While the question of whether selected-effects accounts of function or causal-role accounts of function provide the ‘true’ functional analysis has given way to a general pluralistic consensus, Philip Kitcher has suggested that different functional accounts allow for unification. I argue that Kitcher's attempt to unify the two functional analyses fails because he adopts the environment-centered perspective on selection as a premise. The premise is undermined by the role niche construction is likely to play in the context of evolution. Moreover, I raise the tentative suggestion that niche construction may threaten the applicability, or at least the relevance, of selected-effects ascriptions.

This essay criticizes John Norton's 2010 defense of the thesis that “all induction is local.” Norton's local inductions are bound, if cogent, to involve general principles, and the need to accredit these general principles threatens to lead to all the usual problems associated with the ‘problem of induction’. Norton, in fact, recognizes this threat, but his responses are inadequate. The right response involves not induction but a sophisticated version of hypothetico-deduction. Norton's secondary thesis—that if there is a general account of cogent scientific reasoning, then it is certainly not the one supported by personalist Bayesians—is also criticized.

Does Hume's skeptical critique of inductive reasoning depend for its force on the assumption that such reasoning is a matter of following general rules? I explore this question in connection with John Norton's “Material Theory of Induction.”

In a material theory of induction, inductive inferences are warranted by facts that prevail locally. This approach, it is urged, is preferable to formal theories of induction in which the good inductive inferences are delineated as those conforming to universal schemas. An inductive inference problem concerning indeterministic, nonprobabilistic systems in physics is posed, and it is argued that Bayesians cannot responsibly analyze it, thereby demonstrating that the probability calculus is not the universal logic of induction.

This essay uses Györgi Buzsáki's use of EEG data to draw conclusions about brain function as an example to show that investigators sometimes draw conclusions from noisy data by analyzing the noise rather than by extracting a signal from it. The example makes vivid some important differences between McAllister's, Woodward's, and my ideas about how data are interpreted.

This essay attempts to provide additional motivation for the data/phenomena framework advocated in Bogen and Woodward, “Saving the Phenomena” (1988).

This article defends the following claims. First, for patterns exhibited in empirical data, there is no criterion on which to demarcate patterns that are physically significant and patterns that are not physically significant. I call a pattern physically significant if it corresponds to a structure in the world. Second, all patterns must be regarded as physically significant. Third, distinct patterns must be regarded as providing evidence for distinct structures in the world. Fourth, in consequence, the world must be conceived as showing all possible structures.

Bogen and Woodward argued the indirect connection between data and theory in terms of their conception of “phenomena.” I outline and elaborate on their presentation. To illuminate the connection with contemporary thinking in terms of models, I distinguish between phenomena tokens, representations of which can be identified with data models, and phenomena types that can be identified with relatively low-lying models or aspects of models in the model hierarchy. Throughout I stress the role of idealization in these considerations.

Taking Bogen and Woodward's discussion of data and phenomena as his starting point, McAllister presents a challenge to scientific realism. I discuss this challenge and offer a suggestion for how the scientific realist could respond to both its epistemic and ontological aspects. In so doing, I urge that the scientific realist should not reject ontological pluralism from the start, but should seek to explore versions of scientific realism that leave open the possibility of certain kinds of pluralist ontology. I investigate the available options (in terms of foundationalism, reductionism, and universalism) and use a law-constitutive approach to offer a strategy for the scientific realist who is open-minded about ontological pluralism.

What are the relative epistemic merits of building prosthetic models versus building nonprosthetic models and simulations? I argue that prosthetic models provide a sufficient test of affordance validity, that is, of whether the target system affords mechanisms that can be commandeered by a prosthesis. In other respects, prosthetic models are epistemically on par with nonprosthetic models. I focus on prosthetics in neuroscience, but the results are general. The goal of understanding how brain mechanisms work under ecologically and physiologically relevant conditions is narrow compared to the search for maker's knowledge about how the brain can be made to work for us.

