Popper distinguishes the problems of theoretical and pragmatic preference between rival theories, but he claims that there is a common non-inductive solution to both of them, viz. the “best-tested theory”, or the theory with the highest degree of corroboration. He further suggests that the degrees of corroboration serve as indicators of verisimilitude. One may therefore raise the question whether the recent theory of verisimilitude gives a general non-inductive solution to the problem of theoretical preference. This paper argues that this is not the case: the theory of verisimilitude is applicable to this problem if and only if there is an independent solution to the problem of induction. Moreover, the solutions to the theoretical and pragmatic problems of preference coincide only in some special cases.

By observing a black swan, one ascertains an interesting zoological fact. The fact involves two items, a specific object and the property of being a black swan, and consists in the former instantiating the latter. The object is in itself of little interest. Our environment abounds in objects, and knowledge is hardly enhanced by one of them being merely picked out for consideration. The same goes for the property. Properties are at least as plentiful as objects and one does not get to know anything by merely focussing attention upon one of them. What is of interest is the combination of the two items, i.e. the circumstance that the object instantiates the property. And this is what the said fact consists in.

The critics of “hereditarianism” often claim that any attempt to explain human behavior by invoking genes is confronted with insurmountable methodological difficulties. They reject the idea that heritability estimates could lead to genetic explanations by pointing out that these estimates are strictly valid only for a given population and that they are exposed to the irremovable confounding effects of genotype-environment interaction and genotype-environment correlation. I argue that these difficulties are greatly exaggerated, and that we would be wrong to regard them as presenting a fundamental obstacle to the search for genetic explanations. I also show that, to the extent they are cogent, these objections may prove to be even more damaging to the “environmentalist” standpoint.

The article responds to some of the points raised by B. van Fraassen concerning probability kinematics and direct inference within the framework of the approach to the revision of probability judgment proposed by Levi in The Enterprise of Knowledge. In particular, the critical importance of the question of direct inference is emphasized and explained.

Frances Egan argues that the states of computational theories of vision are individuated individualistically and, as far as the theory is concerned, are not intentional. Her argument depends on equating the goals and explanatory strategies of computational psychology with those of its algorithmic level. However, closer inspection of computational psychology reveals that the computational level plays an essential role in explaining visual processes and that explanations at this level are nonindividualistic and intentional. In conclusion, I sketch an account of content in which content does the sort of explanatory work that Egan denies is possible.

Research on diseases such as cancer reveals that primary mechanisms, which have been the focus of study by the new mechanists in philosophy of science, are often subject to control by other mechanisms. Cancer cells employ the same primary mechanisms as healthy cells but control them differently. I use cancer research to highlight just how widespread control is in individual cells. To provide a framework for understanding control, I reconceptualize mechanisms as imposing constraints on flows of free energy, with control mechanisms operating on flexible constraints in primary mechanisms. I argue that control mechanisms themselves often form complex, integrated networks.

We critically examine Denis Walsh's latest attack on the causalist view of fitness. Relying on Judea Pearl's Sure-Thing Principle and geneticist John Gillespie's model for fitness, Walsh has argued that the causal interpretation of fitness results in a reductio. We show that his conclusion only follows from misuse of the models, that is, (1) the disregard of the real biological bearing of the population-size parameter in Gillespie's model and (2) the confusion of the distinction between ordinary probability and Pearl's causal probability. Properly understood, the models used by Walsh do not threaten the causalist view of fitness.

Large changes of financial market prices without exogenous causes deviate significantly from the Gaussian behavior of random variables. This indicates that financial markets should be treated as complex systems, for which nonlinear interactions of its subunits/agents are crucial. I focus on how the complex systems perspective impacts the notion of explanations in economics. The mechanistic model seems to fit the bill, but problems surface on closer scrutiny. One characteristic of complex systems is that their behavior is surprisingly independent from microscopic details. Thus, mechanistic explanations in the microreductionist manner seem unavailable. Despite these conflicts, I defend a modified structural mechanistic approach.

The simple question, what is empirical success? turns out to have a surprisingly complicated answer. We need to distinguish between meritorious fit and ‘fudged fit’, which is akin to the distinction between prediction and accommodation. The final proposal is that empirical success emerges in a theory dependent way from the agreement of independent measurements of theoretically postulated quantities. Implications for realism and Bayesianism are discussed.

I criticize conceptual pluralism, as endorsed recently by John Dupré and Philip Kitcher, for failing to supply strategies for demarcating science from non-science. Using creation-science as a test case, I argue that pluralism blocks arguments that keep creation-science in check and that metaphysical pluralism offers it positive, metaphysical support. Logical empiricism, however, still provides useful resources to reconfigure and manage the problem of creation-science in those practical and political contexts where pluralism will fail.

