There are at least twelve major virtues of good theories: evidential accuracy, causal adequacy, explanatory depth, internal consistency, internal coherence, universal coherence, beauty, simplicity, unification, durability, fruitfulness, and applicability. These virtues are best classified into four classes: evidential, coherential, aesthetic, and diachronic. Each virtue class contains at least three virtues that sequentially follow a repeating pattern of progressive disclosure and expansion. Systematizing the theoretical virtues in this manner clarifies each virtue and suggests how they might have a coordinated and cumulative (...) role in theory formation and evaluation across the disciplines—with allowance for discipline specific modification. An informal and flexible logic of theory choice is in the making here. Evidential accuracy, according to my systematization, is not a largely isolated trait of good theories, as some have made it out to be. Rather, it bears multifaceted relationships, constituting significant epistemic entanglements, with other theoretical virtues. (shrink)

Eliminative materialism is the thesis that our common-sense conception of psychological phenomena constitutes a radically false theory, a theory so fundamentally defective that both the principles and the ontology of that theory will eventually be displaced, rather than smoothly reduced, by completed neuroscience. Our mutual understanding and even our introspection may then be reconstituted within the conceptual framework of completed neuroscience, a theory we may expect to be more powerful by far than the common-sense psychology it displaces, and more substantially (...) integrated within physical science generally. My purpose in this paper is to explore these projections, especially as they bear on (1) the principal elements of common-sense psychology: the propositional attitudes (beliefs, desires, etc.), and (2) the conception of rationality in which these elements figure. (shrink)

With twentieth- and twenty-first-century philosophy of science’s unfolding acceptance of the nature of scientific inquiry being value-laden, the persistent worry has been that there are no means for legitimate negotiation of the social or non-epistemic values that enter into science. The rejection of the value-free ideal in science has thereby been coupled with the spectres of indiscriminate relativism and bias in scientific inquiry. I challenge this view in the context of recently expressed concerns regarding Canada's death of evidence controversy. The (...) worry, raised by Stathis Psillos, is that as constructivist accounts of science demoted the previously secure status of evidence for drawing justified conclusions in science, we were left with no rational delineation between the right and wrong values for science. The implication for the death of evidence controversy is that we may have no rational grounds for claiming that the Canadian Government is wrong to interfere with scientific enterprise. But he does offer another avenue for reaching the conclusion that the wrong social values are directing the current stifling of some sectors of Canadian science. Psillos draws from standpoint epistemologies to devise a salient defence of ‘valuing evidence’ as a universalizable social value. That is, government bodies ought to enable scientific research via adequate funding as well as political non-interference. In this paper, I counter that non-epistemic values can be rationally evaluated and that standpoint epistemology’s universalizable standpoint provides an inadequate framework for negotiating social values in science. Regarding, I draw from the evidence-based medicine debate in philosophy of medicine and from feminist empiricist investigations into the science–values relationship in order to make the argument for empirically driven value arbitration. If social values can be rationally chosen in the context of justification, then we can have grounds for charging the Canadian leadership with being ‘at war with science’. I further argue that my recommended empiricist methodology is preferable to Psillos’s search for universalizable perspectives for negotiating social values in science because the latter method permits little more than the trivial conclusion that evidence is valuable to science. (shrink)

This paper is meant to link the philosophical debate concerning the underdetermination of theories by evidence with a rather significant socio-political issue that has been taking place in Canada over the past few years: the so-called ‘death of evidence’ controversy. It places this debate within a broader philosophical framework by discussing the connection between evidence and theory; by bringing out the role of epistemic values in the so-called scientific method; and by examining the role of social values in science. While (...) it should be admitted that social values play an important role in science, the key question for anyone who advocates this view is: what and whose values? The way it is answered makes an important epistemic difference to how the relation between evidence and theory is appraised. I first review various arguments for the claim that evidence underdetermines theory and shows their presuppositions and limitations, using conceptual analysis and historical examples. After broaching the relation between evidence and method in science by highlighting the need to incorporate epistemic values into the scientific method, my discussion focuses on recent arguments for the role of social values in science. Finally, I address the implications of the approach outlined for the current ‘death of evidence’ debate in Canada. (shrink)

In various contexts and for various reasons, writers often define cognitive processes and architectures as those involving representational states and structures. Similarly, cognitive theories are also often delineated as those that invoke representations. In this paper, I present several reasons for rejecting this way of demarcating the cognitive. Some of the reasons against defining cognition in representational terms are that doing so needlessly restricts our theorizing, it undermines the empirical status of the representational theory of mind, and it encourages wildly (...) deflationary and explanatorily vacuous conceptions of representation. After criticizing this outlook, I sketch alternative ways we might try to capture what is distinctive about cognition and cognitive theorizing. (shrink)

