Robert Cummins

In this paper, I sketch a revision of jonathan bennett's "meaning-Nominalist strategy" for explaining the conventional meanings of utterance-Types. Bennett's strategy does not explain sentence-Meaning by appeal to sub-Sentential meanings, And hence cannot hope to yield a theory that assigns a meaning to every sentence. I revise the strategy to make it applicable to predication and identification. The meaning-Convention for a term can then be used to fix its satisfaction conditions. Adapting a familiar trick of tarski's, We can then determine an infinity of conventional meanings from a finite number of meaning-Conventions.

As a procedure, reflective equilibrium is simply a familiar kind of standard scientific method with a new name. A theory is constructed to account for a set of observations. Recalcitrant data may be rejected as noise or explained away as the effects of interference of some sort. Recalcitrant data that cannot be plausibly dismissed force emendations in theory. What counts as a plausible dismissal depends, among other things, on the going theory, as well as on background theory and on knowledge that may be relevant to under-standing the experimental design that is generating the observations, including knowledge of the apparatus and observation conditions. This sort of mutual adjustment between theory and data is a familiar feature of scientific practice. Whatever authority RE seems to have comes, I think, from a tacit or explicit recognition that it has the same form as this familiar sort of scientific inference. One way to see the rationale underlying this procedure in science is to focus on prediction. Think of prediction as a matter of projecting what is known onto uncharted territory. To do this, you need a vehicle—a theory—that captures some invariant or pattern in what is known so that you can project it onto the unknown. How convincing the projection is depends on two factors: how sure one is of the observational base, and how sure one is that the theory gets the invariants right. The two factors are not independent, of course. One's confidence in the observational base will be affected by how persuasively the theory identifies and dismisses noise; one's confidence in the theory, on the other hand, will depend on one's confidence in the observations it takes seriously. Prediction is important as a test of theory precisely because verified predictions seem to show that the theory has correctly captured the general in the particular, that it has got the drift of the observational evidence in which our confidence is ultimately grounded.

The "conservative" holds that mental disorder exculpates only if it is evidence of a standard excuse or justification, i.e., one that a mentally "normal" person could have. The Liberal holds that mental disorder sometimes exculpates in itself. I argue that moral culpability in the case of mental disorder is often moot, and that the real issue is what a court should be allowed to do with such individuals. This undermines the idea that culpability is a necessary condition for sentencing, but we already have that in cases of strict liability, and there seems to be no viable alternative in any case.

D O N A L D D AV I D S O N’S “ Meaning and Truth,” re vo l u t i o n i zed our conception of how truth and meaning are related (Davidson    ). In that famous art i c l e, Davidson put forw a rd the bold conjecture that meanings are satisfaction conditions, and that a Tarskian theory of truth for a language is a theory of meaning for that language. In “Meaning and Truth,” Davidson proposed only that a Tarskian truth theory is a theory of meaning. But in “Theories of Me a n i n g and Learnable Languages,” he argued that the finite base of a Tarskian theory, together with the now familiar combinatorics, would explain how a language with unbounded expre s s i ve capacity could be learned with finite means ( Davidson    ). This certainly seems to imply that learning a language is, in p a rt at least, learning a Tarskian truth theory for it, or, at least, learning what is specified by such a theory. Davisdon was cagey about committing to the view that meanings actually a re satisfaction conditions, but subsequent followers had no such scru p l e s. We can sum this up in a trio of claims: Davidson’s Conjecture () A theory of meaning for L is a truth-conditional semantics for L. () To know the meaning of an expression in L is to know a satisfaction condition for that expression. () Meanings are satisfaction conditions. For the most part, it will not matter in what follows which of these claims is at stake. I will simply take the three to be different ways of formulating what I will call Davidson’s Conjecture (or sometimes just The Conjecture). Davidson’s Conjecture was a very bold conjecture. I think we are now in a..

