This paper sketches a taxonomy of forms of substantivalism and relationism concerning space and time, and of the traditional arguments for these positions. Several natural sorts of relationism are able to account for Newton's bucket experiment. Conversely, appropriately constructed substantivalism can survive Leibniz's critique, a fact which has been obscured by the conflation of two of Leibniz's arguments. The form of relationism appropriate to the Special Theory of Relativity is also able to evade the problems raised by Field. I survey the effect of the General Theory of Relativity and of plenism on these considerations.

Proponents of genic selectionism have claimed that evolutionary processes normally viewed as selection on individuals can be “represented” as selection on alleles. This paper discusses the relationship between mathematical questions about the formal requirements upon state spaces necessary for the representation of different types of evolutionary processes and causal questions about the units of selection in such processes.

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.

In this paper I argue three things: (1) that the interactionist view underlying Benacerraf's (1973) challenge to mathematical beliefs renders inexplicable the reliability of most of our beliefs in physics; (2) that examples from mathematical physics suggest that we should view reliability differently; and (3) that abstract mathematical considerations are indispensable to explanations of the reliability of our beliefs.

The critics of “hereditarianism” often claim that any attempt to explain human behavior by invoking genes is confronted with insurmountable methodological difficulties. They reject the idea that heritability estimates could lead to genetic explanations by pointing out that these estimates are strictly valid only for a given population and that they are exposed to the irremovable confounding effects of genotype-environment interaction and genotype-environment correlation. I argue that these difficulties are greatly exaggerated, and that we would be wrong to regard them as presenting a fundamental obstacle to the search for genetic explanations. I also show that, to the extent they are cogent, these objections may prove to be even more damaging to the “environmentalist” standpoint.

The paper claims that analytic philosophy has failed within the philosophy of science due to the way the dynamic aspect of scientific theories is traditionally treated. On the formal side this failure manifests itself in the first-order logical and the model-theoretic analyses of scientific theories. An amendment of the treatment is sketched. It is based on using model generation, of the kind used in proving the Completeness Theorem for first-order logic, in such a way that some dynamic quantities in the dynamic theory are formally represented as functions relating closed terms and sentences to their interpretations in a generated model.

The standard theory of computation excludes computations whose completion requires an infinite number of steps. Malament-Hogarth spacetimes admit observers whose pasts contain entire future-directed, timelike half-curves of infinite proper length. We investigate the physical properties of these spacetimes and ask whether they and other spacetimes allow the observer to know the outcome of a computation with infinitely many steps.

Arguments favoring the existence of extraterrestrial intelligence nearly always contain an overt appeal to big numbers, often combined with a covert reliance on generalization from a single instance. In this paper I examine both motifs, and consider whether big numbers might actually make palatable otherwise implausible single-case inductions. In the end, the dispute between believers and skeptics is seen to boil down to a conflict of intuitions which can barely be engaged, let alone resolved, given our present state of knowledge.

According to Mohan Matthen and Edwin Levy, certain immunological processes require explanations in which the immune system is attributed intentional states. This, they think, strengthens the scientific credentials of intentional psychology and undermines the position of those who argue that the scientific treatment of human action should involve the elimination of intentional description. In this paper, I argue that immunology does not and need not employ intentional explanation or description and consequently has nothing to offer those who seek to defend the scientific standing of intentional psychology by looking for other disciplines that “accommodate the intentional”.

When philosophers and psychologists think about consciousness, they generally focus on one or more of three features: phenomenality (how experiences feel), intentionality (that experiences are “of” something, that experiences mean something), and introspectibility (our awareness of the phenomenality and intentionality of experience). Using examples from empirical psychology and neuroscience, I argue that consciousness is not a unitary state, that, instead, these three features characterize different and dissociable states, which often happen to occur together. Understanding these three features as dissociable from each other will resolve philosophical disputes and facilitate scientific investigation.

