The notion of reduction in the natural sciences has been assimilated to the notion of inter-theoretical explanation. Many philosophers of science (following Nagel) have held that the apparently ontological issues involved in reduction should be replaced by analyses of the syntactic and semantic connections involved in explaining one theory on the basis of another. The replacement does not seem to have been especially successful, for we still lack a plausible account of inter-theoretical explanation. I attempt to provide one.

Three recent, influential critiques (Stich 1978; Fodor 1981c; Block 1980) have argued that various tasks on the agenda for computational psychology put conflicting pressures on its theoretical constructs. Unless something is done, the inevitable result will be confusion or outright incoherence. Stich, Fodor, and Block present different versions of this worry and each proposes a different remedy. Stich wants the central notion of belief to be jettisoned if it cannot be shown to be sound. Fodor tries to reduce confusion in computational psychology by dismissing some putative tasks as impossible. Block argues that the widespread faith in functionalism is just not warranted. I argue that all these critiques are misguided because they depend on holding cognitive psychology to taxonomic standards that other sciences routinely rise above.

In this essay I examine a well-known articulation of human nature skepticism, a paper by Hull. I then review a recent reply to Hull by Machery, which argues for an account of human nature that he claims is both useful and scientifically robust. I challenge Machery’s account and introduce an alternative account—the “life-history trait cluster” conception of human nature—that I hold is scientifically sound and makes sense of (at least some of) our intuitions about—and desiderata for—human nature.

The problem of how to make optimal choices in the face of risk (or uncertainty) arises in both economics/decision theory and also evolutionary biology; in the former, ‘optimal’ means utility maximizing, while in the latter it means fitness maximizing. This article explores the links, thematic and formal, between the economic and evolutionary theories of optimal choice in risky situations, with particular reference to the relationship between utility and fitness. It is argued that the link is strongest between evolution and ‘nonexpected’ utility theory, rather than traditional expected utility theory.

On the received view, the Representational Theory of Measurement reduces measurement to the numerical representation of empirical relations. This account of measurement has been widely criticized. In this article, I provide a new interpretation of the Representational Theory of Measurement that sidesteps these debates. I propose to view the Representational Theory of Measurement as a library of theorems that investigate the numerical representability of qualitative relations. Such theorems are useful tools for concept formation that, in turn, is one crucial aspect of measurement for a broad range of cases in linguistics, rational choice, metaphysics, and the social sciences.

This article uses sim-max games to model perceptual categorization with the goal of answering the following question: To what degree should we expect the perceptual categories of biological actors to track properties of the world around them? I argue that an analysis of these games suggests that the relationship between real-world structure and evolved perceptual categories is mediated by successful action in the sense that organisms evolve to categorize together states of nature for which similar actions lead to similar results. This conclusion indicates that both strongly realist and strongly antirealist views about perceptual categories are too simple.

What, if anything, is wrong with typological thinking? The question is important, for some evolutionary developmental biologists appear to espouse a form of typology. I isolate four allegations that have been brought against it. They include the claim that typological thinking is mystical; the claim that typological thinking is at odds with the fact of evolution; the claim that typological thinking is committed to an objectionable metaphysical view, which Elliott Sober calls the ‘natural state model’; and finally the view (endorsed by Ron Amundson and Günter Wagner) that typological thinking—and specifically evolutionary developmental biology's typological thinking—is committed to a peculiar form of causation that does not fit neatly into the causal models endorsed by population genetics. I argue that, properly understood, the typological thinking of evolutionary developmental biology does not run into any of these problems.

The partial structures program of da Costa, French and others offers a unified framework within which to handle a wide range of issues central to contemporary philosophy of science. I argue that the program is inadequately equipped to account for simple cases where idealizations are used to construct abstract, mathematical models of physical systems. These problems show that da Costa and French have not overcome the objections raised by Cartwright and Suárez to using model-theoretic techniques in the philosophy of science. However, my concerns arise independently of the more controversial assumptions that Cartwright and Suárez have employed.

Maher (1988, 1990) has recently argued that the way a hypothesis is generated can affect its confirmation by the available evidence, and that Bayesian confirmation theory can explain this. In particular, he argues that evidence known at the time a theory was proposed does not confirm the theory as much as it would had that evidence been discovered after the theory was proposed. We examine Maher's arguments for this “predictivist” position and conclude that they do not, in fact, support his view. We also cast doubt on the assumptions of Maher's alleged Bayesian proofs.

Protagonists in the so-called Science Wars differ most markedly in their views about the role of values in science and what makes science valuable. Scientists and philosophers of science have traditionally considered the principal aims of science to be explanation and application. Only cognitive values should influence what is taken to be explanatory. Social and political values affect the priority assigned to various scientific problems and the ways in which scientific results are applied. Ethical considerations may be brought to bear on the treatment of human and animal subjects, and the manner in which scientific results are communicated.

