This article defends the view that having a language just is knowing how to engage in communication with it. It also argues that, despite claims to the contrary, this view is compatible and complementary with the Chomskyan conception of language on which humans have languages in virtue of being in brain states realizing tacit knowledge of grammars for those languages.

Sentences in context have semantic contents determined by a range of factors both internal and external to speakers. I argue against the thesis that semantic content is transparent to speakers in the sense of being immediately accessible to speakers in virtue of their linguistic competence.

In this paper, I utilise the growing literature on scientific modelling to investigate the nature of formal semantics from the perspective of the philosophy of science. Specifically, I incorporate the inferential framework proposed by Bueno and Colyvan : 345–374, 2011) in the philosophy of applied mathematics to offer an account of how formal semantics explains and models its data. This view produces a picture of formal semantic models as involving an embedded process of inference and representation applying indirectly to linguistic (...) phenomena. The final aim of the paper is directed at proposing a novel account of the syntax–semantics interface while shedding light on empty categories, semantically null forms, underspecified content and compositionality as a whole. (shrink)

Assuming that linguistic representation has been studied only by linguists using grammaticality judgments, Branigan & Pickering present structural priming as a novel alternative. We show that their assumptions are incorrect for cognitive-functional linguistics, exposing converging perspectives on form/meaning pairings between generativists and cognitive-functional linguists that we hope will spark the cross-disciplinary discussion necessary to produce a cognitively plausible model of linguistic representation.

In his “Meaning and Formal Semantics in Generative Grammar” (Erkenntnis 2015, 61–87), Stephen Schiffer argues that truth-conditional semantics is a poor fit with generative linguistics. In particular, he thinks that it fails to explain speakers’ abilities to understand the sentences of their language. In its place, he recommends his “Best Bet Theory”—a theory which aims to directly explain speakers’ abilities to mean things by their utterances and know what others mean by their utterances. I argue that Schiffer does not provide (...) good reason to prefer the Best Bet Theory over truth-conditional semantics in the context of generative linguistics. First, his negative arguments against the truth-conditional approach are unpersuasive, and second, the Best Bet Theory involves an explanatory circularity which makes it unfit for linguistic theorizing. I conclude that the Best Bet Theory is thus not even a viable competitor to truth-conditional semantics in generative linguistics. (shrink)