Darwin proposed that evolutionary novelties are environmentally induced in organisms “constitutionally” sensitive to environmental change, with selection effective owing to the inheritance of constitutional responses. A molecular theory of inheritance, pangenesis, explained the cross-generational transmission of environmentally induced traits, as required for evolution by natural selection. The twentieth-century evolutionary synthesis featured mutation as the source of novelty, neglecting the role of environmental induction. But current knowledge of environmentally sensitive gene expression, combined with the idea of genetic accommodation of mutationally and environmentally induced change, supports a revival of Darwin's original theory that is consistent with modern molecular and population genetics.

For nearly as long as the word ‘correlation’ has been part of statistical parlance, students have been warned that correlation does not prove causation, and that only experimental studies, e.g., randomized clinical trials, can establish the existence of a causal relationship. Over the last few decades, somewhat of a consensus has emerged between statisticians, computer scientists, and philosophers on how to represent causal claims and connect them to probabilistic relations. One strand of this work studies the conditions under which evidence accumulated from non-experimental (observational) studies can be used to infer a causal relationship. In this paper, I compare the typical conditions required to infer that one variable is a direct cause of another in observational and experimental studies. I argue that they are essentially the same.

A common methodological adage holds that diverse evidence better confirms a hypothesis than does the same amount of similar evidence. Proponents of Bayesian approaches to scientific reasoning such as Horwich, Howson and Urbach, and Earman claim to offer both a precise rendering of this maxim in probabilistic terms and an explanation of why the maxim should be part of the methodological canon of good science. This paper contends that these claims are mistaken and that, at best, Bayesian accounts of diverse evidence are crucially incomplete. This failure should lend renewed force to a long-neglected global worry about Bayesian approaches.

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.

Bayesian, Jeffrey and Field conditionals are compared and it is shown why the last two cannot be reduced to the first. Maximum relative entropy is used in two kinds of justification of the Field conditional and the dispensability of entropy principles in general is discussed.

This article considers a puzzling conflict between two positions that are each compelling: (a) it is irrational for an agent to pay to avoid ‘free’ evidence, and (b) rational agents may have imprecise beliefs. An important aspect of responding to this conflict is resolving the question of how rational (imprecise) agents ought to make sequences of decisions—we make explicit what the key alternatives are and defend our own approach. We endorse a resolution of the aforementioned puzzle—we privilege decision theories that merely permit avoiding free evidence over decision theories that make avoiding free information obligatory.

The ontic conception of explanation, according to which explanations are full-bodied things in the world, is fundamentally misguided. I argue instead for what I call the eikonic conception, according to which explanations are the product of an epistemic activity involving representations of the phenomena to be explained. What is explained in the first instance is a particular conceptualization of the explanandum phenomenon, contextualized within a given research program or explanatory project. I conclude that this eikonic conception has a number of benefits, including making better sense of scientific practice and allowing for the full range of normative constraints on explanation.

A survey of the literature on the problem of the synthetic a priori soon reveals that the term “analytic” is used in a narrower and a broader sense. In the narrower sense, a proposition is analytic if it is either a truth of logic or is logically true. By saying of a proposition that it is logically true, I mean, roughly, and with an eye on the problem of the relation of logical categories to natural languages, that when defined terms are replaced by their definientia, it becomes a substitution instance of a truth of logic. And a truth of logic can be adequately characterized for present purposes as a proposition which occurs in the body of Principia Mathematica, or which would properly occur in a vermehrte und verbesserte Auflage of this already monumental work. If we now agree to extend the convenient phrase “logically true” to cover truths of logic as well as propositions which are logically true in the sense just defined, we can say that an analytic proposition in the narrower sense is a proposition which is logically true.

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.

The syllogism has often been criticized. Yet the theory of the syllogism cannot be omitted from logic. Even if it were not for its historical significance, its nature as a chapter of class logic assigns to it a place in any presentation of logic.

