Since the introduction of mathematical population genetics, its machinery has shaped our fundamental understanding of natural selection. Selection is taken to occur when differential fitnesses produce differential rates of reproductive success, where fitnesses are understood as parameters in a population genetics model. To understand selection is to understand what these parameter values measure and how differences in them lead to frequency changes. I argue that this traditional view is mistaken. The descriptions of natural selection rendered by population genetics models are in general neither predictive nor explanatory and introduce avoidable conceptual confusions. I conclude that a correct understanding of natural selection requires explicitly causal models of reproductive success.

This paper proposes a revision of our understanding of causation that is designed to address what Hartry Field has suggested is the central problem in the metaphysics of causation today: reconciling Bertrand Russell's arguments that the concept of causation can play no role in the advanced sciences with Nancy Cartwright's arguments that causal concepts are essential to a scientific understanding of the world. The paper shows that Russell's main argument is, ironically, very similar to an argument that Cartwright has put forward against the truth of universal laws of nature. The paper uses this insight to develop an account of causation that does justice to traditional views yet avoids the arguments of Russell.

I defend the view that many biological categories are defined by homology against a series of arguments designed to show that all biological categories are defined, at least in part, by selected function. I show that categories of homology are ‘abnormality inclusive’—something often alleged to be unique to selected function categories. I show that classifications by selected function are logically dependent on classifications by homology, but not vice-versa. Finally, I reject the view that biologists must use considerations of selected function to abstract away from variation and pathology to form a canonical description of a class of biological systems.

This paper discusses several philosophical problems with the use of randomized clinical trials (RCTs) in psychotherapy outcome research. The problems include: the impermanence problem, the identification problem, and idiographic problems. The paper concludes with an assessment of the overall case for and against the use of RCTs in psychotherapy outcome research.

This paper examines a novel notion of causality, namely, fuzzy-set-theoretic causality. Over the last decade, a number of conceptual models of causality, in the language of fuzzy-set theory, have appeared in the scientific literature and have been applied to empirical research. They have circulated widely from one scientific discipline to another, weaving a unifying thread through them. However, they have received no philosophical attention. In this paper, I will discuss the value and limitations of this type of model and will read into its application several dimensions of philosophical significance.

Starting from the standard quantum formalism for a single spin$\frac{1}{2}$ system (e.g., an electron), this essay develops a model rich enough not only to afford an explication of symmetry breaking but also to frame questions about how to circumscribe physical possibility on behalf of theories that countenance symmetry breaking.

A common presupposition in the concepts literature is that concepts constitute a singular natural kind. If, on the contrary, concepts split into more than one kind, this literature needs to be recast in terms of other kinds of mental representation. We offer two new arguments that concepts, in fact, divide into different kinds: (a) concepts split because different kinds of mental representation, processed independently, must be posited to explain different sets of relevant phenomena; (b) concepts split because different kinds of mental representation, processed independently, must be posited to explain responses to different kinds of category. Whether these arguments are sound remains an open empirical question, to be resolved by future empirical and theoretical work.

Genic selectionists (Williams 1966; Dawkins 1976) defend the view that genes are the (unique) units of selection and that all evolutionary events can be adequately represented at the genic level. Pluralistic genic selectionists (Sterelny and Kitcher 1988; Waters 1991; Dawkins 1982) defend the weaker view that in many cases there are multiple equally adequate accounts of evolutionary events, but that always among the set of equally adequate representations will be one at the genic level. We describe a range of cases all involving stable equilibria actively maintained by selection. In these cases genotypic models correctly show that selection is active at the equilibrium point. In contrast, the genic models have selection disappearing at equilibrium. For deterministic models this difference makes no difference. However, once drift is added in, the two sets of models diverge in their predicted evolutionary trajectories. Thus, contrary to received wisdom on this matter, the two sets of models are not empirically equivalent. Moreover, the genic models get the facts wrong.

Von Neumann argued by means of a thought experiment involving measurements of spin observables that the quantum mechanical quantity$S_{VN}=-k\mathrm{Tr}\,(\rho \mathrm{log}\,\rho) $ is conceptually equivalent to thermodynamic entropy. We analyze Von Neumann's thought experiment and show that his argument fails.

In “Concepts Are Not a Natural Kind” (2005), I argued that the notion of concept in psychology and in neuropsychology fails to pick out a natural kind. Piccinini and Scott (2006, in this issue) have criticized the argument I used to support this conclusion. They also proposed two alternative arguments for a similar conclusion. In this reply, I rebut Piccinini and Scott's main objection against the argument proposed in “Concepts Are Not a Natural Kind.” Moreover, I show that the two alternative arguments developed by Piccinini and Scott are not promising for supporting the conclusion that concepts are not a natural kind.

