Jerry Fodor has recently proposed a new entry into the list of information based approaches to semantic content aimed at explicating the general notion of representation for both mental states and linguistic tokens. The basic idea is that a token means what causes its production. The burden of the theory is to select the proper cause from the sea of causal influences which aid in generating any token while at the same time avoiding the absurdity of everything's being literally meaningful (since everything has a cause). I argue that a detailed examination of the theory reveals that neither burden can be successfully shouldered.

The framework of Solomonoff prediction assigns prior probability to hypotheses inversely proportional to their Kolmogorov complexity. There are two well-known problems. First, the Solomonoff prior is relative to a choice of universal Turing machine. Second, the Solomonoff prior is not computable. However, there are responses to both problems. Different Solomonoff priors converge with more and more data. Further, there are computable approximations to the Solomonoff prior. I argue that there is a tension between these two responses. This is because computable approximations to Solomonoff prediction do not always converge.

Climate scientists frequently employ heavily idealized models. How should these models be interpreted? Some philosophers have advanced a possibilist interpretation: climate models stand in for possible scenarios that could occur but do not provide information about how probable those scenarios are. This article argues that possibilism is (1) undermotivated, (2) incompatible with successful practices in the science, and (3) unable to correct for known biases. The upshot is that the models should be interpreted probabilistically in at least some cases.

Sexes are normally taken to be fundamental categories in biology—many sexually reproducing organisms fall under the categories of female/male. Much research aims at explaining differences between sexes. Sexual selection forms a central framework for explaining “typical” distributions of traits among sexes and explicating circumstances leading to “reversal.” I claim that sexual selection models need not make use of sexes and that sexes lack explanatory significance in such models. I offer a framework of reproductive dimorphism and argue that it is better than that of sexes because it (1) is more compatible with explanations of sexual selection and (2) allows for their greater applicability.

Describing a physical system in idealized terms involves making claims about the system that we know to be literally false. Because of this, it is not clear how calculations involving idealizations can generate justified belief and explain facts about the world. I argue that this puzzling aspect of idealizations cannot be explained away by talking about approximations, as is often supposed. I develop a different account of how justified beliefs and explanations can be generated from idealized descriptions of physical systems. My account involves a type of contextualism about the truth of mathematical descriptions of physical systems.

This is an interesting, well argued, and highly readable book; anyone interested in the central philosophical problems with which it deals will benefit from studying it.

Stalnaker defines inquiry as the process of forming, testing, and revising beliefs. His goal is to lay the groundwork for a theory of inquiry, by elaborating and defending a certain apparatus in terms of which the process of inquiry should be described.

Charlotte Werndl and Roman Frigg discuss the relationship between the Boltzmannian and Gibbsian framework of statistical mechanics, addressing, in particular, the question when equilibrium values calculated in both frameworks agree. This note points out conceptual confusions that could arise from their discussion, concerning, in particular, the authors’ use of “Boltzmann equilibrium.” It also clarifies the status of the Khinchin condition for the equivalence of Boltzmannian and Gibbsian equilibrium predictions and shows that it follows, under the assumptions proposed by Werndl and Frigg, from standard arguments in probability theory.

The contentions of this paper are essentially two. One is that truth does not consist of verifiability—and still less of verification—in the sense in which this has been maintained by some pragmatists, operationalists, and positivists. The other is that in a certain other sense of “verifiability”, which will be described, truth is the same thing as verifiability. The paper, it should be understood, attempts only to make clear what is and what is not the relation between truth and verifiability. It does not attempt in addition to carry the analysis of verification itself to the point where it would, by implication, furnish a terminal answer to the question, what is truth. The latter task, because of space limitations, must be reserved for some future occasion.

In Science, Truth, and Democracy, Philip Kitcher challenges the view that science has a single, context-independent, goal, and that the pursuit of this goal is essentially immune from moral critique. He substitutes a context-dependent account of science's goal, and shows that this account subjects science to moral evaluation. I argue that Kitcher's approach must be modified, as his account of science ultimately must be explicated in terms of moral concepts. I attempt, therefore, to give an account of science's goal that is free of direct moral entanglements but still makes this goal context-dependent and leaves the choice of which projects to pursue subject to moral scrutiny.

The meaning of consciousness (i.e. the mind-brain problem), has interested thinkers throughout recorded time, and yet it is quite obvious that its understanding is still exceedingly remote. This is evident from the fact that even the presently used definitions give rise to contradictions. As implied by the title, the purpose of this paper is to remove some of the main difficulties concerned with this definition by using epistemological methods which have recently been developed. It is hoped that by clarifying the definition of consciousness, or, more accurately, by clarifying the process leading to a scientifically rigorous definition of consciousness, some of the paradoxes surrounding the concept might be removed.

Based on the historical case of galvanic experimentation in Germany, I identify five types of experimentation which explored and shaped the new phenomenon rather than tested theoretical predictions. Verification evaluated initial reports of Galvani's phenomenon. Simplification reduced the experimental protocol to the fewest and most basic steps. Optimization found experimental conditions that magnified the observed effect. Exploration tested a wide variety of metals, animals or configurations. Application modified the experiment to address unresolved related problems. Attempts to derive laws of the phenomenon or establish its underlying causes were unsuccessful primarily due to the great variability of the experimental results.

Contemporary empiricism has attempted to ground its analysis of science in a falsificationism based in selection theory. This paper links these evolutionary epistemologies with commitments to certain epistemological and ontological assumptions found in the later work of K. Popper, D. Campbell, and D. Hull. I argue that their assumptions about the character of contemporary empiricism are part of a shared paradigm of epistemological explanation which results in unresolved tensions within their own projects. I argue further that their claim to be doing a science of science is not defensible. Hull's selectionism is analyzed to show how this epistemological agenda has played itself out in late empiricism. I suggest some directions that Hull might take toward an historical epistemology.

The use that the scientist makes of his principles is well known. In the normal course of scientific investigation, a hypothesis which explains some physical phenomenon adequately in every particular, but which runs counter to, say, the laws of inertia, cannot be held without further experimentation. Such experimentation must continue until the irreconcilability of the hypothesis with the laws is resolved. In most cases the hypothesis will fail to submit to further tests, will be declared inadequate, and will give way to a new one.

This paper attempts to place Goodman's “New Riddle of Induction” within the context of a subjectivist understanding of inductive logic. It will be argued that predicates such as ‘grue’ cannot be denied projectible status in any a priori way, but must be considered in the context of a situation of inductive support. In particular, it will be argued that questions of projectibility are to be understood as a variety of questions about the ways a given sample is random. Various examples are considered, including cases when ‘grue’ (as opposed to 'green') should be projected, and some remarks are offered on what is meant when it is claimed that a sample is random (in ways relevant to inductive support) and how such randomness is determined. The view presented helps to make clear the relation between such apparently non-projectible predicates as 'grue' and the concept of being examined.

When an experimenter uses the experimental method to investigate the effects of the experimenter's expectancy it may be that this research, too, is affected by his expectancy and thus there is an expectancy paradox. To the extent that the experimenter expectancy effect accounts for the variation in the dependent variable and is general, that is to say, universal in psychological research, the expectancy paradox is ineluctable. However, an analysis of the research reviews extant in this area yields the conclusion that expectancy effects are neither inexorable nor highly general in psychological research and this provides the basis for its extrication from the expectancy paradox.