Young children’s failures in reasoning about beliefs and desires, and especially about false beliefs, have been much studied. However, there are few accounts of successful belief-desire reasoning in older children or adults. An exception to this is a model in which belief attribution is treated as a process wherein an inhibitory system selects the most likely content for the belief to be attributed from amongst several competing contents [Leslie, A. M., & Polizzi, P. (1998). Developmental Science, 1, 247–254]. We tested (...) this model with an ‘avoidance false belief task’ in which subjects predict the behavior of a character, who wants to avoid an object but who is mistaken about which of three locations it is in. The task has two equally correct answers—in seeking to avoid the location where she mistakenly believes the object to be, the character might equally go to the location where the object actually is, or to the remaining empty location. However, the model predicts that subjects will prefer one of these answers, selecting the object’s actual location over the empty location. This bias was confirmed in a series of five experiments with children aged between 4 and 8 years of age. A sixth experiment ruled out two rival explanations for children’s biased responding. Two further experiments found the opposite bias in adults. These findings support one selection model as an account of belief-desire reasoning in children, and suggest that a different model is needed for adults. The process of selecting contents for mental state attributions shows a developmental shift between 8 years of age and adulthood. (shrink)

We argue that dynamical and mathematical models in systems and cognitive neuro- science explain (rather than redescribe) a phenomenon only if there is a plausible mapping between elements in the model and elements in the mechanism for the phe- nomenon. We demonstrate how this model-to-mechanism-mapping constraint, when satisfied, endows a model with explanatory force with respect to the phenomenon to be explained. Several paradigmatic models including the Haken-Kelso-Bunz model of bimanual coordination and the difference-of-Gaussians model of visual receptive fields are (...) explored. (shrink)

We sketch a framework for building a unified science of cognition. This unification is achieved by showing how functional analyses of cognitive capacities can be integrated with the multilevel mechanistic explanations of neural systems. The core idea is that functional analyses are sketches of mechanisms , in which some structural aspects of a mechanistic explanation are omitted. Once the missing aspects are filled in, a functional analysis turns into a full-blown mechanistic explanation. By this process, functional analyses are seamlessly integrated (...) with multilevel mechanistic explanations. (shrink)

Suppose now that two philosophers, McX and I, differ over ontology. Suppose McX maintains there is something which I maintain there is not. McX can, quite consistently with his own point of view, describe our difference of opinion by saying that I refuse to recognize certain entities. I should protest of course that he is wrong in his formulation of our disagreement, for I maintain that there are no entities, of the kind which he alleges, for me to recognize; but (...) my finding him wrong in his formulation of our disagreement is unimportant, for I am committed to considering him wrong in his ontology anyway. When I try to formulate our difference of opinion, on the other hand, I seem to be in a predicament. I cannot admit that there are some things which McX countenances and I do not, for in admitting that there are such things I should be contradicting my own rejection of them. (shrink)

By a `denoting phrase' I mean a phrase such as any one of the following: a man, some man, any man, every man, all men, the present King of England, the present King of France, the center of mass of the solar system at the first instant of the twentieth century, the revolution of the earth round the sun, the revolution of the sun round the earth. Thus a phrase is denoting solely in virtue of its form. We may distinguish (...) three cases: (1) A phrase may be denoting, and yet not denote anything; e.g., `the present King of France'. (2) A phrase may denote one definite object; e.g., `the present King of England' denotes a certain man. (3) A phrase may denote ambiguously; e.g. `a man' denotes not many men, but an ambiguous man. The interpretation of such phrases is a matter of considerably difficulty; indeed, it is very hard to frame any theory not susceptible of formal refutation. All the difficulties with which I am acquainted are met, so far as I can discover, by the theory which I am about to explain. (shrink)

I argue against the tendency in the philosophy of science literature to link abduction to the inference to the best explanation (IBE), and in particular, to claim that Peireean abduction is a conceptual predecessor to IBE. This is not to discount either abduction or IBE. Rather the purpose of this paper is to clarify the relation between Peireean abduction and IBE in accounting for ampliative inference in science. This paper aims at a proper classification—not justification—of types of scientific reasoning. In (...) particular, I claim that Peireean abduction is an in-depth account of the process of generating explanatory hypotheses, while IBE, at least in Peter Lipton's thorough treatment, is a more encompassing account of the processes both of generating and of evaluating scientific hypotheses. There is then a two-fold problem with the claim that abduction is IBE. On the one hand, it conflates abduction and induction, which are two distinct forms of logical inference, with two distinct aims, as shown by Charles S. Peirce; on the other hand it lacks a clear sense of the full scope of IBE as an account of scientific inference. (shrink)

Some philosophers argue that we should eschew cross-explanatory integrations of mechanistic, dynamicist, and psychological explanations in cognitive science, because, unlike integrations of mechanistic explanations, they do not deliver genuine, cognitive scientific explanations. Here I challenge this claim by comparing the theoretical virtues of both kinds of explanatory integrations. I first identify two theoretical virtues of integrations of mechanistic explanations—unification and greater qualitative parsimony—and argue that no cross-explanatory integration could have such virtues. However, I go on to argue that this is (...) only a problem for those who think that cognitive science aims to specify one fundamental structure responsible for cognition. For those who do not, cross-explanatory integration will have at least two theoretical virtues to a greater extent than integrations of mechanistic explanations: explanatory depth and applicability. I conclude that one’s views about explanatory integration in cognitive science cannot be segregated from one’s views about the explanatory task of cognitive science. (shrink)

