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.

Standard models of statistical explanation face two intractable difficulties. In his 1984 Salmon argues that because statistical explanations are essentially probabilistic we can make sense of statistical explanation only by rejecting the intuition that scientific explanations are contrastive. Further, frequently the point of a statistical explanation is to identify the etiology of its explanandum, but on standard models probabilistic explanations often fail to do so. This paper offers an alternative conception of statistical explanations on which explanations of the frequency of a property consist in the derivation of that frequency from a statistical specification of the mechanism by which instances of the relevant property are produced. Such explanations are contrastive precisely because they identify the determinate causal etiologies of their explananda.

Daniel Steel argues that a causal theory of explanation can account for Ferguson's anthropological theory of Yanomami warfare but that a unification theory of explanation cannot. I argue that a unification theory can explain such an account, in a manner similar to Hempel's view of explanation in history. I go on to argue that the unification theory allows for different explanations of specific and general social circumstances.

Laws are supposed to tell us how physical systems actually behave. The analysis of an important part of physical practice—abstraction—shows, however, that laws describe the behavior of physical systems under very special circumstances, namely when they are isolated. Nevertheless, laws are applied in cases of non-isolation as well. This practice requires an explanation. It is argued that one has to assume that physical systems have dispositions. I take these to be innocuous from an empiricist's standpoint because they can—at least in principle—be measured. Laws can be applied whenever such a disposition is present, they describe how the physical system would behave if the disposition were manifest.

1. Ramsey Sentences and the Function of Theoretical Concepts. In his famous paper “Theories,” Frank Ramsey (1931, 212–236; 1978, Ch. 4) introduced a technique of examining a scientific theory by means of certain propositions, dubbed later “Ramsey Sentences.” They are the results of what is often called Ramsey elimination. This prima facie elimination is often presented as a method of dispensing with theoretical concepts in scientific theorizing. The idea is this: Assume that we are given a finitely axiomatized scientific theory

where O1, O2, … are the primitive observation terms (individual constants, predicate constants, function constants, etc.) of (1) and H1, H2, … its primitive theoretical terms. For simplicity, it will be assumed that (1) is a first-order theory. Since it is finitely axiomatizable, we may think of it as having the form of a single complex proposition, i.e., the conjunction of all the axioms. What can then be done is to generalize existentially with respect to (1). The result is a sentence of the form

In (2), the theoretical terms H1, H2, … do not occur any longer. They have been replaced by the variables X1, X2, … bound to initial existential quantifiers. In this sense at least, Ramsey sentences do effect on elimination. Unlike (1), (2) is not a first-order sentence but a second-order one.

This paper concerns the ways in which one can/cannot combine extensive quantities. Given a particular theory of extensive measurement, there can be no alternative ways of combining extensive quantities, where ‘alternative’ means that one combining operation can be used instead of another causing only a change in the number assigned to the quantity. As a consequence, rectangular concatenation cannot be an alternative combining operation for length as was suggested by Ellis and agreed by Krantz, Luce, Suppes, and Tversky. I argue as well that a theory which imposes such restrictions on the combining operation is more desirable than less stringent rival theories.

Information theory offers a measure of “mutual information” which provides an appropriate measure of tracking efficiency for the naturalistic epistemologist. The statistical entropy on which it is based is arguably the best way of characterizing the uncertainty associated with the behavior of a system, and it is ontologically neutral. Though not appropriate for the naturalization of meaning, mutual information can serve as a measure of epistemic success independent of semantic maps and payoff structures. While not containing payoffs as terms, mutual information places both upper and lower bounds on payoffs. This constitutes a non-trivial relationship to utility.

This paper is an empirical critique of causal accounts of scientific explanation. Drawing on explanations which rely on nonlinear dynamical modeling, I argue that the requirement of causal relevance is both too strong and too weak to be constitutive of scientific explanation. In addition, causal accounts obscure how the process of mathematical modeling produces explanatory information. I advance three arguments for the inadequacy of causal accounts. First, I argue that explanatorily relevant information is not always information about causes, even in cases where the explanandum has an identifiable causal history. Second, I argue that treating theoretical explanations as reductions from general causal laws does not accurately describe the types of “top-down” explanations typical of dynamical modeling. Finally, I argue that causal/mechanical accounts of explanation are intrinsically vulnerable to the irrelevance problem.

