A correct analysis of hierarchical selection processes must specify 1) the objects that succeed differentially as units, and 2) the properties that provide the causal bases for differential success. Here I illustrate how failing to recognize the units/bases distinction creates a contradiction in Elliott Sober's recent account of selection. A revised criterion for units of selection is developed and applied to examples at several biological levels. Criteria for bases of selection are discussed in terms of the degree of context-dependence and directness of a property's effect on the success of units. The significance of previous work by Sober, Wimsatt and Brandon is thereby clarified.

In “Realism and Reason” Hilary Putnam has offered an apparently strong argument that the position of metaphysical realism provides an incoherent model of the relation of a correct scientific theory to the world. However, although Putnam's attack upon the notion of the “intended” interpretation of a scientific theory is sound, it is shown here that realism may be formulated in such a way that the realist need make no appeal to any “intended” interpretation of such a theory. Consequently, it can be shown that realism is immune to Putnam's criticism and that attempts at reformulating this criticism are not likely to meet with success.

Ethological theory standardly attributes representational content to animal signals. In this article I first assess whether Ruth Millikan's teleosemantic theory accounts for the content of animal signals. I conclude that it does not, because many signals do not exhibit the required sort of cooperation between signal-producing and signal-consuming devices. It is then argued that Kim Sterelny's proposal, while not requiring cooperation, sometimes yields the wrong content. Finally, I outline an alternative view, according to which consumers alone are responsible for conferring representational status and determining content. I suggest that consumer-based teleosemantics reconstruct the content of both cooperative and noncooperative signals and explain how a given trait can mean different things to different consumers.

Hierarchical Bayesian models (HBMs) provide an account of Bayesian inference in a hierarchically structured hypothesis space. Scientific theories are plausibly regarded as organized into hierarchies in many cases, with higher levels sometimes called ‘paradigms’ and lower levels encoding more specific or concrete hypotheses. Therefore, HBMs provide a useful model for scientific theory change, showing how higher-level theory change may be driven by the impact of evidence on lower levels. HBMs capture features described in the Kuhnian tradition, particularly the idea that higher-level theories guide learning at lower levels. In addition, they help resolve certain issues for Bayesians, such as scientific preference for simplicity and the problem of new theories.

Throughout this century many philosophers and physicists have gone for the ‘big kill’ regarding tenses. They have tried to show via McTaggart's paradox and special relativity that tenses are logically and physically impossible, respectively. Neither attempt succeeds, though as I argue, both leave their mark. In the first two sections of the paper I introduce some conceptual difficulties for the tensed theory of time. The next section then discusses the standing of tenses in light of special relativity, especially recent work by Stein on the topic. I argue that, Stein's possibility theorem notwithstanding, special relativity is inconsistent with any philosophically interesting conception of tense. Finally, I search for help for tenses in the broader context of quantum theory, Lorentzian interpretations of time dilation/length contraction, and general relativistic spacetimes. I suggest that these avenues do not provide tenses the home for which some have hoped.

Hodgkin and Huxley's model of the action potential is an apparent dream case of covering-law explanation in biology. The model includes laws of physics and chemistry that, coupled with details about antecedent and background conditions, can be used to derive features of the action potential. Hodgkin and Huxley insist that their model is not an explanation. This suggests either that subsuming a phenomenon under physical laws is insufficient to explain it or that Hodgkin and Huxley were wrong. I defend Hodgkin and Huxley against Weber's heteronomy thesis and argue that explanations are descriptions of mechanisms.

Mark Hinchliff concludes a recent paper, “The Puzzle of Change,” with a section entitled “Is the Presentist Refuted by the Special Theory of Relativity?” His answer is “no.”

I respond by arguing that presentists face great difficulties in merely stating their position in Minkowski spacetime. I round up some likely candidates for the job and exhibit their deficiencies.

Recent discussions in the physical literature, designed to clarify the logical position of modern physical theory, have brought to light an amazing divergence of fundamental attitudes which may well bewilder the careful student of physics as well as philosophy. Quantum mechanics, representing an abstract formalism, should be capable of having its logical structure analyzed with great precision like any other mathematical discipline. Its consequences in all problems to which its method can be applied are so unambiguous, consistent, and successful in predicting physical experience as to disperse immediately all thoughts of possible discrepancies in its fundamental texture. Yet it must be said that even the founders of quantum theory are not in harmony in their various expositions of the bases of that theory. However, while this situation seems disquieting on the face of it, there is no cause for serious brow raising, for it is a fact that there exists agreement with regard to the central axioms of the theory, and that the ambiguities affect only their philosophical interpretation, a field in which differences of opinion may at present be honestly entertained.

Two approaches to evidential reasoning compete in the biomedical and social sciences: the experimental and the pragmatist. Whereas experimentalism has received considerable philosophical analysis and support since the times of Bacon and Mill (and continues to enjoy attention and support in very recent work on causation and evidence), pragmatism about evidence has been neither articulated nor defended. The overall aim is to fill this gap and develop a theory that articulates the latter. The main ideas of the theory will be illustrated and supported by a case study on the smoking/lung cancer controversy in the 1950s.

