In this paper I show how the conserved quantity theory, or more generally the process theory of Wesley Salmon and myself, provides a sufficient condition in an analysis of causation. To do so I will show how it handles the problem of alleged ‘misconnections’. I show what the conserved quantity theory says about such cases, and why intuitions are not to be taken as sacrosanct.

One of the problems of quantum cosmology follows from the fact that the Hamiltonian H of classical general relativity equals zero. Quantizing canonically in the Schrodinger picture, the Schrodinger equation for the wave function Ψ of the universe is therefore the so-called Wheeler-DeWitt equation (where Ĥ is the operator version of H) and we have no quantum dynamics. In particular, it follows directly that, if Ȓ is the operator representing the radius of the universe, where <Ȓ>ψ = Ψ<|Ȓ|>Ψ, for every Ψ. The universe described by (1) does not expand. But worse still is the fact that there is no time development, contrary to our experience. Like a particle in an eigenstate of zero energy, the state of the universe does not change. The still universe resulting from (1) is a manifestation of the more general “problem of time” afflicting canonical quantum gravity. Despite rare claims to the contrary, most consider it to be a serious difficulty for quantum cosmology.

In a recent essay, John Norton proposes a material theory of induction, according to which all justification for inductive inference ultimately stems from the particular facts of the case at hand. Despite being sympathetic to the pluralistic spirit of this proposal, I argue that central controversies among leading theories of inductive inference turn not on material facts but upon normative judgments regarding the proper standards and aims of induction. Thus, a pluralistic approach to induction can be successfully developed only given an explanation of how the choice of such aims and standards depends on features of particular cases.

Michael Ruse [3] has criticized the distinction between biological function and evolutionary adaptation that I argued for in my article “Biological Adaptation” [2]. I shall show below that Ruse's criticisms are not, for the most part, well taken and that the distinction remains as I made it.

I critically explore various forms of the language of thought (LOT) hypothesis. Many considerations, including the complexity of representational content and the systematicity of language understanding, support the view that some, but not all, of our mental representations occur in a language. I examine several arguments concerning sententialism and the prepositional attitudes, Fodor's arguments concerning infant and animal thought, and Fodor's argument for radical concept nativism and show that none of these considerations require us to postulate a LOT that is innate or otherwise distinct from spoken languages. Instead, I suggest that we maintain the more conservative hypothesis, supported by introspection, that some of our thoughts occur in the languages that we speak.

The four case studies on chance in evolution provide a rich source for further philosophical analysis. Among the issues raised are the following: Are there different conceptions of chance at work, or is there a common underlying conception? How can a given concept of chance be distinguished from other chance concepts and from nonchance concepts? How can the occurrence of a given chance process be distinguished empirically from nonchance processes or other chance processes? What role does chance play in evolutionary theory? I argue that in order to answer these questions, a careful distinction between process and outcome must be made; however, the purpose of this essay is not to answer these questions definitively, but rather to elaborate on them and to provide a starting point for further discussion.

What meaning does epidemiological evidence have for the individual? In evidence-based medicine, epidemiological evidence measures the patient’s risk of the outcome or the change in risk due to an intervention. The patient’s risk is commonly understood as an individual probability. The problem of understanding epidemiological evidence and risk thus becomes the challenge of interpreting individual patient probabilities. I argue that the patient’s risk is interpreted ontically, as a propensity. After exploring formidable problems with this interpretation in the medical context, I propose an epistemic reinterpretation of individual patient probabilities as credences. On this view, epidemiological evidence informs medical uncertainty.

One of the obstacles facing massive modularity is how a pervasively modular mind might generate non-domain-specific thoughts by integrating the content produced by various domain-specific modules. Peter Carruthers has recently argued that the operations of the language faculty are constitutive of the process by which the human mind is able to integrate content from heterogeneous conceptual domains. In this article, I first argue that Carruthers's data do not provide support for either of two possible interpretations of his thesis. In addition, I provide empirical and theoretical reasons for thinking content integration is performed external to the language faculty.

I introduce a distinction between general and local model-data symbiosis and offer three examples of local symbiosis in the fields of meteorology and climate science. Local model-data symbiosis refers to a beneficial, two-way interdependence between a particular model and data set or between closely related models and data sets. For each example presented here, I show how the symbiotic relationship works—what the interdependence consists in and how it is supposed to be beneficial—and I consider whether, alongside the benefits, there is some risk of problematic circularity.

As stochastic independence is essential to the mathematical development of probability theory, it seems that any foundational work on probability should be able to account for this property. Bayesian decision theory appears to be wanting in this respect. Savage’s postulates on preferences under uncertainty entail a subjective expected utility representation, and this asserts only the existence and uniqueness of a subjective probability measure, regardless of its properties. What is missing is a preference condition corresponding to stochastic independence. To fill this significant gap, the article axiomatizes Bayesian decision theory afresh and proves several representation theorems in this novel framework.