Recent work on inference to the best explanation has come to an impasse regarding the proper way to coordinate the theoretical virtues in explanatory inference with probabilistic confirmation theory, and in particular with aspects of Bayes's Theorem. I argue that the theoretical virtues are best conceived heuristically and that such a conception gives us the resources to explicate the virtues in terms of ceteris paribus theorems. Contrary to some Bayesians, this is not equivalent to identifying the virtues with likelihoods or (...) priors per se; the virtues may be more accessible epistemically than likelihoods or priors. I then prove a ceteris paribus theorem regarding theoretical consilience, use it to correct a recent application of Reichenbach's common cause principle, and apply it to a test case of scientific reasoning. Explanation and confirmation The heuristic conception of theoretical virtues Abduction and the accessibility of explanatory power Evidential and theoretical consilience A test case: gravitational lensing Conclusion Thus natural science appears completely to lose from sight the large and general questions; but all the more splendid is the success when, groping in the thicket of special questions, we suddenly find a small opening that allows a hitherto undreamt of outlook on the whole. (L. Boltzmann, Theoretical Physics and Philosophical Problems). (shrink)

I argue that so-called 'background knowledge' in confirmation theory has little, if anything, to do with 'knowledge' in the sense of mainstream epistemology. I argue that it is better construed as 'background information', which need not be believed in, justified, or true.

According to Williamson, your evidence consists of all and only what you know (E = K). According to his critics, it doesn’t. While E = K calls for revision, the revisions it calls for are minor. E = K gets this much right. Only true propositions can constitute evidence and anything you know non-inferentially is part of your evidence. In this paper, I defend these two theses about evidence and its possession from Williamson’s critics who think we should break more (...) radically from E = K. (shrink)

The “top-down” and “bottom-up” approaches have been thought to exhaust the possibilities for doing cognitive neuroscience. We argue that neither approach is likely to succeed in providing a theory that enables us to understand how cognition is achieved in biological creatures like ourselves. We consider a promising third way of doing cognitive neuroscience, what might be called the “neural dynamic systems” approach, that construes cognitive neuroscience as an autonomous explanatory endeavor, aiming to characterize in its own terms the states and (...) processes responsible for brain-based cognition. We sketch the basic motivation for the approach, describe a particular version of the approach, so-called ‘Dynamic Causal Modeling’ (DCM), and consider a concrete example of DCM. This third way, we argue, has the potential to avoid the problems that afflict the other two approaches. (shrink)

I present an argument that encapsulates the view that theory is underdetermined by evidence. I show that if we accept Williamson's equation of evidence and knowledge, then this argument is question-begging. I examine ways of defenders of underdetermination may avoid this criticism. I also relate this argument and my critique to van Fraassen's constructive empiricism.

We provide a taxonomy of the two most important debates in the philosophy of the cognitive and neural sciences. The first debate is over methodological individualism: is the object of the cognitive and neural sciences the brain, the whole animal, or the animal--environment system? The second is over explanatory style: should explanation in cognitive and neural science be reductionist-mechanistic, inter-level mechanistic, or dynamical? After setting out the debates, we discuss the ways in which they are interconnected. Finally, we make some (...) recommendations that we hope will help philosophers interested in the cognitive and neural sciences to avoid dead ends. (shrink)

A normative Bayesian theory of deliberation and judgement requires a procedure for merging the evidence of a collection of agents. In order to provide such a procedure, one needs to ask what the evidence is that grounds Bayesian probabilities. After finding fault with several views on the nature of evidence (the views that evidence is knowledge; that evidence is whatever is fully believed; that evidence is observationally set credence; that evidence is information), it is argued that evidence is whatever is (...) rationally taken for granted. This view is shown to have consequences for an account of merging evidence, and it is argued that standard axioms for merging need to be altered somewhat. (shrink)

Van Fraassen (1989) argues that Inference to the Best Explanation is incoherent in the sense that adopting it as a rule for belief change will make one susceptible to a dynamic Dutch book. The present paper argues against this. A strategy is described that allows us to infer to the best explanation free of charge.

Machery and Weiskopf argue that the kind concept is a natural kind if and only if it plays an explanatory role in cognitive scientific explanations. In this paper, we argue against this explanationist approach to determining the natural kind-hood of concept. We first demonstrate that hybrid, pluralist, and eliminativist theories of concepts afford the kind concept different explanatory roles. Then, we argue that we cannot decide between hybrid, pluralist, and eliminativist theories of concepts, because each endorses a different, but equally (...) viable, specification of the explananda of cognitive science. It follows that an explanationist approach to determining the natural kind-hood of concept fails, because there is no consensus about whether or not concept should be afforded an explanatory role in our best cognitive scientific explanations. We conclude by considering what our critique of explanationism could imply for further discussions about the explanatory role of concepts in cognitive science. (shrink)