Huggett and Weingard's critical review provides an opportunity to continue the interpretive examination of quantum field theory in terms of some specific issues as well as comparison of alternative approaches to the subject. This note recasts their example of inequivalent Fock spaces in an effort to further clarify what it illustrates. Questions are addressed about the role of analogy in developing quantum field theory and about the conflict between formal vs. concrete methods in both physics and its interpretation, continuing the well-known historical debate between Pierre Duhem and Clark Maxwell. Huggett and Weingard's examination very usefully occasions clarification on some points of exposition which, it is hoped, will make An Interpretive Introduction to Quantum Field Theory a more useful resource for understanding this subject.

The first aim of this paper is to introduce a new way of looking at supertasks in the light of special relativity which makes use of the elementary dynamics of relativistic point particles subjected to elastic binary collisions and constrained to move unidimensionally. In addition, this will enable us to draw new physical consequences from the possibility of supertasks whose ordinal type is higher than the usual ω or ω* considered so far in the literature. Thus, the paper shows how an entire collection of infinitely many particles may place itself spontaneously in motion (mechanical self-acceleration) or even reach the speed of light in a way compatible with special relativity. Interesting implications for classical mechanics are also derived, particularly the possibility of a system of particles disappearing spontaneously in spatial infinity even under the condition of the non-existence of non-collision singularities.

Why does classical equilibrium statistical mechanics work? Malament and Zabell (1980) noticed that, for ergodic dynamical systems, the unique absolutely continuous invariant probability measure is the microcanonical. Earman and Rédei (1996) replied that systems of interest are very probably not ergodic, so that absolutely continuous invariant probability measures very distant from the microcanonical exist. In response I define the generalized properties of epsilon-ergodicity and epsilon-continuity, I review computational evidence indicating that systems of interest are epsilon-ergodic, I adapt Malament and Zabell's defense of absolute continuity to support epsilon-continuity, and I prove that, for epsilon-ergodic systems, every epsilon-continuous invariant probability measure is very close to the microcanonical.

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.

A superselection rule advanced in the course of a quantum-mechanical treatment of some phenomenon is an assertion to the effect that the superposition principle of quantum mechanics is to be restricted in the application at hand. Superselection accounts of measurement all have in common a decision to represent the indicator states of detectors by eigenspaces of superselection operators named in a superselection rule, on the grounds that the states in question are states of a so-called classical quantity and therefore not subject to quantum interference effects. By this strategy superselectionists of measurement expect to dispense with use of projection postulates in treatments of measurement. I shall argue that superselection accounts of measurement are self-contradictory, and that treatments of infinite systems, if they can avoid the contradiction, are not true superselection accounts.

The Facts of Causation claims to be a “complete account of causation and its implications.” Mellor's concern is with singular causation; that is, where causes and effects are singular (he takes general causation to be a generalization concerning singular causation (pp. 6–7)). Singular causes and effects come in two sorts. Firstly, there are facts. Facts are actual states of affairs, and states of affairs correlate with whatever can be expressed in a sentence (so facts correlate with whatever can be expressed in a true sentence) (8–9). For example, that Don falls and that Don dies are facts, if actual. In general terms, the causation of one fact, E, by another, C, fits under the designation ‘E, because C’.

Born to Rebel (Sulloway 1996) is an innovative and important work with much to say to philosophers of science, as well as historians and sociologists of science. Sulloway uses, successfully, quantitative statistical methods that others have despaired of using to analyze the complexities of historical change. In particular, he investigates scientific decision-making during scientific controversies with a multivariate analysis. The goal is to discern, precisely, the contribution of factors such as religious belief, social class, age, years of education, nationality, sex and personality.

This article considers the recent work of David Lewis, Ned Hall, and Michael Thau on chance and the best system account of law. My rejoinder suggests that, though their proposals may succeed at the stated goal of reworking the problematic relationship between chance, credence, and law, the resulting account of law suffers from an even more significant difficulty. To oversimplify a bit, I argue that their account is unable to handle the nomic necessity of laws. My criticisms suggest an alternative account of law which provides, I argue, a preferable account of nomic necessity.