Since Ramsey, much discussion of the relation between probability and belief has taken for granted that there are degrees of belief, i.e., that there is a real-valued function, B, that characterizes the degree of belief that an agent has in each statement of his language. It is then supposed that B is a probability. It is then often supposed that as the agent accumulates evidence, this function should be updated by conditioning:$B^{E}(\cdot) $ should be$B(\cdot \wedge E) / B(E) $ . Probability is also important in classical statistics, where it is generally supposed that probabilities are frequencies, and that inference proceeds by controlling error and not by conditioning. I will focus on the tension between these two approaches to probability, and in the main part of the paper show where and when Bayesian conditioning conflicts with error based statistics and how to resolve these conflicts.

The Higgs mechanism is an essential but elusive component of the Standard Model of particle physics. Without it Yang-Mills gauge theories would have been little more than a warm-up exercise in the attempt to quantize gravity rather than serving as the basis for the Standard Model. This article focuses on two problems related to the Higgs mechanism clearly posed in Earman's recent papers (Earman 2003, 2004a, 2004b): what is the gauge-invariant content of the Higgs mechanism, and what does it mean to break a local gauge symmetry?

Scientists can choose different claims as interpretations of the results of their research. Scientific rhetoric is understood as the attempt to make those claims most beneficial for the scientists’ interests. A rational choice, game-theoretic model is developed to analyze how this choice can be made and to assess it from a normative point of view. The main conclusion is that ‘social’ interests (pursuit of recognition) may conflict with ‘cognitive’ ones when no constraints are put on the choices of the authors of scientific papers, as in an ‘ideal free speech situation’. Scientific institutions may help to solve this conflict. Lastly, some empirical predictions are offered that can inspire future social research of the refereeing process.

This article investigates the implications of string theory for the conception of scientific theory confirmation. The classical understanding of theory confirmation is based on the assumption that scientific theory building is underdetermined by the available empirical data. Several arguments are presented, which suggest a devaluation of this ‘principle of scientific underdetermination’ in the context of string theory. An altered conception of scientific progress emerges that is not based on the notion of theory succession.

Hermann Weyl succeeded in presenting a consistent overarching analysis that accounts for symmetry in (1) material artifacts, (2) natural phenomena, and (3) physical theories. Weyl showed that group theory is the underlying mathematical structure for symmetry in all three domains. But in this study Weyl did not include appeals to symmetry arguments which, for example, Einstein expressed as “for reasons of symmetry” (wegen der Symmetrie; aus Symmetriegründen). An argument typically takes the form of a set of premises and rules of inference that lead to a conclusion. Symmetry may enter an argument both in the premises and the rules of inference, and the resulting conclusion may also exhibit symmetrical properties. Taking our cue from Pierre Curie, we distinguish two categories of symmetry arguments, axiomatic and heuristic; they will be defined and then illustrated by historical cases.

Carnap's inductive logic (or confirmation) project is revisited from an “increase in firmness” (or probabilistic relevance) point of view. It is argued that Carnap's main desiderata can be satisfied in this setting, without the need for a theory of “logical probability.” The emphasis here will be on explaining how Carnap's epistemological desiderata for inductive logic will need to be modified in this new setting. The key move is to abandon Carnap's goal of bridging confirmation and credence, in favor of bridging confirmation and evidential support.

A common complaint against the increasing privatization of research is that research that is conducted with the immediate purpose of producing applicable knowledge will not yield knowledge as valuable as that generated in more curiosity-driven, academic settings. In this paper, I make this concern precise and reconstruct the rationale behind it. Subsequently, I examine the case of industry research on the giant magnetoresistance effect in the 1990s as a characteristic example of research undertaken under considerable pressure to produce applicable results. The example permits one to arrive at a more optimistic assessment of the epistemic merits of private, application-driven research. I attempt to specify the conditions that, in this case, advanced the production of interesting and reliable knowledge.

Controversies over the innateness of cognitive structures play a persistent role in driving research in philosophy as well as cognitive science, but the appropriate way to understand the category of the innate remains in dispute. The invariantist approaches of Stich and Sober face counterexample cases of traits that, though developing invariantly across different environments, nonetheless are not held by nativism partisans to count as innate. Appeals to canalization (Ariew) or to psychological primitiveness (Samuels) fail to handle this liberalism problem. We suggest a novel approach to innateness: closed process invariantism.

In Science, Truth, and Democracy, Philip Kitcher challenges the view that science has a single, context-independent, goal, and that the pursuit of this goal is essentially immune from moral critique. He substitutes a context-dependent account of science's goal, and shows that this account subjects science to moral evaluation. I argue that Kitcher's approach must be modified, as his account of science ultimately must be explicated in terms of moral concepts. I attempt, therefore, to give an account of science's goal that is free of direct moral entanglements but still makes this goal context-dependent and leaves the choice of which projects to pursue subject to moral scrutiny.