Confirmation theorists seek to define a function that will take into account the various factors relevant in determining the degree to which an hypothesis is confirmed by its evidence. Among confirmation theorists, only Rudolf Carnap has constructed a system which purports to consider factors in addition to the number of instances, viz. the variety manifested by the instances and the amount of analogy between the instances. It is the purpose of this paper to examine the problem which these additional factors raise for confirmation theory, and to prove that, despite Carnap's claim, no confirmation function satisfying the requirements he has specified can take account of variety and analogy. This result is first proved for a special case, and then, in a subsequent section, is generalized through the introduction of a theorem (the proof of which is given in Appendix I). In the final section of the paper it is shown that, contrary to a claim which Carnap has made, not even the concept of the “logical width” of a predicate will enable confirmation functions satisfying his requirements to take adequate account of analogies between instances.

Developmental systems theory (DST) is often dismissed on the basis that the causal indispensability of nongenetic factors in evolution and development has long been appreciated. A reformulation makes a more substantive claim: that the special role played by genes is also played by some (but not all) nongenetic resources. That special role can be captured by Shea's ‘inherited representation’. Formulating DST as the claim that there are nongenetic inherited representations turns it into a striking, empirically testable hypothesis. DST's characteristic rejection of a gene versus environment dichotomy is preserved but without dissolving into an interactionist casual soup, as some have alleged.

A gas prepared in a nonequilibrium state will approach equilibrium and stay there. An influential contemporary approach to statistical mechanics explains this behavior in terms of typicality. However, this explanation has been criticized as mysterious as long as no connection with the dynamics of the system is established. We take this criticism as our point of departure. Our central claim is that Hamiltonians of gases that are epsilon-ergodic are typical with respect to the Whitney topology. Because equilibrium states are typical, it follows that typical initial conditions approach equilibrium and stay there.

Experimental realism aims at striking a middle ground between scientific realism and anti-realism, between the success of experimental physics it would explain and the realism about scientific theories it would supplant. This middle ground reinstates the engineering idea that belief in scientific entities is justified on purely experimental grounds, without any commitment to scientific theories and laws. This paper argues that there is no defensible middle ground to be staked out when it comes to justifying physicists’ belief in colored quarks, and that experimental realism shifts, under analysis, into scientific realism.

The purpose of this paper is to provide a methodological rather than, strictly speaking, a philosophical discussion of its subject, the logic of concept formation in psychology. But even a treatment of this kind cannot entirely avoid matters of a more general nature, some of them logical, some epistemological. By insisting on the limitations of this essay I merely wish to caution the reader in three respects. First, those more general matters, logical and epistemological, will be kept at a minimum. Second, no attempt will be made to state them with the degree of precision and all the qualifications which are in order in a paper that addresses itself exclusively to logical analysts. Third, I shall for the most part content myself with stating them, without defending them in the way and in the sense in which a technical philosopher who speaks to his colleagues must defend what he asserts.

I offer an explanation of why inertial and gravitational mass are equal in Newtonian gravitation. I then argue that this is an example of a kind of explanation that is not captured by standard philosophical accounts of scientific explanation. Moreover, this form of explanation is particularly important, at least in physics, because demands for this kind of explanation are used to motivate and shape research into the next generation of physical theories. I suggest that explanations of the sort I describe reveal something important about one way in which physical theories may be related diachronically.

This paper is inter-disciplinary. Its disadvantage is that the author is not sufficiently conversant with the disciplines it is inter. He may however, like Lord Wavell, claim that at least the thread that binds them is his own.

The paper is of philosophic interest in that it is inspired by, and hopes to shed some light on, the notion of an ideal language. It is of interest to social anthropology in that its main subject is kinship structure. It may be of interest to mathematicians in setting a task.

This paper is a critique of Kenneth Arrow's thesis concerning the logical impossibility of a constitution. I argue that one of the premises of Arrow's proof, that of the transitivity of indifference, is untenable. Several concepts of preference are introduced and counter-instances are offered to the transitivity of indifference defined along the standard lines in terms of these concepts. Alternate analyses of indifference in terms of preference are considered, and it is shown that these do not serve Arrow's purposes either. Finally, it is argued that in the single special case in which indifference could plausibly be held to be transitive, Arrow's thesis is innocuous.

Naive deductivist accounts of confirmation have the undesirable consequence that if E confirms H, then E also confirms the conjunction H·X, for any X—even if X is completely irrelevant to E and H. Bayesian accounts of confirmation may appear to have the same problem. In a recent article in this journal Fitelson (2002) argued that existing Bayesian attempts to resolve of this problem are inadequate in several important respects. Fitelson then proposes a new-and-improved Bayesian account that overcomes the problem of irrelevant conjunction, and does so in a more general setting than past attempts. We will show how to simplify and improve upon Fitelson's solution.