Computationalism—the view that cognition is computation—has always been controversial. It faces two types of objection. According to insufficiency objections, computation is insufficient for some cognitive phenomenon X. According to objections from neural realization, cognitive processes are realized by neural processes, but neural processes have feature Y, and having Y is incompatible with being (or realizing) computations. In this article, I explain why computationalism has survived these objections. To adjudicate the dispute between computationalism and its foes, I will conclude that we need a better account of computation.

What does it mean to say that a physical system computes or, specifically, to say that the nervous system computes? One answer, endorsed here, is that computing is a sort of modeling. I trace this line of answer in the conceptual and philosophical work conducted over the last 3 decades by researchers associated with the University of California, San Diego (UCSD). The linkage between their work and the modeling notion is no coincidence: the modeling notion aims to account for the computational approach in neuroscience, and UCSD has been home to central studies in neurophilosophy, connectionism, and computational neuroscience.

What role does the concept of representation play in the contexts of experimentation and explanation in cognitive neurobiology? In this article, a distinction is drawn between minimal and substantive roles for representation. It is argued by appeal to a case study that representation currently plays a role in cognitive neurobiology somewhere in between minimal and substantive and that this is problematic given the ultimate explanatory goals of cognitive neurobiological research. It is suggested that what is needed is for representation to instead play a substantive role.

This essay focuses on the place of the second law of thermodynamics in Wilhelm Ostwald's physical chemistry. After a brief introduction to his energetic theory, which was supposed to be a generalization of thermodynamics, I contrast Ostwald's understanding of the second law, which ignored entropy and irreversibility, with Max Planck's, which emphasized both. I then consider how Ostwald sought to develop physical chemistry without any concern for irreversibility and little concern for entropy, and I argue that he was mistaken.

Gibbs's phase rule treats mixtures by relating the number of independent variables governing their state to the numbers of phases and independent substances. For the case of a single substance, it provides a criterion of purity. But where more substances are involved, the notion of independent substance is less readily understood. Textbook writers sometimes use algebraic terminology in ways that are suggestive but cannot be taken as literally accurate. I suggest that a mereological interpretation applies to these cases, as it captures more concisely the insights underlying the use of algebraic terminology and illuminates the general notion of substance.

Varieties of chemical and phase equilibria are controlled by the minimum Gibbs energy principle, according to which the Gibbs energy for a system will have the minimum value at any given temperature and pressure. It is understood that the minimum is with respect to all nonequilibrium states at the same temperature and pressure. The abstract relation between Gibbs energy and the equilibrium constant is deduced from fundamental laws of thermodynamics. However, actual use of this relation calls for the Gibbs energy as a function of concentrations of the chemicals. Since thermodynamics is formulated without any reference to materials, how does one get that relation? This article provides the answer, and in the process shows that application of theory to experiments requires several intermediate layers where theory and experiment commingle.

In this essay I critically examine the role of entropy of mixing in articulating a macroscopic criterion for the sameness and difference of chemical substances. Consider three cases of mixing in which entropy change occurs: isotopic variants, spin isomers, and populations of atoms in different orthogonal quantum states. Using these cases I argue that entropy of mixing tracks differences between physical states, differences that may or may not correspond to a difference of substance. It does not provide a criterion for the sameness and difference of substance that is appropriate to chemistry.

Explanations in physics commonly appeal to data drawn from different length or time scales, as when a “top-down” macroscopic constraint such as rigidity is used to evade the complexities one would confront in attempting to model the situation in a purely “bottom-up” fashion. Such techniques commonly embody rather complex shifts in explanatory strategy.

In this paper, I discuss the prospects of nominalistic scientific realism (NSR) and show that it fails on many counts. In section 2, I discuss what is required for NSR to get off the ground. In section 3, I question the idea that theories have well-defined nominalistic content and the idea that causal activity is a necessary condition for commitment to the reality of an entity. In section 4, I challenge the notion of nominalistic adequacy of theories.