Despite some recent advances, multiple realization remains a largely misunderstood thesis. Consider the dispute between Lawrence Shapiro and Carl Gillett over the application of Shapiro's recipe for deciding when we have genuine cases of multiple realization. I argue that Gillett follows many philosophers in mistakenly supposing that multiple realization is absolute and transitive. Both of these are problematic. They are tempting only when we extract the question of multiple realization from the explanatory context in which it is invoked. Anchoring multiple realizability in its theoretical context provides grounds for arbitrating disagreements. Doing so, I argue, favors the view advanced by Shapiro.

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.

The so-called problem of irrelevant conjunction has been seen as a serious challenge for theories of confirmation. It involves the consequences of conjoining irrelevant statements to a hypothesis that is confirmed by some piece of evidence. Following Hawthorne and Fitelson, we reconstruct the problem with reference to Bayesian confirmation theory. Then we extend it to the case of conjoining irrelevant statements to a hypothesis that is disconfirmed by some piece of evidence. As a consequence, we obtain and formally present a novel and more troublesome problem of irrelevant conjunction. We conclude by indicating a possible solution based on a measure-sensitive approach and by critically discussing a major alternative way to address the problem.

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.

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.

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 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.

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.

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.

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.

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.

Model-data symbiosis is the view that there is an interdependent and mutually beneficial relationship between data and models, whereby models are data-laden and data are model-laden. In this article I elaborate and defend the second, more controversial, component of the symbiosis view and construct a taxonomy of the different ways in which theoretical and simulation models are used in the production of data sets. Each is defined and briefly illustrated with an example from the geosciences. I argue that model-filtered data are typically more accurate and reliable than so-called raw data and, hence, beneficially serve the epistemic aims of science.

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.

In this discussion note, we explain how to relax some of the standard assumptions made in Garber-style solutions to the Problem of Old Evidence. The result is a more general and explanatory Bayesian approach.

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.

Ecologists typically invoke “law-like” generalizations, ranging over “structural” and/or “functional” kinds, in order to explain generalizations about “historical” kinds (such as biological taxa)—rather than vice versa. This practice is justified, since structural and functional kinds tend to correlate better with important ecological phenomena than do historical kinds. I support these contentions with three recent case studies. In one sense, therefore, ecology is, and should be, more nomothetic, or law-oriented, than idiographic, or historically oriented. This conclusion challenges several recent philosophical claims about the nature of ecological science.

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.

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.

The Cold Dark Matter model faces many controversies at small scales, as simulations fail to reproduce the observed properties of dark matter (DM) halos. Since rival DM models differ on their predictions about the structure of DM halos, understanding their mass distribution is crucial for determining the nature of DM. However, only numerical approaches to determining what a hypothesis implies for the mass distribution are possible. Hence, simulations are a crucial part of evaluating DM rival models, as is assessing their reliability. I argue that robustness analysis is not a sufficient criterion for the trustworthiness of cosmological simulations.

Typically, the imagination in thought experiments has been taken to consist in mental images; we visualize the state of affairs described. A recent alternative from Fiora Salis and Roman Frigg maintains that it is only the propositional imagination that is necessary for the conduct of a thought experiment. I set out problems with these monistic accounts and develop a pluralist stance. Thought experiments appeal to a variety of our imaginative capacities, and we ought to focus on the function of particular thought experiments when considering what type of imaginative engagement they invite.