This article calls into question the charge that frequentist testing is susceptible to the base-rate fallacy. It is argued that the apparent similarity between examples like the Harvard Medical School test and frequentist testing is highly misleading. A closer scrutiny reveals that such examples have none of the basic features of a proper frequentist test, such as legitimate data, hypotheses, test statistics, and sampling distributions. Indeed, the relevant error probabilities are replaced with the false positive/negative rates that constitute deductive calculations based on known probabilities among events. As a result, the ampliative dimension of frequentist induction—learning from data about the underlying data-generating mechanism—is missing.

Several authors have argued that higher taxa are monophyletic homeostatic property cluster natural kinds. On the traditional definition of monophyly, this will not work: the emergence of taxon-defining homeostatic property clusters would not always correspond to unique speciation events. An alternative conception of monophyly is developed and advocated, which can accommodate the homeostatic property cluster proposal. Recent work in philosophy of science shows that it meets appropriate standards of objectivity and precision.

I defend an account of explanatory depth according to which explanations in the nonfundamental sciences can be deeper than explanations in fundamental physics.

Prominent defenders of the extended cognition thesis have looked to evolutionary theory for support. Roughly, the idea is that natural selection leads one to expect that cognitive strategies should exploit the environment, and exploitation of the right sort results in a cognitive system that extends beyond the head of the organism. I argue that proper appreciation of evolutionary theory should create no such expectation. This leaves open whether cognitive systems might in fact bear a relationship to the environment that leads to their extension.

Over the last 2,300 years or so, many philosophers have believed that species are individuated by essences that are at least in part intrinsic. Psychologists tell us most folks also believe this view. But most philosophers of biology have abandoned the view, in light of evolutionary conceptions of species. In defiance, Michael Devitt has attempted in this journal to resurrect a version of the view, which he calls Intrinsic Biological Essentialism. I show that his arguments for the resurrection fail, and I identify challenges that face anyone wishing to defend Intrinsic Biological Essentialism.

Recently philosophers of biology have argued over whether or not Newtonian mechanics provides a useful analogy for thinking about evolutionary theory. For philosophers, the canonical presentation of this analogy is Sober's. Matthen and Ariew and Walsh, Lewins, and Ariew argue that this analogy is deeply wrong-headed. Here I argue that the analogy is indeed useful, however, not in the way it is usually interpreted. The Newtonian analogy depends on having the proper analogue of Newton's First Law. That analogue is what McShea and Brandon call the Zero Force Evolutionary Law (ZFEL). According to the ZFEL, change, not stasis, is the default state of evolutionary systems.

In a recent Philosophy of Science article, Gerhard Schurz proposes meta-inductivistic prediction strategies as a new approach to Hume's problem. This discussion examines the limitations of Schurz's approach. It can be proved that the meta-inductivistic approach does not work anymore if meta-inductivists have to face an infinite number of alternative predictors. With this limitation it remains doubtful whether the meta-inductivist can provide a full solution to the problem of induction.

Many empirically minded philosophers have used neuroscientific data to argue against the multiple realization of cognitive functions in existing biological organisms. I argue that neuroscientists themselves have proposed a biologically based concept of multiple realization as an alternative to interpreting empirical findings in terms of one-to-one structure-function mappings. I introduce this concept and its associated research framework and also how some of the main neuroscience-based arguments against multiple realization go wrong.

Philosophy of scientific practice aims to critically evaluate as well as describe scientific inquiry. Epistemic norms are required for such evaluation. Social constructivism is widely thought to oppose this critical project. I argue, however, that one variety of social constructivism, focused on epistemic justification, can be a basis for critical epistemology of scientific practice, while normative accounts that reject this variety of social constructivism (SCj) cannot. Abstract, idealized epistemic norms cannot ground effective critique of our practices. I propose a new approach, placing SCj within a general framework of social action theory. This framework can be used to explicate epistemic norms implicit in our scientific practices.

Problems concerning scientists’ uses of representations have received quite a bit of attention recently. The focus has been on how such representations get their contents and on just what those contents are. Less attention has been paid to what makes certain kinds of scientific representations different from one another and thus well suited to this or that epistemic end. This article considers the latter question with particular focus on the distinction between images and graphs on the one hand and descriptions and related representations on the other.

In their book What Darwin Got Wrong, Jerry Fodor and Massimo Piattelli-Palmarini construct an a priori philosophical argument and an empirical biological argument. The biological argument aims to show that natural selection is much less important in the evolutionary process than many biologists maintain. The a priori argument begins with the claim that there cannot be selection for one but not the other of two traits that are perfectly correlated in a population; it concludes that there cannot be an evolutionary theory of adaptation. This article focuses mainly on the a priori argument.

It is argued that recent discussion of the principle of the identity of indiscernibles (PII) and quantum mechanics has lost sight of the broader philosophical motivation and significance of PII and that the ‘received view' of the status of PII in the light of quantum mechanics survives recent criticisms of it by Muller, Saunders, and Seevinck.

The traditional view of evolutionary theory asserts that we can usefully understand natural selection, drift, mutation, migration, and the system of mating as forces that cause evolutionary change. Recently, Denis Walsh and Robert Brandon have objected to this view. Walsh argues that the traditional view faces a fatal dilemma and that the force analogy must be rejected altogether. Brandon accepts the force analogy but argues that drift, rather than the Hardy-Weinberg law, is the best candidate for a zero-force law. Here I defend the traditional view against these objections.

Denis Walsh has written a striking new defense in this journal of the statisticalist (i.e., noncausalist) position regarding the forces of evolution. I defend the causalist view against his new objections. I argue that the heart of the issue lies in the nature of nonadditive causation. Detailed consideration of that turns out to defuse Walsh's ‘description-dependence’ critique of causalism. Nevertheless, the critique does suggest a basis for reconciliation between the two competing views.

I consider and reject William Whewell's attack on the inductivism of Isaac Newton and John Stuart Mill, as well as John Norton's attack on any universal system of inductive rules. I also explain how a system of inductive rules of the sort proposed by Newton and Mill should be understood.

Recently, Barbara Renzi argued that Kuhn's account of scientific change is undermined by mismatches in the analogy that Kuhn supposedly draws between scientific change and biological evolution. We argue that Renzi's criticism is inadequate to Kuhn's account of scientific change, as Kuhn does not draw any precise analogy between the mechanisms of scientific change and biological evolution nor aims to argue that the mechanisms of scientific change and biological evolution are similar in any important respects. Therefore, pointing to mismatches between the central concepts that feature in the descriptions of the two phenomena simply misses the point of Kuhn's analogy.

Some writers have urged that evolutionary theory produces generalizations that hold only ceteris paribus, that is, provided “everything else is equal.” Others have claimed that all laws in the special sciences, or even all laws in science generally, hold only ceteris paribus. However, if we lack a way to determine when everything else really is equal, hedging generalizations with the phrase “ceteris paribus” renders those generalizations vacuous. In what follows, I propose a solution to this problem for the case of causal equations from classical population genetics. My proviso is generated on the basis of a couple of conceptual maneuvers, “tricks,” which should be usable elsewhere too.