The usual exposition of the theory of the syllogism, however, whether given by the use of the familiar rules of the syllogism, or by the help of diagrams, appears clumsy and lacks the lucidity of modern chapters of logic. The reason seems to be given in the inefficient notation, taken over from ancient and medieval logic. In the following I should like to present an improved notation, which combines some of the traditional features with modern ones, and which is based on the criticism of the syllogistic theory which I have given elsewhere. It will be seen that in the revised form the theory of the syllogism is apt to meet the standards of modern logic.

The relationship between economics and the philosophy of natural science has changed substantially during the last few years. What was once exclusively a one-way relationship from philosophy to economics now seems to be much closer to bilateral exchange. The purpose of this paper is to examine this new relationship. First, I document the change. Second, I examine the situation within contemporary philosophy of science in order to explain why economics might have its current appeal. Third, I consider some of the issues that might jeopardize the success of this philosophical project.

N. Maxwell (1985) has claimed that special relativity and “probabilism” are incompatible; “probabilism” he defines as the doctrine that “the universe is such that, at any instant, there is only one past but many alternative possible futures”. Thus defined, the doctrine is evidently prerelativistic as it depends on the notion of a universal instant of the universe. In this note I show, however, that there is a straightforward relativistic generalization, and that therefore Maxwell's conclusion that the special theory of relativity should be amended is unwarranted. I leave open the question whether or not probabilism (or the related doctrine of the flow of time) is true, but argue that the special theory of relativity has no fundamental significance for this question.

In a number of recent papers I have been developing the theory of “nomic probability,“ which is supposed to be the kind of probability involved in statistical laws of nature. One of the main principles of this theory is an acceptance rule explicitly designed to handle the lottery paradox. This paper shows that the rule can also handle the paradox of the preface. The solution proceeds in part by pointing out a surprising connection between the paradox of the preface and the gambler's fallacy.

John Norton has recently argued that Newtonian gravitation theory (at least as applied to cosmological contexts where one envisions the possibility of a homogeneous mass distribution throughout all of space) is inconsistent. I am not convinced. Traditional formulations of the theory may seem to break down in cases of the sort Norton considers. But the difficulties they face are only apparent. They are artifacts of the formulations themselves, and disappear if one passes to the so-called “geometrized” formulation of the theory.

The availability of unitarily inequivalent representations of the canonical commutation relations constituting a quantization of a classical field theory raises questions about how to formulate and pursue quantum field theory. In a minimally technical way, I explain how these questions arise and how advocates of the Hilbert space and of the algebraic approaches to quantum theory might answer them. Where these answers differ, I sketch considerations for and against each approach, as well as considerations which might temper their apparent rivalry.

Multilevel research strategies characterize contemporary molecular inquiry into biological systems. We outline conceptual, methodological, and explanatory dimensions of these multilevel strategies in microbial ecology, systems biology, protein research, and developmental biology. This review of emerging lines of inquiry in these fields suggests that multilevel research in molecular life sciences has significant implications for philosophical understandings of explanation, modeling, and representation.

Scientific realism is the position that success of a scientific theory licenses an inference to its approximate truth. The argument from pessimistic metainduction maintains that this inference is undermined due to the existence of theories from the history of science that were successful but false. I aim to counter pessimistic metainduction and defend scientific realism. To do this, I adopt a notion of success that admits of degrees and show that our current best theories enjoy far higher degrees of success than any of the successful but refuted theories of the past.

We appeal to the theory of Bayesian Networks to model different strategies for obtaining confirmation for a hypothesis from experimental test results provided by less than fully reliable instruments. In particular, we consider (i) repeated measurements of a single test consequence of the hypothesis, (ii) measurements of multiple test consequences of the hypothesis, (iii) theoretical support for the reliability of the instrument, and (iv) calibration procedures. We evaluate these strategies on their relative merits under idealized conditions and show some surprising repercussions on the variety-of-evidence thesis and the Duhem-Quine thesis.