Gödel's conclusion that time-travel is possible in his models of Einstein's gravitational theory has been questioned by Chandrasekhar and Wright, and treated as doubtful in the recent philosophical literature. The present note is intended to remove this doubt: a review of Gödel's construction shows that his arguments are entirely correct; and the objection is seen to rest upon a misunderstanding. Computational points treated succinctly by Gödel are here presented in fuller detail. The philosophical significance of Gödel's results is briefly considered, and a set of technical questions is posed whose answers would clarify this significance.

This paper takes a critical look at the idea that evolutionary theory is a statistical theory. It argues that despite the strong instrumental motivation for statistical theories, they are not necessary to explain deterministic systems. Biological evolution is fundamentally a result of deterministic processes. Hence, a statistical theory is not necessary for describing the evolutionary forces of genetic drift and natural selection, nor is it needed for describing the fitness of organisms. There is a computational advantage to the statistical theory of population genetics, but population genetics succeeds only by eliminating causes from its account of evolutionary change.

We discuss the probabilistic analysis of explanatory power and prove a representation theorem for posterior ratio measures recently advocated by Schupbach and Sprenger. We then prove a representation theorem for an alternative class of measures that rely on the notion of relative probability distance. We end up endorsing the latter, as relative distance measures share the properties of posterior ratio measures that are genuinely appealing, while overcoming a feature that we consider undesirable. They also yield a telling result concerning formal accounts of explanatory power versus inductive confirmation, thereby bridging our discussion to a so-called no-miracle argument.

This article discusses the dual interpretation of the Jeffreys-Lindley paradox associated with Bayesian posterior probabilities and Bayes factors, both as a differentiation between frequentist and Bayesian statistics and as a pointer to the difficulty of using improper priors while testing. I stress the considerable impact of this paradox on the foundations of both classical and Bayesian statistics. While assessing existing resolutions of the paradox, I focus on a critical viewpoint of the paradox discussed by Spanos in Philosophy of Science.

I show that the recent account of levels in neuroscience proposed by Craver and Bechtel is unsatisfactory since it fails to provide a plausible criterion for being at the same level and is incompatible with Craver and Bechtel’s account of downward causation. Furthermore, I argue that no distinct notion of levels is needed for analyzing explanations and causal issues in neuroscience: it is better to rely on more well-defined notions such as composition and scale. One outcome of this is that apparent cases of downward causation can be analyzed away.

When conceived as an empirical claim, it is natural to wonder how one might test the hypothesis of multiple realization. I consider general issues of testability, show how they apply specifically to the hypothesis of multiple realization, and propose an auxiliary assumption that, I argue, must be conjoined to the hypothesis of multiple realization to ensure its testability. I argue further that Bechtel and Mundale (1999) go astray because they fail to appreciate the need for this auxiliary assumption.

I respond to H. M. Collins's claim (1985, 1990, 1993) that experimental inquiry cannot be objective because the only criterium experimentalists have for determining whether a technique is “working” is the production of “correct” (i.e., the expected) data. Collins claims that the “experimenters' regress,” the name he gives to this data-technique circle, cannot be broken using the resources of experiment alone. I argue that the data-technique circle, can be broken even though any interpretation of the raw data produced by techniques is theory-dependent. However, it is possible to break this circle by eliminating dependence on even those theoretical presuppositions that are shared by an entire scientific community through the use of multiple independently theory-dependent techniques to produce robust bodies of data. Moreover, I argue, that it is the production of robust bodies of data that convinces experimentalists of the objectivity of their data interpretations.

In both axiomatic theories and the practice of extensive measurement, it is assumed that a series of replicas of any given object can be found. The replicas give rise to a standard series, the “multiples” of the given object. The numerical value assigned to any object is determined, approximately, by comparisons with members of a suitable standard series.

This prescription introduces unspecified errors, if the comparison process is somewhat insensitive, so that “replicas” are not really equivalent. In this paper, it is assumed that the comparison process leads only to a semiorder, which allows for such insensitivity. It is shown that, nevertheless, extensive measurement can be carried out, provided that a certain set of (plausible) axioms is valid. Approximate measures, and their limits of error, can be derived from finite sets of semiorder observations. These approximate measures converge to ratio-scale exact measurement.

A common argument against explanatory reductionism is that higher-level explanations are sometimes or always preferable because they are more general than reductive explanations. Here I challenge two basic assumptions that are needed for that argument to succeed. It cannot be assumed that higher-level explanations are more general than their lower-level alternatives or that higher-level explanations are general in the right way to be explanatory. I suggest a novel form of pluralism regarding levels of explanation, according to which explanations at different levels are preferable in different circumstances because they offer different types of generality, which are appropriate in different circumstances of explanation.

This essay advocates a “functional” approach to causation and causal reasoning: these are to be understood in terms of the goals and purposes of causal thinking. This approach is distinguished from accounts based on metaphysical considerations or on reconstruction of “intuitions.”

Contemporary scientific theories assume a primarily micro-deterministic view of nature. This paper explores the question of whether micro-determinism is incompatible with the alleged emergence of properties and laws that some biologists and philosophers assert occurs in various biological systems. I argue that a preferable unified treatment of these emergence claims takes properties, rather than laws, to be the units of emergence. Four distinct conceptions of emergence are explored and three shown to be compatible with micro-determinism. The remaining concept of emergence, direct macro-determination, does not, I argue, meet the general requirement that an adequate scientific explanation provide a coherent mechanism or effective means of determination.