Although accounts of evolutionary altruism which leave the question of whether altruism can evolve in nature open to empirical confirmation/refutation have been worked out for special (two-trait) cases, no real effort has been made to work out such accounts for general (N-trait) cases. It is tempting to take this lack of attention as evidence for an inextricably conventional element, which precludes such accounts from being of practical scientific value. I argue that such accounts do generalize in a natural way. As is often the case in science, generalizing theoretically simplified notions is not straightforward because of issues hidden in the special case. These issues do not, however, turn out to be essentially conventional.

This paper considers definitions of classical dynamical chaos that focus primarily on notions of predictability and computability, sometimes called algorithmic complexity definitions of chaos. I argue that accounts of this type are seriously flawed. They focus on a likely consequence of chaos, namely, randomness in behavior which gets characterized in terms of the unpredictability or uncomputability of final given initial states. In doing so, however, they can overlook the definitive feature of dynamical chaos—the fact that the underlying motion generating the behavior exhibits extreme trajectory instability. I formulate a simple criterion of adequacy for any definition of chaos and show how such accounts fail to satisfy it.

This essay defends two theses that jointly establish a link between causal and explanatory asymmetry. The first thesis is that statements specifying facts about effects, unlike statements specifying facts about causes, are not “independently variable”. The second thesis is that independent variability among purportedly explanatory factors is a necessary condition on scientific explanations.

Neurath's proposal for the form of protocol statements explicates the multiple embedding of a singular sentence as specifying different conditions for the acceptance of such a sentence as a bona fide scientific datum. Before theories are accepted or rejected in the light of such evidence, however, a further condition must be met which Neurath did not formalize. The different conditions are discussed and shown to constitute a naturalistic theory of scientific data and a pragmatic theory of theory acceptance.

I argue that, contrary to some critics, the notion of conscious experience is a good candidate for denoting a distinct and scientifically interesting phenomenon in the brain. I base this claim mainly on an analysis of neuropsychological data concerning deficits resulting from various types of brain damage as well as some additional supporting empirical evidence. These data strongly point to the hypothesis that conscious experience expresses information that is available for global, integrated, and flexible behavior.

There is a growing acceptance of the idea that the explanatory states of folk psychology do not supervene on the physical. Even Fodor (1987) seems to grant as much. He argues, however, that this cannot be true of theoretical psychology. Since theoretical psychology offers causal explanations, its explanatory states must be taxonomized in such a way as to supervene on the physical. I use this concession to invert his argument and cast doubt on the received model of folk psychological explanation as causal explanation by intentionally individuated states. This in turn undermines the central model of cognitive theory—causal explanation by representational states.

I propose an approach to naturalized philosophy of science that takes the social nature of scientific practice seriously. I criticize several prominent naturalistic approaches for adopting “cognitive individualism”, which limits the study of science to an examination of the internal psychological mechanisms of scientists. I argue that this limits the explanatory capacity of these approaches. I then propose a three-level model of the social nature of scientific practice, and use the model to defend the claim that scientific knowledge is socially produced.

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.

According to Marr's theory of vision, computational processes of early vision rely for their success on certain “natural constraints” in the physical environment. I examine the implications of this feature of Marr's theory for the question whether psychological states supervene on neural states. It is reasonable to hold that Marr's theory is nonindividualistic in that, given the role of natural constraints, distinct computational theories of the same neural processes may be justified in different environments. But to avoid trivializing computational explanations, theories must respect methodological solipsism in the sense that within a theory there cannot be differences in content without a corresponding difference in neural states.

Butterfield's (1992a,b,c) claim of the equivalence of absence of Lewisian probabilistic counterfactual causality (LC) to Hellman's stochastic Einstein locality (SEL) is questioned. Butterfield's assumption on which the proof of his claim is based would suffice to prove that SEL implies absence of LC also for appropriately given versions of these notions in algebraic quantum field theory, but the assumption is not an admissible one. The conclusion must be that the relation of SEL and absence of LC is open, and that they may be independent.