This article presents a distinct sense of ‘mechanism’, which I call the functional sense of mechanism. According to this sense, mechanisms serve functions, and this fact places substantive restrictions on the kinds of system activities ‘for which’ there can be a mechanism. On this view, there are no mechanisms for pathology; pathologies result from disrupting mechanisms for functions. Second, on this sense, natural selection is probably not a mechanism for evolution because it does not serve a function. After distinguishing this sense from similar explications of ‘mechanism’, I argue that it is ubiquitous in biology and has valuable epistemic benefits.

Obviously we could have failed to be successful scientists. But a serious question lurks beneath the banal one stated in my title. If the results of a scientific investigation are correct, would any investigation of roughly the same subject matter, if successful, at least implicitly contain or imply the same results? Using examples ranging from immunology to high-energy physics, the paper presents the cases for both positive and negative answers. The paper is deliberately non-conclusive, arguing that the question is one of the few serious philosophical issues that divides protagonists in the “science wars.”

Industry is a major source of funding for scientific research. There is also a growing concern for how it corrupts researchers faced with conflicts of interest. As such, the debate has focused on whether researchers have maintained their integrity. In this article we draw on both the history of medicine and formal modeling to argue that given methodological diversity and a merit-based system, industry funding can bias a community without corrupting any particular individual. We close by considering a policy solution (i.e., independent funding) that may seem to promote unbiased inquiry but that actually exacerbates the problem without additional restrictions.

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.

Although the application of social science to practical problems of policy and action is still in its early stages, a large body of experience has been accumulated. Social science has been applied, in diverse spheres and with diverse results. The experience is there, but it has not been systematically reviewed and codified. Consequently, no one knows the present status of applied social science or, more importantly, its potentialities.

In this paper we examine the following problems: How many concepts of function are there in biology, social science, and technology? Are they logically related and if so, how? Which of these function concepts effect a functional explanation as opposed to a mere functional account? What are the consequences of a pluralist view of functions for functionalism? We submit that there are five concepts of function in biology, which are logically related in a particular way, and six function concepts in social science and technology. Only two of them may help effect a genuine functional explanation. Finally, our synthetic approach allows us to distinguish four different varieties of functionalism in biology, psychology, social science, and technology: formalist, black boxist, adaptationist, and teleological. And only one of them is explanatory in the strong sense defended here.

Many philosophers have claimed that evidence for a theory is better when multiple independent tests yield the same result, i.e., when experimental results are robust. Little has been said about the grounds on which such a claim rests, however. The present essay presents an analysis of the evidential value of robustness that rests on the fallibility of assumptions about the reliability of testing procedures and a distinction between the strength of evidence and the security of an evidence claim. Robustness can enhance the security of an evidence claim either by providing what I call second-order evidence, or by providing back-up evidence for a hypothesis.

In this paper I expound an argument which seems to establish that probabilism and special relativity are incompatible. I examine the argument critically, and consider its implications for interpretative problems of quantum theory, and for theoretical physics as a whole.

This paper explores how data serve as evidence for phenomena. In contrast to standard philosophical models which invite us to think of evidential relationships as logical relationships, I argue that evidential relationships in the context of data-to-phenomena reasoning are empirical relationships that depend on holding the right sort of pattern of counterfactual dependence between the data and the conclusions investigators reach on the phenomena themselves.

It is here argued that functionalist constraints on psychology do not preclude the applicability of classic forms of reduction and, therefore, do not support claims to a principled, or de jure, autonomy of psychology. In Part I, after isolating one minimal restriction any functionalist theory must impose on its categories, it is shown that any functionalism imposing an additional constraint of de facto autonomy must also be committed to a pure functionalist—that is, a computationalist—model for psychology. Using an extended parallel to the reduction of Mendelian to molecular genetics, it is shown in Parts II and III that, contrary to the claims of Hilary Putnam and Jerry Fodor, there is no inconsistency between computational models and classical reductionism: neither plurality of physical realization nor plurality of function are inconsistent with reductionism as defended by Ernest Nagel. Employing the results of Part I, the conclusions of Parts II and III are generalized in Part IV to cover any version of functionalism whatsoever; thus, functionalism and reductionism are shown to be consistent. It is urged in conclusion that although a de facto form of autonomy is defensible, there are sound methodological grounds for unconditionally rejecting any principled version of the autonomy of psychology.

Cognitive scientists often employ the notion of innateness without defining it. The issue is, how is innateness defined in biology? Some critics contend that innateness is not a legitimate concept in biology. In this paper I will argue that it is. However, neither the concept of high heritability nor the concept of flat norm of reaction (two popular accounts in the biology literature) define innateness. An adequate account is found in developmental biology. I propose that innateness is best defined in terms of C. H. Waddington's concept of canalization.