In seeking general accounts of evidence, confirmation, or inference, philosophers have looked to logical relationships between evidence and hypotheses. Such logics of evidential relationship, whether hypothetico-deductive, Bayesian, or instantiationist fail to capture or be relevant to scientific practice. They require information that scientists do not generally have (e.g., an exhaustive set of hypotheses), while lacking slots within which to include considerations to which scientists regularly appeal (e.g., error probabilities). Building on my co-symposiasts contributions, I suggest some directions in which a new and more adequate philosophy of evidence can move.

The method of Ramsey sentences has been proposed for handling theoretical constructs within a scientific system. Essentially it consists of constructing a certain “monolithic” sentence for an entire theory. In this present paper several improvements are suggested which help to overcome some of the awkward features of the method. In particular we have here many Ramsey sentences rather than just one, each erstwhile primitive theoretical term giving rise to a Ramsey sentence. Such a sentence in effect defines what we call a Ramsey constant. Using Ramsey constants, we attempt to improve the method in important logical and semantical respects. It is suggested also that such constants are of interest for the philosophy of mathematics.

I shall attempt in this paper to give a rounded, if schematic, account of the concept of probability. My central concern will be to clarify the sense in which law-like statements (including ‘statistical’ law-like statements) are made probable by observational data which, in a sense equally demanding analysis, ‘accord’ with them.

Using H. Whitney's algebra of physical quantities and his definition of a similarity transformation, a family of similar systems (R. L. Causey [3] and [4]) is any maximal collection of subsets of a Cartesian product of dimensions for which every pair of subsets is related by a similarity transformation. We show that such families are characterized by dimensionally invariant laws (in Whitney's sense, [10], not Causey's). Dimensional constants play a crucial role in the formulation of such laws. They are represented as a function g, known as a system measure, from the family into a certain Cartesian product of dimensions and having the property gφ = φg for every similarity φ. The dimensions involved in g are related to the family by means of certain stability groups of similarities. A one-to-one system measure is a proportional representing function, which plays an analogous role in Causey's theory, but not conversely. The present results simplify and clarify those of Causey.

This essay sketches an account of extrapolation in terms of analogical reasoning that generalizes the notion of comparative process tracing. The account offered here relies on something known as chain graphs, which are used to explicate the role of “fingerprints,” or distinctive markers, as a strategy for avoiding an underdetermination problem having to do with spurious analogies. Moreover, I show how the extrapolator's circle, one of the central challenges for extrapolation, is closely tied to distinctive markers and the Markov condition as it applies to chain graphs.

Causal relations among components and activities are intentionally misrepresented in mechanistic explanations found routinely across the life sciences. Since several mechanists explicitly advocate accurately representing factors that make a difference to the outcome, these idealizations conflict with the stated rationale for mechanistic explanation. We argue that these idealizations signal an overlooked feature of reasoning in molecular and cell biology—mechanistic explanations do not occur in isolation—and suggest that explanatory practices within the mechanistic tradition share commonalities with model-based approaches prevalent in population biology.

A common complaint against the increasing privatization of research is that research that is conducted with the immediate purpose of producing applicable knowledge will not yield knowledge as valuable as that generated in more curiosity-driven, academic settings. In this paper, I make this concern precise and reconstruct the rationale behind it. Subsequently, I examine the case of industry research on the giant magnetoresistance effect in the 1990s as a characteristic example of research undertaken under considerable pressure to produce applicable results. The example permits one to arrive at a more optimistic assessment of the epistemic merits of private, application-driven research. I attempt to specify the conditions that, in this case, advanced the production of interesting and reliable knowledge.

Recent years have seen increased interest in the question of whether it is possible to provide an evolutionary game-theoretic explanation for certain kinds of social norms. I sketch a proof of a general representation theorem for a large class of evolutionary game-theoretic models played on a social network, in hope that this will contribute to a greater understanding of the long-term evolutionary dynamics of such models, and hence the evolution of social norms.

To infer the state of a cause from the states of its effects, independent lines of evidence are preferable to dependent ones. This familiar idea is here investigated, the goal being to identify its presuppositions. Connections are drawn with Reichenbach's (1956) and Salmon's (1984) discussions of the principle of the common cause.

Inevitably, much of this reply will concern points on which I disagree with one or other of the commentators. I should start, therefore, by saying that I am delighted to find that their thinking is in many ways similar to my own, and that a serious attempt is under way to clarify the concept of information in biology.