The aim of this paper is modest. It is argued that if the nature of the “equivalence” between first-quantized particle theories and second-quantized (Fock Space) theories is examined closely, if the inadequacies of de Muynck's “indexed particle” version of Fock Space are recognized, and if the question is not begged against modal metaphysics, then van Fraassen's attempted deflation of ontological issues in quantum theory can be seen to fail.

The hidden-variables model constructed by Karl Hess and Walter Philipp is claimed by its authors to exploit a “loophole” in Bell's theorem; according to Hess and Philipp, the parameters employed in their model extend beyond those considered by Bell. Furthermore, they claim that their model satisfies Einstein locality and is free of any “suspicion of spooky action at a distance.” Both of these claims are false; the Hess-Philipp model achieves agreement with the quantum-mechanical predictions, not by circumventing Bell's theorem, but via Parameter Dependence.

Uncertainty about the actual orientation of the measurement device has been claimed to open a loophole for hidden variable models of quantum mechanics. In this paper I describe the statistics of inaccurate spin measurements by unsharp spin observables. A no-go theorem for hidden variable models of the inaccurate measurement statistics follows: There is a finite set of directions for which not all results of inaccurate spin measurements can be predetermined in a non-contextual way. In contrast to an earlier theorem (Breuer 2002) this result does not rely on the assigment of approximate truth values, and it holds under weaker assumptions on the measurement inaccuracy.

In this paper, I investigate the nature of a priori biological laws in connection with the idea that laws must be empirical. I argue that the epistemic functions of a priori biological laws in biology are the same as those of empirical laws in physics. Thus, the requirement that laws be empirical is idle in connection with how laws operate in science. This result presents a choice between sticking with an unmotivated philosophical requirement and taking the functional equivalence of laws seriously and modifying our philosophical account. I favor the latter.

Ecologists typically invoke “law-like” generalizations, ranging over “structural” and/or “functional” kinds, in order to explain generalizations about “historical” kinds (such as biological taxa)—rather than vice versa. This practice is justified, since structural and functional kinds tend to correlate better with important ecological phenomena than do historical kinds. I support these contentions with three recent case studies. In one sense, therefore, ecology is, and should be, more nomothetic, or law-oriented, than idiographic, or historically oriented. This conclusion challenges several recent philosophical claims about the nature of ecological science.

In this paper I defend fundamental physical laws from the arguments mounted by Nancy Cartwright in her (1999) book The Dappled World (and other publications). I argue, positively, that we have a good deal of evidence for mathematical laws—not just causal capacities—underlying many natural phenomena. I also argue, negatively, that Cartwright's main arguments unfairly demand that a fundamentalist be a strong reductionist.

I argue that the orthodox account of probabilistic causation, on which probabilistic causes determine the probability of their effects, is inconsistent with certain ontological assumptions implicit in scientific practice. In particular, scientists recognize the possibility that properties of populations can cause the behavior of members of the populations. Such emergent population-level causation is metaphysically impossible on the orthodoxy.

Hartry Field (1980) has developed an interesting nominalization strategy for Newtonian gravitation theory—a strategy that reformulates the theory without quantification over abstract entities. According to David Malament (1982), Field's strategy cannot be extended to quantum mechanics (QM), and so it only has a limited scope. In a recent work, Mark Balaguer has responded to Malament's challenge by indicating how QM can be nominalized, and by “doing much of the work needed to provide the nominalization” (Balaguer 1998, 114). In this paper, I critically assess Balaguer's proposal, and argue that it ultimately fails. Balaguer's strategy is incompatible with a number of interpretations of QM, in particular with Bas van Fraassen's version of the modal interpretation. And given that Balaguer's strategy invokes physically real propensities, it is unclear whether it is even compatible with nominalism. I conclude that the nominalization of QM remains a major problem for the nominalist.

It is widely acknowledged that the link between quantum language and ordinary language must be “fuzzier” than the traditional eigenstate-eigenvalue link. In the context of spontaneous-collapse theories, Albert and Loewer (1996) argue that the form of this fuzzy link is a matter of convention, and can be freely chosen to minimize anomalies for those theories. I defend the position that the form of the link is empirical, and could be such as to render collapse theories idle. This means that defenders of spontaneous-collapse theories must gamble that the actual form of the link renders such theories tenable.

There exist well-known conundrums, such as measure-theoretic paradoxes and problems of contact, which, within the context of classical physics, can be used to argue against the existence of points in space and space-time. I examine whether quantum mechanics provides additional reasons for supposing that there are no points in space and space-time.

I argue that in the many worlds interpretation of quantum mechanics time has no fundamental direction. I further discuss a way to recover thermodynamics in this interpretation using decoherence theory (Zurek and Paz 1994). Albert's proposal to recover thermodynamics from the collapse theory of Ghirardi et al. (1986) is also considered.

Discussions of representation in science tend to draw on examples from art. However, such examples need to be handled with care given a) the differences between works of art and scientific theories and b) the accommodation of these examples within certain philosophies of art. I shall examine the claim that isomorphism is neither necessary nor sufficient for representation and I shall argue that there exist accounts of representation in both art and science involving isomorphism which accommodate the apparent counterexamples and, moreover, allow us to understand how “impossible” artistic objects and inconsistent scientific theories can be said to represent.

The purpose of this paper is to suggest that models in scientific practice can be conceived of as epistemic artifacts. Approaching models this way accommodates many such things that working scientists themselves call models but that the semantic conception of models does not duly recognize as such. That models are epistemic artifacts implies, firstly, that they cannot be understood apart from purposeful human activity; secondly, that they are somehow materialized inhabitants of the intersubjective field of that activity; and thirdly, that they can function also as knowledge objects. We argue that models as epistemic artifacts provide knowledge in many other ways than just via direct representative links. To substantiate our view we use a language-technological artifact, a parser, as an example.

Ecologist Richard Levins argues population biologists must trade-off the generality, realism, and precision of their models since biological systems are complex and our limitations are severe. Steven Orzack and Elliott Sober argue that there are cases where these model properties cannot be varied independently of one another. If this is correct, then Levins's thesis that there is a necessary trade-off between generality, precision, and realism in mathematical models in biology is false. I argue that Orzack and Sober's arguments fail since Levins's thesis concerns the pragmatic features of model building not just the formal properties of models.

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.