Recent critiques of science allege that the content of scientific explanations reflects the dominant ideology and interests of scientists and their patrons. Instead of calling for more value neutrality, some now urge that science take as a principal aim the emancipation of oppressed subcultures. Not only should progressive political values be allowed to set the problems attempted, they also should be used to constrain the types of answers which are pursued. Since scientific knowledge is constructed by us, we should take responsibility for its content.

This paper argues that the project of Emancipationist science is impractical and self-defeating. There is good reason to believe that there would be unresolvable political disputes concerning which kinds of scientific theories are truly emancipiatory. Furthermore, just as placebos cease to work when recognized as such, so would a science known to be constrained by political considerations lose its special epistemic authority.

The Conventionality of Simultaneity espoused by Reichenbach, Grünbaum, Edwards, and Winnie is herein extended to mechanics and electrodynamics. The extension is seen to be a special case of a generally covariant formulation of physics, and therefore consistent with Special Relativity as the geometry of flat space-time. Many of the quantities of classical physics, such as mass, charge density, and force, are found to be synchronization dependent in this formulation and, therefore, in Reichenbach's terminology, “metrogenic.” The relationship of these quantities to 4-vectors and their physical significance is discussed.

Climate change fingerprint studies investigate the causes of recent climate change. I argue that these studies have much in common with Steel's streamlined comparative process tracing, illustrating a mechanisms-based approach to extrapolation in which the mechanisms of interest are simulated rather than physically instantiated. I then explain why robustness and variety-of-evidence considerations turn out to be important for understanding the evidential value of climate change fingerprint studies.

In a recent article, Carlos Santana shows that in common interest signaling games when signals are costly and when receivers can observe contextual environmental cues, ambiguous signaling strategies outperform precise ones and can, as a result, evolve. I show that if one assumes a realistic structure on the state space of a common interest signaling game, ambiguous strategies can be explained without appeal to contextual cues. I conclude by arguing that there are multiple types of cases of payoff-beneficial ambiguity, some of which are better explained by Santana’s models and some of which are better explained by models presented here.

Gödel began to seriously study Husserl's phenomenology in 1959, and the Gödel Nachlass is known to contain many notes on Husserl. In this paper I describe what is presently known about Gödel's interest in phenomenology. Among other things, it appears that the 1963 supplement to “What is Cantor's Continuum Hypothesis?”, which contains Gödel's famous views on mathematical intuition, may have been influenced by Husserl. I then show how Gödel's views on mathematical intuition and objectivity can be readily interpreted in a phenomenological theory of intuition and mathematical knowledge.

Many explanations in physics rely on idealized models of physical systems. These explanations fail to satisfy the conditions of standard accounts of explanation. Recently, some philosophers have claimed that idealizations can be used to underwrite explanation nonetheless but only when they are what have variously been called representational, Galilean, controllable, or harmless idealizations. This article argues that such a half-measure is untenable and that idealizations not of this sort can have explanatory capacities.

We show there is only one consistent way to update a probability assignment, that given by Bayes's rule. The price of inconsistent updating is a loss of efficiency. The implications of this for the problem of induction are discussed.

In attempting to clarify the problem of personality integration the writer gained the impression that the difficulty of such a task does does not lie alone in the paucity of usable factual data but it is due, even to a greater extent, to the inadequacy of our logical tools. Such a handicap is felt not only in the study of personality, but in the study of wholes in general. Here the attempt will be made to develop some concepts which may be useful for the understanding of the structure of wholes.

This paper explains the metaphysical implications of the view that species are individuals (SAI). I first clarify SAI in light of the separate distinctions between individuals and classes, particulars and universals, and abstract and concrete things. I then show why the standard arguments given in defense of SAI are not compelling. Nonetheless, the ontological status of species is linked to the traditional “species problem,” in that certain species concepts do entail that species are individuals. I develop the idea that species names are rigid designators and show how this provides additional motivation for SAI.

Psychologists say a measure has construct validity when it, in fact, measures the construct it is intended to measure. Construct validity is both an important notion in psychological research methods and the source of much confusion and debate among psychologists. I argue that this confusion arises, in part, because of a failure to distinguish between construct validity, a feature of measures relative to a construct, and construct legitimacy, a feature of the construct itself. I propose a prescriptive account of construct validity on the basis of this distinction, then provide evidence for my account through two examples from research psychology.

Leuridan argued that mechanisms cannot provide a genuine alternative to laws of nature as a model of explanation in the sciences, and he advocates Mitchell's pragmatic account of laws. I first demonstrate that Leuridan gets the order of priority wrong among mechanisms, regularity, and laws, and then make some clarifying remarks about how laws and mechanisms relate to regularities. Mechanisms are not an explanatory alternative to regularities; they are an alternative to laws. The existence of stable regularities in nature is necessary for either model of explanation: regularities are what laws describe and what mechanisms explain.