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<p> One of Carnap&rsquo;s overarching aims was to set philosophy on a firm scientific footing. He relied primarily on two ideas to achieve his ideal of a scientific philosophy: verificationism, according to which only empirically testable or logically determinate sentences are meaningful, and the Principle of Tolerance, which held that we are free to choose whichever system of empirical knowledge is most expedient. The logical empiricism embodied in these views is is widely believed to have been decisively refuted by a variety of objections. </p><p> My dissertation seeks to clarify the content and aims of Carnap&rsquo;s tolerance and verificationism, and to defend the resulting view against some of the most influential objections to logical empiricism. I argue that both tolerance and verificationism are manifestations of Carnap&rsquo;s fundamentally pragmatic conception of scientific language; for Carnap, precise formulations of scientific theory&mdash;&ldquo;languages for science&rdquo;&mdash; are to be viewed as instruments for the derivation of intersubjective observational knowledge. </p><p> Verificationism, on my interpretation, is the decision to narrow one&rsquo;s options for a language for science to those languages in which every sentence is either empirically testable or logically determinate. This decision is motivated by Carnap&rsquo;s pragmatism: any sentence that is neither empirically testable nor logically determinate makes no contribution to the aim with which the pragmatist uses scientific language. </p><p> I use this pragmatist account of verificationism to respond to two objections. The first is Hilary Putnam&rsquo;s version of the argument that verificationism is neither empirical nor analytic, and is therefore meaningless by its own lights. According to Putnam, Carnap&rsquo;s construal of verificationism as significant in a practical, but non-cognitive, sense, in response to the objection, presupposes verificationism. Carnap&rsquo;s response is therefore viciously circular. I respond that Carnap&rsquo;s non-cognitive conception of verificationism presupposes pragmatism, and not verificationism, and thereby avoids Putnam&rsquo;s circularity. Second, there is a widespread belief that verificationism requires a criterion of empirical significance in order to demarcate the empirically testable sentences, but that no such criterion can be formulated. I reply that by adopting the pragmatic conception, the verificationist can select her favored language in the case-by-case manner described by Goldfarb and Ricketts, without a criterion of empirical significance. </p><p> Carnap&rsquo;s pragmatism maintains that the goal of scientific language is the derivation of observation reports. It therefore helps itself to a notion of observation report, of observation language. This notion is another major source of skepticism about logical empiricism. I argue that Carnap&rsquo;s account of observation language in &ldquo;Testability and Meaning&rdquo; is sufficient for the purposes of his pragmatism. On this account, a term is observational to the extent that it can be applied on the basis of minimal observation and inference. A degree of observationality can then be arbitrarily designated sufficient and necessary for a term&rsquo;s being observational in the language. I show that this approach to fixing the observation language is not vulnerable to van Fraassen&rsquo;s objections. </p><p> Finally, pragmatism helps to clarify Carnap&rsquo;s Principle of Tolerance. According to a widely held view, Carnap&rsquo;s tolerance rests on &ldquo;relativity to language&rdquo;: since a language for science provides the rules for inquiry&mdash;be these semantic or evidential rules&mdash;language cannot itself be subject to such rules. So interpreted, the Principle of Tolerance is able to provide a critique of what I call &lsquo;first philosophy&rsquo;, i.e., the doctrine that the choice of concepts or rules in science can be constrained by considerations external to these rules. (Abstract shortened by UMI.)</p>

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<p> My dissertation lies at the philosophical intersection of the American pragmatist tradition and contemporary epistemology. By treating truth, justification, and belief as matters of degree, I develop a measure of knowledge that captures all of our fundamental intuitions while providing answers to the problems of epistemic luck, skepticism, and scientific pessimism. </p><p> Traditionally, knowledge is understood as justified true belief that is not due to luck. My project follows this general outline. First, I describe the pragmatist understanding of truth first articulated by Charles Sanders Peirce in the late nineteenth century. My first chapter offers Peirce's understanding of truth as the best explanation of our intuitive understanding of what it is for a proposition to be the case and shows how we can understand Peirce's theory as compatible with contemporary theories of truth. </p><p> In my second chapter, I develop a theory of belief such that an agent believes a proposition when she acts as if that proposition were a rule governing her behavior. On this view, beliefs are theoretical entities posited to make sense of other agents' actions. Following this account of belief, I describe what it is for a belief to be true and argue that sense of truth in which beliefs are true is best understood as an approximation of the full descriptive truth. </p><p> My third, fourth, and fifth chapters are an account of justification. Chapter 3 is a descriptive account of synchronic justification: we all reject or accept propositions in accordance with maximizing the coherence of our belief-networks. Chapters 4 and 5 articulate and then defend a new measure of diachronic justification, which is a measure of the degree to which a belief is appropriately revisable and therefore embeddable in an ongoing process of fallibilist inquiry. I develop a novel formal quantification of methodological justification and show that it gives plausible results when applied to popular cases. </p><p> My final chapter brings justification, truth, and belief together into a scalar knowledge measure. I locate my theory in ongoing epistemic inquiry, describing its conceptual advantages over rival theories as well as its ability to replicate their successes.</p>

In this essay I consider the foundations of a particular approach to cognitive science. There is a belief, among some, that cognitive research ought to proceed in two steps. In the first step, cognitive systems ought to be interpreted as rational beings, endowed with knowledge of their environments and motivated by goals and desires. Questions about the modularity of knowledge and about the sort of knowledge that is necessary or sufficient for a given competence are addressed at this stage. In the second step, inferences are to be made about the design of control systems that might instantiate these kinds of knowledge states, goals and rationality. Studies at the knowledge level are meant to serve as guidelines in the search for mechanisms. Problems arise as soon as one asks for the justification of this view. For instance, one often hears that knowledge is attributed by a process of interpretation that is subjective; it depends on the scientist having a 'manual' for interpreting behaviour that has no foundation in fact. Knowledge is essentially observer relative; it designates nothing intrinsic in a system. In Chapter Three I argue that this position is false. By introducing the notion of 'robustness 1 as the touchstone of realism I suggest that knowledge states are potentially as robust as any in science. Moreover realism about knowledge does not entail accepting what Fodor has called the Language of Thought hypothesis. We can reason about knowledge states in abstraction from the various ways knowledge can be implemented in a system. The language of thought is just one of many ways that knowledge can be used by a system. Hence there is no simple way to move from an account of what a system knows to how it uses or has access to that knowledge. In Chapter One I argue that the step from 'knowledge theories' to 'process theories' is more complicated than language of thought theorists suppose. In Chapter Two I discuss the basic methodology of research at the knowledge level. Any well-defined task imposes severe constraints on the way it can be accomplished. The discovery of these constraints and the consequences that flow from them is perhaps the central job of knowledge level research. I conclude the thesis with two chapters on the limitations of knowledge level research. Given that the more structured and rigid a task environment is, the more determinate the knowledge that is necessary or sufficient for task competence, we would expect that tasks and environments which are more open-ended, less closed to intervention from outside interference, would not submit to knowledge level research. Relying on a distinction between peripheral and central cognitive faculties, I question the prospects for knowledge level research of central faculties. Unlike the problem of vision or muscular co-ordination, the problem of deliberation is radically open-ended. Too many factors might become relevant to bound the class of task knowledge that might become vital.

No description available.

Thesis (Ph. D.)--Columbia University. / Vita.

Diss.--Erlangen-Nürnberg. / Bibliography: p. [266]-274.

Thesis (Ph. D.)--Columbia University. / Vita.

Thesis (PH.D.) -- Syracuse University, 2006 / "Publication number AAT 3242509."