Bertrand's random-chord paradox purports to illustrate the inconsistency of the principle of indifference when applied to problems in which the number of possible cases is infinite. This paper shows that Bertrand's original problem is vaguely posed, but demonstrates that clearly stated variations lead to different, but theoretically and empirically self-consistent solutions. The resolution of the paradox lies in appreciating how different geometric entities, represented by uniformly distributed random variables, give rise to respectively different nonuniform distributions of random chords, and hence to different probabilities. The principle of indifference appears consistently applicable to infinite sets provided that problems can be formulated unambiguously.

This paper investigates what molecular biology has done for our understanding of the gene. I base a new account of the gene concept of classical genetics on the classical dogma that gene differences cause phenotypic differences. Although contemporary biologists often think of genes in terms of this concept, molecular biology provides a second way to understand genes. I clarify this second way by articulating a molecular gene concept. This concept unifies our understanding of the molecular basis of a wide variety of phenomena, including the phenomena that classical genetics explains in terms of gene differences causing phenotypic differences.

According to a standard account of evidence, one piece of information is stronger evidence for an hypothesis than is another iff the probability of the hypothesis on the one is greater than it is on the other. This condition, I argue, is neither necessary nor sufficient because various factors can strengthen the evidence for an hypothesis without increasing (and even decreasing) its probability. Contrary to what probabilists claim, I show that this obtains even if a probability function can take these evidential factors into account in ways they suggest and yield a unique probability value. Nor will the problem be solved by appealing to second-order probabilities.

The proper treatment of correlation in evolutionary game theory has unexpected connections with recent philosophical discussions of the theory of rational decision. The Logic of Decision (Jeffrey 1983) provides the correct framework for correlated evolutionary game theory and a variant of “ratifiability” is the appropriate generalization of “evolutionarily stable strategy”. The resulting theory unifies the treatment of correlation due to kin, population viscosity, detection, signaling, reciprocal altruism, and behavior-dependent contexts. It is shown that (1) a strictly dominated strategy may be selected, and (2) under conditions of perfect correlation a strictly efficient strategy must be selected.

This paper argues that when used judiciously Bayes's law has a role to play in the evaluation of scientific hypotheses. Several examples are presented in which a rational response to evidence requires a judgement whether to apply Bayes's law or whether, for example, to redistribute prior probabilities. The paper concludes that reflection on Bayes's law illustrates how an adequate account of the rational evaluation of hypotheses requires an account of judgement—a point which several philosophers have noted despite few attempts to develop an adequate theory of judgement.

A theory may be invalid, not owing to erroneous observations or the invocation of an inappropriate law, but because of the use of equivocal terms. This is demonstrated for Darwin's failed model of sympatric speciation through the principle of divergence.

Contrary to the assumptions of empiricist philosophies of science, the theory-laden character of data will not imply the inherent failure (subjectivity, circularity, or rationalization) of instruments to expose nature's secrets. The success of instruments is credited to scientists' capacity to create artificial technological analogs to familiar physical systems. The design of absorption spectrometers illustrates the point: Progress in designing many modern instruments is generated by analogically projecting theoretical insights from known physical systems to unknown terrain. An experimental realism is defended.

Most biologists use the Linnaean system for constructing classifications of the organic world. The Linnaean system, however, has lost its theoretical basis due to the shift in biology from creationist and essentialist tenets to evolutionary theory. As a result, the Linnaean system is both cumbersome and ontologically vacuous. This paper illustrates the problems facing the Linnaean system, and ends with a brief introduction to an alternative approach to biological classification.

In this paper we critically review the various attempts that have been made to understand quantum field theory. We focus on Teller's (1990) harmonic oscillator interpretation, and Bohm et al.'s (1987) causal interpretation. The former unabashedly aims to be a purely heuristic account, but we show that it is only interestingly applicable to the free bosonic field. Along the way we suggest alternative models. Bohm's interpretation provides an ontology for the theory—a classical field, with a quantum equation of motion. This too has problems; it is not Lorentz invariant.

