This involves theorizing about speakers’ choices of words and listeners’ ways of interpreting. More often than not, this also involves a certain amount of noise and uncertainty: speakers and listeners may not know exactly what the relevant contextual parameters are, they may make mistakes, believe that their interlocutor is uncertain and possibly prone to err, etc. We believe that taking this picture seriously can, despite its apparent messiness, inspire a stringent formal approach to pragmatics that lends itself to precise empirical testing. We call it probabilistic pragmatics here, to emphasize the role that probabilities play in it. But it contains much more. In the following, we try to sketch its main characterizing features in relation to other approaches and give some example applications. We argue that probability models are the natural and most practicable tool for modeling the richness of pragmatic phenomena which are affected by many unknown contextual factors. Sections 2 and 3 characterize probabilistic pragmatics. Section 2 discusses different levels of analysis in pragmatic theory, so as to contrast probabilistic pragmatics with alternative approaches. Section 3 discusses key properties of probabilistic pragmatics. Sections 4, 5 and 6 sketch examples of applications. Section 4 introduces a baseline model for reasoning about referential expressions to demonstrate how the probabilistic modeling, inspired by classical pragmatic theory, can be fit to experimental data. Section 5 exemplifies further ways in which probabilistic pragmatics can shed light on gradient patterns in empirical data. The leading example for illustration is that of scalar implicature. Section 6 argues that considering (multiple levels of) gradient subjective contextual uncertainty, as captured by a probability distribution, is essential to understanding indirect speech acts. This section demonstrates how explicit representations, inspired from game theory, of interlocutors’ preferences and likely dialogue moves help tackle indirectness of speech in non-cooperative contexts.

https://www.sfs.uni-tuebingen.de/~mfranke/Papers/FrankeJager_2015_Probabilistic%20pragmatics,%20or%20why%20Bayes'%20rule%20is%20probably%20important%20for%20pragmatics.pdf

Probabilistic pragmatics, or why Bayes’ rule is probably important for pragmatics

Distinct neural correlates for pragmatic and semantic meaning processing: An event-related potential investigation of scalar implicature processing using picture-sentence verification

Scalar implicaure is often offered as the exemplar of generalized conversational implicature. However, despite the wealth of literature devoted to both the phenomenon in general and to specific examples, little attention has been paid to the various factors that may influence the generation and interpretation of scalar implicatures. This study employs the “Literal Lucy” methodology developed in Larson et al. (in press) to further investigate these factors in a controlled experimental setting. The results of our empirical investigation suggest that the type of scale employed affects whether or not speakers judge a particular scalar implicature to be part of the truth-conditional meaning of an utterance. Moreover, we found that features of the conversational context in which the implicature is situated also play an important role. Specifically, we have found that the number of scalar values evoked in the discourse context plays a significant role in the interpretation of scalar implicatures generated from gradable adjective scales but not other scale types. With respect to the effects of scale type, we have found that gradable adjectives were less frequently incorporated into truth-conditional meaning than cardinals, quantificational items, and ranked orderings. Additionally, ranked orderings were incorporated less than cardinals. Thus, the results from the current study show that the interpretation of scalar implicature is sensitive to both the associated scale type and discourse context.

On the Non-Unified Nature of Scalar Implicature: An Empirical Investigation

A prevalent, but to date untested, assumption about lexicalized scalar implicatures such as those from some to not all , is that they fall into the class of GCIs and as such, constitute a homogeneous class of highly regularized and context-independent implicatures. This paper reports a test of this assumption in which linguistically untrained participants’ implicature strength judgments were collected for naturally occurring utterances containing the word some in a large-scale corpus-based web study. The results indicate that implicature strength is highly variable and systematically dependent on features of the linguistic context such as the partitive, determiner strength, and discourse accessibility. These results call into question the GCI status of scalar implicatures from some to not all and demonstrate the usefulness of corpora and web-based methods for challenging received wisdom, enriching the empirical landscape, and informing theory in pragmatics.

http://dx.doi.org/10.3765/sp.8.11

 BibTeX info

/pdf/investigating-the-distribution-of-some-but-not-all-39f0ihs4e2.pdf

Investigating the distribution of some (but not all ) implicatures using corpora and web-based methods

That there is a theoretical distinction between context-dependent and context-independent aspects of utterance interpretation has become a standard assumption in current theories of meaning; however, how and where to draw this distinction has been the subject of considerable debate. In the current study, we investigate whether speakers can systematically distinguish between what is said and what is implicated (Grice 1989 [1967]) using a novel truth-value judgment paradigm across a wide range of implicature types. We found that, by providing participants with a clear set of judgment criteria, including the adoption of an objective third-person perspective, we were able to enhance their ability to distinguish conversational implicature from truth-conditional meaning. In addition, we found that none of the implicature types we investigated was either consistently incorporated into or consistently excluded from what is said. Instead, our findings revealed considerable variation in frequency of incorporation across implicature types in ways that do not correspond straightforwardly to the various taxonomies of implicature types proposed in the literature.

A novel experimental paradigm for distinguishing between what is said and what is implicated

Distinguishing the said from the implicated using a novel experimental paradigm

/pdf/proximal-demonstratives-in-predicate-nps-b1sueyt5sg.pdf

Proximal Demonstratives in Predicate NPs

This chapter presents a preliminary taxonomy of the various ways in which demonstrative noun phrases are used, with particular focus on examples from English. The classification of demonstrative uses begins with a consideration of the semantic value of the demonstrative NP—whether the speaker is using the demonstrative to denote or refer to an entity, a kind, a predicate, or a variable in a quantificational domain—and then further categorizes the uses of demonstratives on the basis of various pragmatic considerations that influence their interpretation. The taxonomy includes many uses previously identified in the literature as well as other uses that have not heretofore been discussed.

Ryan Doran

Papers

On the Non-Unified Nature of Scalar Implicature: An Empirical Investigation

A novel experimental paradigm for distinguishing between what is said and what is implicated

Distinguishing the said from the implicated using a novel experimental paradigm

Proximal Demonstratives in Predicate NPs

A taxonomy of uses of demonstratives