The author proposes the thesis that all perception, including observation in natural science, is hermeneutical as well as causal; that is, the perceiver (or observer) learns to ‘read’ instrumental or other perceptual stimuli as one learns to read a text. This hermeneutical aspect at the heart of natural science is located where it might be least expected, within acts of scientific observation. In relation to the history of science, the question is addressed to what extent the hermeneutical component within scientific observation opens natural science to the charge of reflecting merely cultural values, and of providing merely a culturally acceptable reading of the “Book of Nature”, rather than, as the author states, one stating universal antecedent conditions of possibility of cultural activity itself.

We reassess Woodward’s counterfactual account of explanation in relation to regularity explananda. Woodward presents an account of causal explanation. We argue, by using an explanation of Kleiber’s law to illustrate, that the account can also cover some noncausal explanations. This leads to a tension between the two key aspects of Woodward’s account: the counterfactual aspect and the causal aspect. We explore this tension and make a case for jettisoning the causal aspect as constitutive of explanatory power in connection with regularity explananda.

To arrive at their final evaluation of a manuscript or grant proposal, reviewers must convert a submission’s strengths and weaknesses for heterogeneous peer review criteria into a single metric of quality or merit. I identify this process of commensuration as the locus for a new kind of peer review bias. Commensuration bias illuminates how the systematic prioritization of some peer review criteria over others permits and facilitates problematic patterns of publication and funding in science. Commensuration bias also foregrounds a range of structural strategies for realigning peer review practices and institutions with the aims of science.

Philosophers of science have insisted that evidence of underlying mechanisms is required to support claims about the effects of medical interventions. Yet evidence about mechanisms does not feature on dominant evidence-based medicine “hierarchies.” After arguing that only inferences from mechanisms (“mechanistic reasoning”)—not mechanisms themselves—count as evidence, I argue for a middle ground. Mechanistic reasoning is not required to establish causation when we have high-quality controlled studies; moreover, mechanistic reasoning is more problematic than has been assumed. Yet where the problems can be overcome, mechanistic reasoning can and should be used as evidence.

This paper argues that conceptualizing unity as “interconnection” (rather than reduction) provides a more fruitful and versatile framework for the philosophical study of scientific unification. Building on the work of Darden and Maull, Kitcher, and Kincaid, I treat unity as a relationship between fields: two fields become more integrated as the number and/or significance of interfield connections grow. Even when reduction fails, two theories or fields can be unified (integrated) in significant ways. I highlight two largely independent dimensions of unification. Fields are theoretically unified to the extent that we understand how the ontologies, concepts, and generalizations of these fields are connected. (Reductionism is one form of theoretical unity, but not the only form). Fields are practically unified through heuristic connections (e.g., using the heuristics of one field to generate hypotheses in another field) and by the development of methods for integrating the qualitatively distinct bodies of data generated by the two fields. I discuss the relationship between paleontological and neontological systematics to illustrate the utility of conceptualizing unity as interconnection.

History of science, it has been argued, has benefited philosophers of science primarily by forcing them into greater contact with “real science.” In this paper I argue that additional major benefits arise from the importance of specifically historical considerations within philosophy of science. Loci for specifically historical investigations include: (1) making and evaluating rational reconstructions of particular theories and explanations, (2) estimating the degree of support earned by particular theories and theoretical claims, and (3) evaluating proposed philosophical norms for the evaluation of the degree of support for theories and the worth of explanations. More generally, I argue that theories develop and change structure with time, that (like biological species) they are historical entities. Accordingly, both the identification and the evaluation of theories are essentially historical in character.

Philosophers of science readily acknowledge that nonepistemic values influence the discovery and pursuit of scientific theories, but many tend to regard these influences as epistemically uninteresting. The present paper challenges this position by identifying three avenues through which nonepistemic values associated with discovery and pursuit in contemporary pollution research influence theory appraisal: (1) by guiding the choice of questions and research projects, (2) by altering experimental design, and (3) by affecting the creation and further investigation of theories or hypotheses. This analysis indicates that the effects of these values are sufficiently complex and epistemically significant to merit further attention.

Lewis sender-receiver games illustrate how a meaningful term language might evolve from initially meaningless random signals (Lewis 1969; Skyrms 2006). Here we consider how a meaningful language with a primitive grammar might evolve in a somewhat more subtle sort of game. The evolution of such a language involves the co-evolution of partitions of the physical world into what may seem, at least from the perspective of someone using the language, to correspond to canonical natural kinds. While the evolved language may allow for the sort of precise representation that is required for successful coordinated action and prediction, the apparent natural kinds reflected in its structure may be purely conventional. This has both positive and negative implications for the limits of naturalized metaphysics.

This paper explores a new reason for preferring a model-theoretic approach to understanding the nature of scientific theories. Identifying the models in philosophers' model-theoretic accounts of theories with the concepts in cognitive scientists' accounts of categorization suggests a structure to families of models far richer than has commonly been assumed. Using classical mechanics as an example, it is argued that families of models may be “mapped” as an array with “horizontal” graded structures, multiply hierarchical “vertical” structures, and local “radial” structures. These structures promise important implications for how scientific theories are learned and used in actual scientific practice.