In this rejoinder to the three preceding comments, I provide some additional philosophical warrant for the biomedical sciences' focus on model organisms. I then relate the inquiries on model systems to the concept of ‘deep homology’, and indicate that the issues that appear to divide my commentators and myself are in part empirical ones. I cite recent work on model organisms, and especially C. elegans that supports my views. Finally, I briefly readdress some of the issues raised by Developmental Systems Theory.

The distinction between psychology, logic, and epistemology is a commonplace. The first treats of experience as an act, experience in its relation to the individual observer. The second concerns itself with the internal marks by which truth may be distinguished from error, and in so far as it deals with experience, has to do with some sort of validity of the experience as evidence of a truth. The third discusses in a general way all the elements—observer, object, immediate presentation—which enter into the experience.

In much recent work, invariance under intervention has become a hallmark of the correctness of a causal-law claim. Despite its importance this thesis generally is either simply assumed or is supported by very general arguments with heavy reliance on examples, and crucial notions involved are characterized only loosely. Yet for both philosophical analysis and practicing science, it is important to get clear about whether invariance under intervention is or is not necessary or sufficient for which kinds of causal claims. Furthermore, we need to know what counts as an intervention and what invariance is. In this paper I offer explicit definitions of two different kinds for the notions intervention, invariance, and causal correctness. Then, given some natural and relatively uncontroversial assumptions, I prove two distinct sets of theorems showing that invariance is indeed a mark of causality when the concepts are appropriately interpreted.

There is often substantial disparity between philosophical ideals and scientific practice. Philosophical reductionism is motivated by a drive for ontological austerity. The vehicle is conceptual parsimony: the fewer our conceptual primitives, the less are our ontological commitments. A general moral to be drawn from my “Functionalism and Reductionism” (1979) is that scientific reduction does not, and should not be expected to, facilitate conceptual economy; yet reduction it still is, and in the classical mold. Those who press for the irreducibility of a functional psychology have been seduced by an inadequate account of scientific reduction. Patricia Kitcher (1980) is unhappy with my argument because it fails to live up to her philosophical ideals. “The claim that psychology is irreducible to neurophysiology,” she suggests, “rests to a large extent on the fact that, even in principle, neurophysiology is not capable of carrying out the explanatory work of a functional psychology” (1980, p. 140).

Neurath's proposal for the form of protocol statements explicates the multiple embedding of a singular sentence as specifying different conditions for the acceptance of such a sentence as a bona fide scientific datum. Before theories are accepted or rejected in the light of such evidence, however, a further condition must be met which Neurath did not formalize. The different conditions are discussed and shown to constitute a naturalistic theory of scientific data and a pragmatic theory of theory acceptance.

A brief discussion is offered of what it means to say that a set of statements provides D-N explanation with special emphasis given to approximative D-N explanation. An idealized theory is seen to provide approximative D-N explanation. An ideal case provides explanation only if postulates are offered which connect the ideal antecedent condition with actual conditions. Such postulates will help in accounting for deviations between what the consequent of the ideal case entails and what actually occurs. Three ways are presented for deciding on the acceptability of idealizations: (i) as actual conditions more closely approximate the ideal antecedent conditions specified in an ideal case, the more closely actual cases ought to approximate the consequent of the ideal case; (ii) the additional postulates connecting ideal antecedent conditions with actual conditions ought to account for deviations between what is entailed by an idealized theory and what actually occurs ; and (iii) an idealized theory is explained by a more general theory when certain state variables in the more general theory are given extreme values. It is argued that (iii) is not a necessary condition for the acceptability of idealizations.

I respond to Belot's argument and defend the view that sometimes ‘fundamental theories’ are explanatorily inadequate and need to be supplemented with certain aspects of less fundamental ‘theories emeritus’.

Phylogenetic information is often necessary to distinguish between evolutionary scenarios. Recently, some prominent proponents of evolutionary psychology have acknowledged this, and have claimed that such evidence has in fact been brought to bear on adaptive hypotheses involving complex human psychological traits. Were this possible, it would be a valuable source of evidence regarding hypothesized adaptive traits in humans. However, the structure of the Hominidae family makes this difficult or impossible. For many traits of interest, the closest extant relatives to the human species are too phenotypically different from humans for such methods to provide meaningful data. While phylogenetic information can be useful for testing adaptive hypotheses in humans, these generally involve traits that are (a) not widely shared in the species or (b) fairly widely shared in the Hominidae family, and hence likely of a lower order of complexity than the sorts of traits evolutionary psychology has so far been interested in.

Theories of function are conventionally divided up into historical and ahistorical ones. Proponents of ahistorical theories often cite the ahistoricity of their accounts as a major virtue. Here, I argue that none of the mainstream “ahistorical” accounts are actually ahistorical. All of them refer, implicitly or explicitly, to history. In Boorse’s goal-contribution account, history is latent in the idea of statistical typicality. In the propensity theory, history is implicit in the idea of a species’ natural habitat. In the causal role theory, history is required for making sense of dysfunction. I elaborate some consequences for the functions debate.