I adopt a cladistic view of species, and explore the possibility that there exists an equally valuable cladistic view of organismic traits. This suggestion seems to run counter to the stress on functional views of biological traits in recent work in philosophy and psychology. I show how the tension between these two views can be defused with a multilevel view of biological explanation. Despite the attractions of this compromise, I conclude that we must reject it, and adopt an essentially cladistic conception of biological traits.

The evolutionary problem of the units of selection has elicited a good deal of conceptual work from philosophers. We review this work to determine where the issues now stand.

The basic problem of perceptual change is how to account for both variation and constancy in perceiving the world. Is order learned? How deep does plasticity go in that respect? I argue that different kinds of perceptual plasticity have been confused in recent debates, notably between J. Fodor and P. M. Churchland. By focusing on changes in the use of concepts, the issues in the Fodor-Churchland debate can be resolved. Beyond that debate, I propose a generalized encoding approach to perception as a way of accounting for a significant form of perceptual change.

Because of the problems associated with ecological concepts, generalizations, and proposed general theories, applied ecology may require a new “logic” of explanation characterized neither by the traditional accounts of confirmation nor by the logic of discovery. Building on the works of Grünbaum, Kuhn, and Wittgenstein, we use detailed descriptions from research on conserving the Northern Spotted Owl, a case typical of problem solving in applied ecology, to (1) characterize the method of case studies; (2) survey its strengths; (3) summarize and respond to its shortcomings; and (4) investigate and defend its underlying “logic”.

Individualists claim that wide explanations in psychology are problematic. I argue that wide psychological explanations sometimes have greater explanatory power than individualistic explanations. The aspects of explanatory power I focus on are causal depth and theoretical appropriateness. Reflection on the depth and appropriateness of other wide explanations of behavior, such as evolutionary explanations, clarifies why wide psychological explanations sometimes have more causal depth and theoretical appropriateness than narrow psychological explanations. I also argue for the rejection of eliminative materialism.

The so-called “adaptationism” of mainstream evolutionary biology has been criticized from a variety of sources. One, which has received relatively little philosophical attention, is developmental biology. Developmental constraints are said to be neglected by adaptationists. This paper explores the divergent methodological and explanatory interests that separate mainstream evolutionary biology from its embryological and developmental critics. It will focus on the concept of constraint itself; even this central concept is understood differently by the two sides of the dispute.

“Accessibility” is a crucial concept of possible worlds semantics. The simplest approach to accessibility is the “magical theory” that construes this relation as analogous to spatial or temporal relations. In this paper I give a nonmagical structural account of the accessibility relation that can be used to give a necessitarian account of kinds and laws. Laws are characterized in a structural way as stable invariants of the world's gestalt. Finally, I point out how the structural approach can be embedded in a general representational theory of modality.

This paper examines the nomic covariationist strategy of using idealization to define representation. While the literature has focused upon the possibility of defining ideal conditions for perception, I argue that nomic covariationist appeals to idealization are pseudoscientific and contrary to a foundational and empirically well-supported methodological presupposition in cognitive science. Moreover, one major figure in this camp fails to come to grips with its role and its problems in mainstream science. Thus he forwards a false dichotomy of the sciences and treats idealization as a blank check written by scientists on an unknown bank. Finally, I consider and reject alternative formulations of the nomic covariationist's idealization strategy.

The biological sciences employ a concept of normality that must be distinguished from statistical or value concepts. The concept of normality is presupposed in the standard explications of biological functions, and it is crucial to the strategy of explanation by approximations in, for example, physiology. Nevertheless, this concept of normality does not seem to be captured in the language of physics. Thus attempts at explaining the methodological relationship between the biological sciences and the physical sciences by concentrating only on the concept of biological function cannot go very far. An analysis of the concept of normality is also necessary.

When classical mechanics is seen as the short-wavelength limit of quantum mechanics (i.e., as the limit of geometrical optics), it becomes clear just how serious and all-pervasive the measurement problem is. This formulation also leads us into the Bohm theory. But this theory has drawbacks: its nonuniqueness, in particular, and its nonlocality. I argue that these both reflect an underlying problem concerning information, which is actually a deeper version of the measurement problem itself.

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.