The United Kingdom Climate Impacts Program’s UKCP09 project makes high-resolution forecasts of climate during the twenty-first century using state of the art global climate models. The aim of this article is to introduce and analyze the methodology used and then urge some caution. Given the acknowledged systematic errors in all current climate models, treating model outputs as decision-relevant probabilistic forecasts can be seriously misleading. This casts doubt on our ability, today, to make trustworthy, high-resolution predictions out to the end of this century.

Discussions of the interpretation of quantum theory are at present obstructed by (1) the increasing axiomania in physics and philosophy which replaces fundamental problems by problems of formulation within a certain preconceived calculus, and (2) the decreasing (since 1927) philosophical interest and sophistication both of professional physicists and of professional philosophers which results in the replacement of subtle positions by crude ones and of dialectical arguments by dogmatic ones. More especially, such discussions are obstructed by the ignorance of both opponents, and also defenders of the Copenhagen point of view, as regards the arguments which once were used in its defence. The publication of Bunge's Quantum Theory and Reality and especially of Popper's contribution to it are taken as an occasion for the restatement of Bohr's position and for the refutation of some quite popular, but surprisingly naive and uninformed objections against it. Bohr's position is distinguished both from the position of Heisenberg and from the vulgarized versions which have become part of the so-called “Copenhagen Interpretation” and whose inarticulateness has been a boon for all those critics who prefer easy victories to a rational debate. Einstein's main counterargument is discussed, and Bohr's refutation restated. The philosophical background and earlier forms of Bohr's views are stated also. Considering that these views are more detailed, better adapted to the facts of the microdomain than any existing alternative it follows that fundamental discussion must first return to them. Their uniqueness is not asserted, however. Here the author still maintains that a hundred shabby flowers are preferable to a single blossom, however exquisite. But a hundred shabby flowers plus an exquisite blossom are more desirable still.

Race is a prominent category in medicine. Epidemiologists describe how rates of morbidity and mortality vary with race, and doctors consider the race of their patients when deciding whether to test them for sickle-cell anemia or what drug to use to treat their hypertension. At the same time, critics of racial classification say that race is not real but only an illusion or that race is scientifically meaningless. In this paper, I explain how race is used in medicine as a proxy for genes that encode drug metabolizing enzymes and how a proper understanding of race calls into doubt the practice of treating race as a marker of any medically relevant genetic trait.

For Savage (1954) as for de Finetti (1974), the existence of subjective (personal) probability is a consequence of the normative theory of preference. (De Finetti achieves the reduction of belief to desire with his generalized Dutch-Book argument for previsions.) Both Savage and de Finetti rebel against legislating countable additivity for subjective probability. They require merely that probability be finitely additive. Simultaneously, they insist that their theories of preference are weak, accommodating all but self-defeating desires. In this paper we dispute these claims by showing that the following three cannot simultaneously hold:

(i) Coherent belief is reducible to rational preference, i.e. the generalized Dutch-Book argument fixes standards of coherence.

(ii) Finitely additive probability is coherent.

(iii) Admissible preference structures may be free of consequences, i.e. they may lack prizes whose values are robust against all contingencies.

Recent accounts of scientific method suggest that a model, or analogy, for an axiomatized theory is another theory, or postulate set, with an identical calculus. The present paper examines five central theses underlying this position. In the light of examples from physical science it seems necessary to distinguish between models and analogies and to recognize the need for important revisions in the position under study, especially in claims involving an emphasis on logical structure and similarity in form between theory and analogy. While formal considerations are often relevant in the employment of an analogy they are neither as extensive as proponents of this viewpoint suggest, nor are they in most cases sufficient for allowing analogies to fulfill the roles imputed to them. Of major importance, and what these authors generally fail to consider, are physical similarities between analogue and theoretical object. Such similarities, which are characteristic in varying degrees of most analogies actually employed, play an important role in affording a better understanding of concepts in the theory and also in the development of the theoretical assumptions.

Figuring prominently in their decisions regarding which theories to pursue are scientists' appeals to the promise or lack of promise of those theories. Yet philosophy of science has had little to say about how one is to assess theory promise. This essay identifies several indices that might be consulted to determine whether or not a theory is promising and worthy of pursuit. Various historical examples of appeals to such indices are introduced.

In many texts on evolution the reader will find a characteristic depiction of inheritance and evolution, one showing the generations of an evolving population linked only by a causal flow from genotype to genotype. On this view, the genotype of each organism in this population plays a dual role as both the motor of individual development and as the sole causal channel across the generations (cf., e.g., Maynard Smith 1993, Fig. 8). This picture is known to be literally false. In many species, parents exert direct causal influence on their offspring, and some of those influences cause the offspring to resemble the parent. For example, a butterfly that lays her eggs on the same plant host on which she hatched thereby exerts a causal influence on her offspring, and one apt to cause them to resemble her more than they would, had she chosen a plant of a different species. None of this is at all controversial, but it poses a puzzle. If the “Weissmanian” conception is literally false, why is it seen as a perspicacious representation of evolution?

Exploratory statistics represents the transformation of a realist theory of statistics held by early nineteenth-century astronomers into an empiricist theory of statistics held by biometricians at the turn of the twentieth century. This paper discusses four key ideas in empiricist thought that influenced the form exploratory statistics took: (1) Baconianism, (2) associationism, (3) the search for cognitive calculi, and (4) phenomenalism.

Some limitations of and alternatives to exploratory statistics as a hypothesis-generating methodology are discussed.

