In this paper I will discuss why (un) marked expressionstypically get an (un)marked interpretation: Horn''sdivision of pragmatic labor. It is argued that it is aconventional fact that we use language this way.This convention will be explained in terms ofthe equilibria of signalling games introduced byLewis (1969), but now in an evolutionary setting. Iwill also relate this signalling game analysis withParikh''s (1991, 2000, 2001) game-theoretical analysis ofsuccessful communication, which in turn is compared withBlutner''s: 2000) bi-directional optimality theory.

This article described three heuristics that are employed in making judgements under uncertainty: representativeness, which is usually employed when people are asked to judge the probability that an object or event A belongs to class or process B; availability of instances or scenarios, which is often employed when people are asked to assess the frequency of a class or the plausibility of a particular development; and adjustment from an anchor, which is usually employed in numerical prediction when a relevant value (...) is available. These heuristics are highly economical and usually effective, but they lead to systematic and predictable errors. A better understanding of these heuristics and of the biases to which they lead could improve judgements and decisions in situations of uncertainty. (shrink)

We review Potts’ influential book on the semantics of conventional implicature (CI), offering an explication of his technical apparatus and drawing out the proposal’s implications, focusing on the class of CIs he calls supplements. While we applaud many facets of this work, we argue that careful considerations of the pragmatics of CIs will be required in order to yield an empirically and explanatorily adequate account.

This paper argues that just as full beliefs can constitute knowledge, so can properties of your credence distribution. The resulting notion of probabilistic knowledge helps us give a natural account of knowledge ascriptions embedding language of subjective uncertainty, and a simple diagnosis of probabilistic analogs of Gettier cases. Just like propositional knowledge, probabilistic knowledge is factive, safe, and sensitive. And it helps us build knowledge-based norms of action without accepting implausible semantic assumptions or endorsing the claim that knowledge is interest-relative.

Sarah Moss argues that degrees of belief, or credences, can amount to knowledge in much the way that full beliefs can. This essay explores a new kind of objective Bayesianism designed to take us some way toward securing such knowledge-constituting credences, or "probabilistic knowledge." Whatever else it takes for an agent's credences to amount to knowledge, their success, or accuracy, must be the product of _cognitive ability_ or _skill_. The brand of Bayesianism developed here helps ensure this ability condition is (...) satisfied. Cognitive ability, in turn, helps make credences valuable in other ways: it helps mitigate their dependence on epistemic luck, for example. What we end up with, at the end of the day, are credences that are particularly good candidates for constituting probabilistic knowledge. What's more, examining the character of these credences teaches us something important about what the pursuit of probabilistic knowledge demands from us. It does _not_ demand that we give hypotheses equal _treatment_, by affording them equal credence. Rather, it demands that we give them equal _consideration_, by affording them an equal chance of being discovered. (shrink)

I argue that code words like “inner city” do not semantically encode hidden or implicit meanings, and offer an account of how they nonetheless manage to bring about the surprising effects discussed in Mendelberg 2001, White 2007, and Stanley 2015 (among others).

This paper refines the game theoretic analysis of conversations in Asher et al. by adding epistemic concepts to make explicit the intuitive idea that conversationalists typically conceive of conversational strategies in a situation of imperfect information. This ‘epistemic’ turn has important ramifications for linguistic analysis, and we illustrate our approach with a detailed treatment of linguistic examples.

When two people engage in a conversation, knowingly or unknowingly, they are playing a game. Players of such games have diverse objectives, or winning conditions: an applicant trying to convince her potential employer of her eligibility over that of a competitor, a prosecutor trying to convict a defendant, a politician trying to convince an electorate in a political debate, and so on. We argue that infinitary games offer a natural model for many structural characteristics of such conversations. We call such (...) games message exchange games, and we compare them to existing game theoretic frameworks used in linguistics—for example, signaling games—and show that message exchange games are needed to handle non-cooperative conversation. In this paper, we concentrate on conversational games where players’ interests are opposed. We provide a taxonomy of conversations based on their winning conditions, and we investigate some essential features of winning conditions like consistency and what we call rhetorical cooperativity. We show that these features make our games decomposition sensitive, a property we define formally in the paper. We show that this property has far-reaching implications for the existence of winning strategies and their complexity. There is a class of winning conditions for which message exchange games are equivalent to Banach- Mazur games, which have been extensively studied and enjoy nice topological results. But decomposition sensitive goals are much more the norm and much more interesting linguistically and philosophically. (shrink)

This essay explores the speech act of dogwhistling (sometimes referred to as ‘using coded language’). Dogwhistles may be overt or covert, and within each of these categories may be intentional or unintentional. Dogwhistles are a powerful form of political speech, allowing people to be manipulated in ways they would resist if the manipulation was carried outmore openly—often drawing on racist attitudes that are consciously rejected. If philosophers focus only on content expressed or otherwise consciously conveyed they may miss what is (...) most powerful and pernicious in the speech of political culture. This essay is a call to start paying attention to these more covert speech acts, and a first attempt at beginning to theorize them. It argues that dogwhistles present a complex and interesting case for the philosopher of language, and explores their implications for democratic politics. (shrink)

This is the first of two papers that use off-training set (OTS) error to investigate the assumption-free relationship between learning algorithms. This first paper discusses the senses in which there are no a priori distinctions between learning algorithms. (The second paper discusses the senses in which there are such distinctions.) In this first paper it is shown, loosely speaking, that for any two algorithms A and B, there are “as many” targets (or priors over targets) for which A has lower (...) expected OTS error than B as vice versa, for loss functions like zero-one loss. In particular, this is true if A is cross-validation and B is “anti-cross-validation” (choose the learning algorithm with largest cross-validation error). This paper ends with a discussion of the implications of these results for computational learning theory. It is shown that one cannot say: if empirical misclassification rate is low, the Vapnik-Chervonenkis dimension of your generalizer is small, and the training set is large, then with high probability your OTS error is small. Other implications for “membership queries” algorithms and “punting” algorithms are also discussed. (shrink)

A speaker wishes to persuade a listener to accept a certain request. The conditions under which the request is justified, from the listener’s point of view, depend on the values of two aspects. The values of the aspects are known only to the speaker and the listener can check the value of at most one. A mechanism specifies a set of messages that the speaker can send and a rule that determines the listener’s response, namely, which aspect he checks and (...) whether he accepts or rejects the speaker’s request. We study mechanisms that maximize the probability that the listener accepts the request when it is justified and rejects the request when it is unjustified, given that the speaker maximizes the probability that his request is accepted. We show that a simple optimal mechanism exists and can be found by solving a linear programming problem in which the set of constraints is derived from what we call the L-principle. (shrink)