On pp. 55–58 of Philosophical Problems of Statistical Inference (Seidenfeld 1979), I argue that in light of unsatisfactory after-trial properties of “best” Neyman-Pearson confidence intervals, we can strengthen a traditional criticism of the orthodox N-P theory. The criticism is that, once particular data become available, we see that the pre-trial concern for tests of maximum power (and for their derivative confidence intervals of shortest expected length) may then misrepresent the conclusion of such a test (or interval estimate). Specifically, I offer a statistical example where there exists a Uniformly Most Powerful test (a UMP-test), a test of highest N-P credentials, which generates a system of “best” confidence intervals (the [CIλ] interval system) with exact confidence coefficients. But the [CIλ] intervals have the unsatisfactory feature that, for a recognizable set of outcomes, the interval estimates cover all parameter values consistent with the data, at strictly less than 100% confidence.

It has been suggested that we can tell whether two theories are equivalent by comparing the structure that they ascribe to the world. If two theories posit different structures, then they must be inequivalent. The aim of this article is to evaluate the extent to which this desideratum holds for the different standards of equivalence that are currently on the table.

The first aim of this paper is to introduce a new way of looking at supertasks in the light of special relativity which makes use of the elementary dynamics of relativistic point particles subjected to elastic binary collisions and constrained to move unidimensionally. In addition, this will enable us to draw new physical consequences from the possibility of supertasks whose ordinal type is higher than the usual ω or ω* considered so far in the literature. Thus, the paper shows how an entire collection of infinitely many particles may place itself spontaneously in motion (mechanical self-acceleration) or even reach the speed of light in a way compatible with special relativity. Interesting implications for classical mechanics are also derived, particularly the possibility of a system of particles disappearing spontaneously in spatial infinity even under the condition of the non-existence of non-collision singularities.

Jaegwon Kim's Mind in a Physical World is an argument about mental causation that provides both a metaphysical theory and a lucid commentary on contemporary philosophical views. While I strongly recommend Kim's book to anyone interested in the subject, my endorsement is not unconditional, because I cannot make the same recomendation of the subject itself. Considering arguments of Davidson, Putnam, Burge, Block, and Kim himself, I conclude that the subject turns on a variety of implausible but received arguments, and that a useful study of mental causation cannot be divorced from scientific details of cognitive psychology, physics, and neuroscience.

Historical inductions, that is, the pessimistic metainduction and the problem of unconceived alternatives, are critically analyzed via John D. Norton’s material theory of induction and subsequently rejected as noncogent arguments. It is suggested that the material theory is amenable to a local version of the pessimistic metainduction, for example, in the context of some medical studies.

Kevin Elliott and Dan McKaughan argue that, in some cases, nonepistemic values provide legitimate reasons for scientists to accept an epistemically inferior option, a claim that they support with two case studies. This essay argues that Elliott and McKaughan have not shown that their case studies are indeed ones in which an epistemically inferior option was accepted. Specifically, their interpretation of these cases depends on problematic premises that it is epistemically better to wait for a slower-but-more-reliable method than to accept the result of a quicker-but-less-reliable one and that a more detailed model is epistemically preferable to a simpler one.

Callender and Cohen have proposed to apply a “Gricean strategy” to the constitution problem of scientific representation. They suggest that scientific representation can be reduced to stipulation by epistemic agents. This account has been criticized for not making a distinction between symbolic and epistemic representation and not taking into account the communal aspects of representation. These criticisms would not apply if Grice’s actual strategy were properly employed. I transpose Grice’s strategy to epistemic representation. The main novelty of the resulting account is a distinction between contextual representational use and general representational status, which I address using the notion of indexicality.

Selectionist evolutionary theory has often been faulted for not making novel predictions that are surprising, risky, and correct. I argue that it in fact exhibits the theoretical virtue of predictive capacity in addition to two other virtues: explanatory unification and model fitting. Two case studies show the predictive capacity of selectionist evolutionary theory: parallel evolutionary change in E. coli and the origin of eukaryotic cells through endosymbiosis.

Rosenberg argues that intentional generalizations in the human sciences cannot be law-like because they are not amenable to significant empirical refinement. This irrefinability is said to result from the principle that supposedly controls in intentional explanation also serving as the standard for successful interpretation. The only credible evidence bearing on such a principle would then need conform to it. I argue that psychological generalizations are refinable and can be nomic. I show how empirical refinement of psychological generalizations is possible by considering concrete cases. A sufficiently detailed view of the role of psychological generalizations in interpretation allows us to find in psychological investigations instances of bootstrap testing.