In a recent paper, after outlining various distinguishing features of derogatory words, Jennifer Hornsby suggests that the phenomenon raises serious difficulties for inferentialism. Against Hornsby, I claim that derogatory words do not pose any insuperable problems for inferentialism, so long as it is supplemented with apparatus borrowed from Grice and Hare. Moreover, I argue, derogatory expressions pose difficulties for Hornsby's favoured alternative theory of meaning, representationalism, unless it too is conjoined with a similar Grice/Hare mechanism. So, the upshot of the (...) discussion is that, contra Hornsby, focus on derogatory expressions alone does not provide grounds for deciding between competing theories of meaning, but nevertheless serves to highlight important features that any such theory must acknowledge and incorporate. (shrink)

Causal theories of content, a popular family of approaches to defining the content of mental states, commonly run afoul of two related and serious problems that prevent them from providing an adequate theory of mental content—the misrepresentation problem and the disjunction problem. In this paper, I present a causal theory of content, built on information theoretic tools, that solves these problems and provides a viable model of mental content. This is the greatest surprise reduction theory of content, which identifies the (...) content of a signal as the event the surprisal of which is most reduced by that signal. Conceptually, this amounts to the claim that the content of a signal is the event the probability of which has increased by the largest proportion, or the event that the signal makes the most less surprising to us. I develop the greatest surprise reduction theory of content in four stages. First, I introduce the general project of causal theories of content, and the challenges presented to this project by the misrepresentation and disjunction problems. Next, I review two recent and prominent causal theories of content and demonstrate the serious challenges faced by these approaches, both clarifying the need for a solution to the misrepresentation and disjunction problems and providing a conceptual background for the greatest surprise reduction theory. Then, I develop the greatest surprise reduction theory of content, demonstrate its ability to resolve the misrepresentation and disjunction problems, and explore some additional applications it may have. Finally, I conclude with a discussion of a particularly difficult challenge that remains to be addressed—the partition problem—and sketch a path to a potential solution. (shrink)

Metaphorical meaning can be analyzed as triggered by an apparent communicative breach, an incongruity that leads to a default of the presumptive interpretation of a vehicle. This breach can be solved through contextual renegotiations of meaning guided by the communicative intention, or rather the presumed purpose of the metaphorical utterance. This paper addresses the problem of analyzing the complex process of reasoning underlying the reconstruction of metaphorical meaning. This process will be described as a type of abductive argument, aimed at (...) explaining how the vehicle can best contribute to the purpose of the utterance. This type of reasoning involves the analysis of the possible predicates that can be and usually are attributed to the vehicle, and the selection of the one that can support the implicit conclusion constituting the communicative goal of the metaphorical utterance. Metaphorical meaning, in this perspective, becomes the outcome of a complex process of meaning reconstruction aimed at providing the best explanation of the function of the vehicle within a discourse move. (shrink)