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.

I argue that four of the fundamental claims of those calling themselves ‘genic pluralists’—Philip Kitcher, Kim Sterelny, and Ken Waters—are defective. First, they claim that once genic selectionism is recognized, the units of selection problems will be dissolved. Second, Sterelny and Kitcher claim that there are no targets of selection (interactors). Third, Sterelny, Kitcher, and Waters claim that they have a concept of genic causation that allows them to give independent genic causal accounts of all selection processes. I argue that each one of these claims is either false or misleading. Moreover, the challenge that arises from the availability of genic causal accounts, namely, the inability to choose on rational grounds among genic and higher-level accounts, is unsupported.

Using the occasion of the publication of a Blackwell anthology in the philosophy of technology, Philosophy of Technology: The Technological Condition (2003), as a key to the contemporary role of this subdiscipline, this article reviews the current state-of-this-art. Both philosophy of science and philosophy of technology are twentieth century inventions, but each has followed a somewhat different set of philosophical traditions and pursued sometimes divergent questions. Here the primary developments of recent philosophy of technology are examined with emphasis upon issues which might also be of greater interest to philosophers of science. These include epistemological, but also environmental and cultural issues. The bibliographical spread includes references to some fifty recent books in the field.

Starting from the standard quantum formalism for a single spin$\frac{1}{2}$ system (e.g., an electron), this essay develops a model rich enough not only to afford an explication of symmetry breaking but also to frame questions about how to circumscribe physical possibility on behalf of theories that countenance symmetry breaking.

The alleged problem of “incommensurability” is examined, and attempts to explain scientific change in terms of concepts of meaning and reference are analyzed and rejected. A way of understanding scientific change through a properly developed concept of “reasons” is presented, and the issues of reasons, meaning, and reference are placed in the context of this broader interpretation of scientific change.

In the context of a discussion of time symmetry in the quantum mechanical measurement process, Aharonov et al. (1964) derived an expression concerning probabilities for the outcomes of measurements conducted on systems which have been pre- and postselected on the basis of both preceding and succeeding measurements. Recent literature has claimed that a resulting “time-symmetrized” interpretation of quantum mechanics has significant implications for some basic issues, such as contextuality and determinateness, in elementary, nonrelativistic quantum mechanics. Bub and Brown (1986) have shown that under the standard interpretation of the aforementioned expression, these claims employ ensembles which are not well defined. It is argued here that under a counterfactual interpretation of the expression, these claims may be understood as employing well-defined ensembles; it is shown, however, that such an interpretation cannot be reconciled with the standard interpretation of quantum mechanics.

The main argument of this paper is that an evaluation of the overall explanatory power of a theory is less problematic and more relevant as an assessment of the state of knowledge than evaluation of statistical explanations of single occurrences in terms of likelihoods that are assigned to explananda.

Classically, a gauge potential was merely a convenient device for generating a corresponding gauge field. Quantum-mechanically, a gauge potential lays claim to independent status as a further feature of the physical situation. But whether this is a local or a global feature is not made any clearer by the variety of mathematical structures used to represent it. I argue that in the theory of electromagnetism (or a non-Abelian generalization) that describes quantum particles subject to a classical interaction, the gauge potential is best understood as a feature of the physical situation whose global character is most naturally represented by the holonomies of closed curves in space-time.

Alan Garfinkel (1981) and Bas van Fraassen (1980), among others, have proposed a contrastive theory of explanation, according to which the proper form of an explanatory why-question is not simply “Why P?” but “Why P rather than Q?”. Dennis Temple (1988) has argued in this journal that the contrastive explanandum “P rather than Q” is equivalent to the conjunction, “P and not-Q”. I show that the contrast is not equivalent to the conjunction, nor to other plausible noncontrastive candidates. I then consider David Lewis's (1986) proposal for the way contrasts determine an explanatory cause, which does not require recasting the contrastive explanandum. Lewis's proposal is found to be unacceptable, but it suggests an improvement that shows contrastive explanations to employ a mechanism of “causal triangulation”, similar to Mill's method of difference.

In this article, I first outline the view developed in my recent book on the role of idealization in scientific understanding. I discuss how this view leads to the recognition of a number of kinds of variability among scientific representations, including variability introduced by the many different aims of scientific projects. I then argue that the role of idealization in securing understanding distances understanding from truth but that this understanding nonetheless gives rise to scientific knowledge. This discussion will clarify how my view relates to three other recent books on understanding by Henk de Regt, Catherine Elgin, and Kareem Khalifa.