The paper presents a simulation of the dynamics of impersonal trust. It shows how a “trust and reciprocate” norm can emerge and stabilize in populations of conditional cooperators. The norm, or behavioral regularity, is not to be identified with a single strategy. It is instead supported by several conditional strategies that vary in the frequency and intensity of sanctions.

Empirical adequacy, formal explanation and understanding are distinct goals of science. While no a priori criterion for understanding should be laid down, there may be inherent limitations on the way we are able to understand explanations of physical phenomena. I examine several recent contributions to the exercise of fashioning an explanatory discourse to mold the formal explanation provided by quantum mechanics to our modes of understanding. The question is whether we are capable of truly understanding (or comprehending) quantum phenomena, as opposed to simply accepting the formalism and certain irreducible quantum correlations. The central issue is that of understanding versus merely redefining terms to paper over our ignorance.

A general form is proposed for epistemological theories, the relevant factors being: the family of epistemic judgments, the epistemic state, the epistemic commitment (governing change of state), and the family of possible epistemic inputs (deliverances of experience). First a simple theory is examined in which the states are probability functions, and the subject of probability kinematics introduced by Richard Jeffrey is explored. Then a second theory is examined in which the state has as constituents a body of information (rational corpus) and a recipe that determines the accepted epistemic judgments on the basis of this corpus. Through an examination of several approaches to the statistical syllogism, a relation is again established with Jeffrey's generalized conditionalization.

This paper consists of two parts. In Part I, an attempt to get around certain well-known criticisms of the trace theory of memory is discussed. Part II consists of an account of the so-called “logical” notion of a memory trace.

Trace theories are sometimes thought to be empirical hypotheses about the functioning of memory. That this is not the case, that trace theories are in fact philosophical theories, is shown, I believe, in the arguments which follow. If this is so, one may well wonder about psychologists' insistence that any empirical theory of memory must involve the postulation of traces (or trace-like entities: engrams, schemata, etc.).

In this article, we provide a case study examining how integrative systems biologists build simulation models in the absence of a theoretical base. Lacking theoretical starting points, integrative systems biology researchers rely cognitively on the model-building process to disentangle and understand complex biochemical systems. They build simulations from the ground up in a nest-like fashion, by pulling together information and techniques from a variety of possible sources and experimenting with different structures in order to discover a stable, robust result. Finally, we analyze the alternative role and meaning theory has in systems biology expressed as canonical template theories like Biochemical Systems Theory.

This article agrees with Philip Kitcher that we should aim for a well-ordered science, one that answers the right questions in the right ways. Crucial to this is to address questions of use: Which scientific account is right for which system in which circumstances? This is a difficult question: evidence that may support a scientific claim in one context may not support it in another. Drawing on examples in physics and other sciences, this article argues that work on the warrant of theories in philosophy of science needs to change. Emphasis should move from the warrant of theories in the abstract to questions of evidence for use.

The representation theorems of expected utility theory show that having certain types of preferences is both necessary and sufficient for being representable as having subjective probabilities. However, unless the expected utility framework is simply assumed, such preferences are also consistent with being representable as having degrees of belief that do not obey the laws of probability. This fact shows that being representable as having subjective probabilities is not necessarily the same as having subjective probabilities. Probabilism can be defended on the basis of the representation theorems only if attributions of degrees of belief are understood either antirealistically or purely qualitatively, or if the representation theorems are supplemented by arguments based on other considerations (simplicity, consilience, and so on) that single out the representation of a person as having subjective probabilities as the only true representation of the mental state of any person whose preferences conform to the axioms of expected utility theory.

This paper describes a theory of accuracy or approximate truth and applies it to problems in the realist interpretation of scientific theories. It argues not only that realism requires approximate truth, but that an adequate theory of approximation also presupposes some elements of a realist interpretation of theories.

The paper distinguishes approximate truth from vagueness, probability and verisimilitude, and applies it to problems of confirmation and deduction from inaccurate premises. Basic results are cited, but details appear elsewhere. Objections are surveyed, including arguments by Miller, Laymon, and Laudan. Comparison is made with Niiniluoto's theory of verisimilitude, and the utility of his theory for realism assessed.

The main puzzle about theoretical definitions is that nothing seems to decide which assumptions contribute to such definitions and which do not. I argue that theoretical definitions are indeed imprecise, but that this does not normally matter, since the definitional imprecision does not normally produce indeterminacy of referential value. Sometimes, however, the definitional imprecision is less benign, and does generate referential indeterminacy. In these special cases, but not otherwise, it is necessary to refine the term's definition.

Halvorson argues through a series of examples and a general result due to Myers that the “semantic view” of theories has no available account of formal theoretical equivalence. De Bouvere provides criteria overlooked in Halvorson’s paper that are immune to his counterexamples and to the theorem he cites. Those criteria accord with a modest version of the semantic view that rejects some of Van Fraassen’s apparent claims while retaining the core of Patrick Suppes’s proposal. I do not endorse any version of the semantic view of theories.

Confirmation is commonly identified with positive relevance, E being said to confirm H if and only if E increases the probability of H. Today, analyses of this general kind are usually Bayesian ones that take the relevant probabilities to be subjective. I argue that these subjective Bayesian analyses are irremediably flawed. In their place I propose a relevance analysis that makes confirmation objective and which, I show, avoids the flaws of the subjective analyses. What I am proposing is in some ways a return to Carnap's conception of confirmation, though there are also important differences between my analysis and his. My analysis includes new accounts of what evidence is and of the indexicality of confirmation claims. Finally, I defend my analysis against Achinstein's criticisms of the relevance concept of confirmation.