This paper considers two ways functions figure into scientific explanations: (i) via laws?events are causally explained by subsuming those events under functional laws; and (ii) via designs?capacities are explained by specifying the functional design of a system. We argue that a proper understanding of how functions figure into design explanations of capacities makes it clear why such functions are ill-suited to figure into functional-cum-causal law explanations of events, as those explanations are typically understood. We further argue that a proper understanding of how functions enter into design explanations of capacities enables us to show why two prominent objections to functionalism in the philosophy mind?the argument from metaphysically necessary effects (Bennett, 2007; Rupert, 2006) and causal exclusion (Kim, 1993, 1998; Malcolm, 1968)?are misguided when interpreted as posing a threat to functional explanation in science across the board. If those arguments pose a threat at all, they pose it to instances of (i); however, a great number of the functional explanations we find in psychology?and the sciences generally?are instances of (ii)

The thesis that subsumption is sufficient for explanation is dying out, but the thesis that it is necessary is alive and well. It is difficult to attack this thesis: non-subsumptive counter-examples are declared incomplete, or mere promissory notes. No theory, it is thought, can be explanatory unless it resorts to subsumption at some point. In this paper I attack this thesis by describing a theory that (1) would explain every event it could describe, (2) does not explain by subsumption, and (3) is fundamental in that it is understood to be irreducible (hence there are no unstated laws waiting in the wings).

There is a certain view abroad in the land concerning the philosophical problems raised by Tarskian semantics. This view has it that a Tarskian theory of truth in a language accomplishes nothing of interest beyond the definition of truth in terms of satisfaction, and, further, that what is missing — the only thing that would yield a solution to the philosophical problem of truth when added to Tarskian semantics — is a reduction of satisfaction to a non-semantic relation. It seems to me that this view either misidentifies the philosophical problem altogether, or encourages a seriously misleading picture of the nature of the problem.The view I have in mind is nowhere more persuasively at work than in a recent paper by Hartry Field.1 In this paper Field argues that a Tarskian theory of truth for a natural language is impossible if we insist on Tarski's case-by-case elimination of ‘satisfies'. More fundamentally, however, he argues that a Tarskian theory could provide nothing of philosophical interest beyond the admittedly interesting reduction of truth to satisfaction, and his ground for this claim is, roughly, that a Tarskian theory does not reduce its primitive semantic relation — satisfaction — to a non-semantic relation.

Neo-teleology is the two part thesis that, e.g., (i) we have hearts because of what hearts are for: Hearts are for blood circulation, not the production of a pulse, so hearts are there--animals have them--because their function is to circulate the blood, and (ii) that (i) is explained by natural selection: traits spread through populations because of their functions. This paper attacks this popular doctrine. The presence of a biological trait or structure is not explained by appeal to its function. To suppose otherwise is to trivialize natural selection.

Haugeland doesn’t have what I would call a theory of mental representation. Indeed, it isn’t clear that he believes there is such a thing. But he does have a theory of intentionality and a correlative theory of objectivity, and it is this material that I will be discussing in what follows. It will facilitate the discussion that follows to have at hand some distinctions and accompanying terminology I introduced in Representations, Targets and Attitudes (Cummins, 1996; RTA hereafter). Couching the discussion in these terms will, I hope, help to identify points of agreement and disagreement between Haugaland and myself. In RTA, I distinguished between the target a representation has on a given occasion of its application, and its content. RTA takes representation deployment to be the business of intenders: mechanisms whose business it is to represent some particular class of targets. Thus, on standard stories about speech perception, there is a mechanism (called a parser) whose business it is to represent the phrase structure of the linguistic input currently being processed. When this intender passes a representation R to the consumers of its products, those consumers will take R to be a representation of the phrase structure of the current input. There is no explicit vocabulary to mark the target-content distinction in ordinary language. Expressions like "what I referred to," "what I meant," and the like, are ambiguous. Sometimes they mean targets, sometimes contents. Consider the following dialogue.

What are the prospects for a cognitive science of meaning? As stated, we think this question is ill posed, for it invites the conflation of several importantly different semantic concepts. In this paper, we want to distinguish the sort of meaning that is an explanandum for cognitive science—something we are going to call meaning—from the sort of meaning that is an explanans in cognitive science—something we are not going to call meaning at all, but rather content. What we are going to call meaning is paradigmatically a property of linguistic expressions or acts: what one’s utterance or sentence means, and what one means by it. What we are going to call content is a property of, among other things, mental representations and indicator signals. We will argue that it is a mistake to identify meaning with content, and that, once this is appreciated, some serious problems emerge for grounding meaning in the sorts of content that cognitive science is likely to provide.