Natural kinds are often contrasted with other kinds of scientific kinds, especially functional kinds, because of a presumed categorical difference in explanatory value: supposedly, natural kinds can ground explanations, while other kinds of kinds cannot. I argue against this view of natural kinds by examining a particular type of explanation—mechanistic explanation—and showing that functional kinds do the same work there as traditionally recognized natural kinds are supposed to do in “standard” scientific explanations. Breaking down this categorical distinction between traditional natural kinds and other kinds of kinds, I argue, delivers two goods: It provides us with a view of natural kindhood that does justice to the epistemic roles of kinds in scientific explanations. And it allows us to solve a problem that HPC theory, currently one of the more popular accounts of natural kindhood, confronts.

The aim of this article is to develop an argument against metaphysical debates about the existence of human races. I argue that the ontology of race is underdetermined by both empirical and nonempirical evidence owing to a plurality of equally permissible candidate meanings of “race.” Furthermore, I argue that this underdetermination leads to a deflationist diagnosis according to which disputes about the existence of human races are nonsubstantive verbal disputes. While this diagnosis resembles general deflationist strategies in contemporary metaphysics, I show that my argument does not presuppose controversial metametaphysical assumptions.

Drawing on models of communication due to Lewis and Skyrms, I contrast sender-receiver systems as they appear within and between organisms, and as they function in the bridging of space and time. Within the organism, memory can be seen as the sending of messages over time, communication between stages as opposed to spatial parts. Psychological memory and genetic memory are compared with respect to their relations to a sender-receiver model. Some puzzles about “genetic information” can be resolved by seeing the genome as a cell-level memory with no sender.

Sewall Wright and Gustave Malécot developed important theories of isolation by distance. Wright's theory was statistical and Malécot's probabilistic. Because of this mathematical difference, they were not clear about the relationship between their theories. In this paper, I make two points to clarify this relationship. First, I argue that Wright's theory concerns what I call ecological isolation by distance, whereas Malécot's concerns what I call genetic isolation by distance. Second, I suggest that if Wright's theory is interpreted appropriately, a previously unnoticed connection between the two theories emerges.

This paper utilizes Scott domains (continuous lattices) to provide a mathematical model for the use of idealized and approximately true data in the testing of scientific theories. Key episodes from the history of science can be understood in terms of this model as attempts to demonstrate that theories are monotonic, that is, yield better predictions when fed better or more realistic data. However, as we show, monotonicity and truth of theories are independent notions. A formal description is given of the pragmatic virtues of theories which are monotonic. We also introduce the stronger concept of continuity and show how it relates to the finite nature of scientific computations. Finally, we show that the space of theories also has the structure of a Scott domain. This result provides an analysis of how one theory can be said to approximate another.

Standard philosophical discussions of theory-ladeness assume that observational evidence consists of perceptual outputs (or reports of such outputs) that are sentential or propositional in structure. Theory-ladeness is conceptualized as having to do with logical or semantical relationships between such outputs or reports and background theories held by observers. Using the recent debate between Fodor and Churchland as a point of departure, we propose an alternative picture in which much of what serves as evidence in science is not perceptual outputs or reports of such outputs and is not sentential in structure.

Heritability estimates obtained from genome-wide association studies (GWAS) are much lower than those of traditional quantitative methods. This phenomenon has been called the “missing heritability problem.” By analyzing and comparing GWAS and traditional quantitative methods, we first show that the estimates obtained from the latter involve some terms other than additive genetic variance, while the estimates from the former do not. Second, GWAS, when used to estimate heritability, do not take into account additive epigenetic factors transmitted across generations, while traditional quantitative methods do. Given these two points we show that the missing heritability problem can largely be dissolved.

This paper offers an account of data manipulation in scientific experiments. It will be shown that in many cases raw, unprocessed data is not produced, but rather a form of processed data that will be referred to as a data model. The language of data models will be used to provide a framework within which to understand a recent debate about the status of data and data manipulation. It will be seen that a description in terms of data models allows one to understand cases in which data acquisition and data manipulation cannot be separated into two independent activities.

Naive deductive 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 utterly irrelevant to H (and E). Bayesian accounts of confirmation also have this property (in the case of deductive evidence). Several Bayesians have attempted to soften the impact of this fact by arguing that—according to Bayesian accounts of confirmation— E will confirm the conjunction H & X less strongly than E confirms H (again, in the case of deductive evidence). I argue that existing Bayesian “resolutions” of this problem are inadequate in several important respects. In the end, I suggest a new-and-improved Bayesian account (and understanding) of the problem of irrelevant conjunction.