Most philosophical accounts of emergence are incompatible with reduction. Most scientists regard a system property as emergent relative to properties of the system's parts if it depends upon their mode of organization—a view consistent with reduction. Emergence can be analyzed as a failure of aggregativity—a state in which “the whole is nothing more than the sum of its parts.” Aggregativity requires four conditions, giving tools for analyzing modes of organization. Differently met for different decompositions of the system, and in different degrees, these conditions provide powerful evaluation criteria for choosing decompositions, and heuristics for detecting biases of vulgar reductionisms. This analysis of emergence is compatible with reduction.

The so-called “adaptationism” of mainstream evolutionary biology has been criticized from a variety of sources. One, which has received relatively little philosophical attention, is developmental biology. Developmental constraints are said to be neglected by adaptationists. This paper explores the divergent methodological and explanatory interests that separate mainstream evolutionary biology from its embryological and developmental critics. It will focus on the concept of constraint itself; even this central concept is understood differently by the two sides of the dispute.

What is the relation between coherence and truth? This paper rejects numerous answers to this question, including the following: truth is coherence; coherence is irrelevant to truth; coherence always leads to truth; coherence leads to probability, which leads to truth. I will argue that coherence of the right kind leads to at least approximate truth. The right kind is explanatory coherence, where explanation consists in describing mechanisms. We can judge that a scientific theory is progressively approximating the truth if it is increasing its explanatory coherence in two key respects: broadening by explaining more phenomena and deepening by investigating layers of mechanisms. I sketch an explanation of why deepening is a good epistemic strategy and discuss the prospect of deepening knowledge in the social sciences and everyday life.

Representation has been one of the main themes in the recent discussion of models. Several authors have argued for a pragmatic approach to representation that takes users and their interpretations into account. It appears to me, however, that this emphasis on representation places excessive limitations on our view of models and their epistemic value. Models should rather be thought of as epistemic artifacts through which we gain knowledge in diverse ways. Approaching models this way stresses their materiality and media-specificity. Focusing on models as multifunctional artifacts releases them from any preestablished and fixed representational relationships and leads me to argue for a twofold approach to representation.

This paper takes up the cause of species pluralism. An argument for species pluralism is provided and standard monist objections to pluralism are answered. A new form of species pluralism is developed and shown to be an improvement over previous forms. This paper also offers a general foundation on which to base a pluralistic approach to biological classification.

This article identifies conditions under which robust predictive modeling results have special epistemic significance—related to truth, confidence, and security—and considers whether those conditions hold in the context of present-day climate modeling. The findings are disappointing. When today’s climate models agree that an interesting hypothesis about future climate change is true, it cannot be inferred—via the arguments considered here anyway—that the hypothesis is likely to be true or that scientists’ confidence in the hypothesis should be significantly increased or that a claim to have evidence for the hypothesis is now more secure.

The dominant neuroscientific theory of spatial memory is, like many theories in neuroscience, a multilevel description of a mechanism. The theory links the activities of molecules, cells, brain regions, and whole organisms into an integrated sketch of an explanation for the ability of organisms to navigate novel environments. Here I develop a taxonomy of interlevel experimental strategies for integrating the levels in such multilevel mechanisms. These experimental strategies include activation strategies, interference strategies, and additive strategies. These strategies are mutually reinforcing, providing a kind of interlevel and intratheoretic robustness that has not previously been recognized.

This paper discusses several distinct process theories of causality offered in recent years by Phil Dowe and me. It addresses problems concerning the explication of causal process, causal interaction, and causal transmission, whether given in terms of transmission of marks, transmission of invariant or conserved quantities, or mere possession of conserved quantities. Renouncing the mark-transmission and invariant quantity criteria, I accept a conserved quantity theory similar to Dowe's—differing basically with respect to causal transmission. This paper also responds to several fundamental constructive criticisms contained in Christopher Hitchcock's discussion of both the mark-transmission and the conserved quantity theories.

It is shown how a causal ordering can be defined in a complete structure, and how it is equivalent to identifying the mechanisms of a system. Several techniques are shown that may be useful in actually accomplishing such identification. Finally, it is shown how this explication of causal ordering can be used to analyse causal counterfactual conditionals. First the counterfactual proposition at issue is articulated through the device of a belief-contravening supposition. Then the causal ordering is used to provide modal categories for the factual propositions, and the logical contradiction in the system is resolved by ordering the factual propositions according to these causal categories.

It is proposed that we use the term “approximation” for inexact description of a target system and “idealization” for another system whose properties also provide an inexact description of the target system. Since systems generated by a limiting process can often have quite unexpected—even inconsistent—properties, familiar limit processes used in statistical physics can fail to provide idealizations but merely provide approximations.

The concept of levels of organization is prominent in science and central to a variety of debates in philosophy of science. Yet many difficulties plague the concept of universal and discrete hierarchical levels, and these undermine implications commonly ascribed to hierarchical organization. We suggest the concept of scale as a promising alternative. Investigating causal processes at different scales allows for a notion of quasi levels that avoids the difficulties inherent in the classic concept of levels. Our primary focus is ecology, but we suggest how the results generalize to other invocations of hierarchy in science and philosophy of science.

David Malament (1996) has recently argued that there can be no relativistic quantum theory of (localizable) particles. We consider and rebut several objections that have been made against the soundness of Malament's argument. We then consider some further objections that might be made against the generality of Malament's conclusion, and we supply three no-go theorems to counter these objections. Finally, we dispel potential worries about the counterintuitive nature of these results by showing that relativistic quantum field theory itself explains the appearance of “particle detections.”

The purpose of this paper is to set forth a sense in which programs can and do explain behavior, and to distinguish from this a number of senses in which they do not. Once we are tolerably clear concerning the sort of explanatory strategy being employed, two rather interesting facts emerge; (1) though it is true that programs are “internally represented,” this fact has no explanatory interest beyond the mere fact that the program is executed; (2) programs which are couched in information processing terms may have an explanatory interest for a given range of behavior which is independent of physiological explanations of the same range of behavior.

Accounts of the concepts of function and dysfunction have not adequately explained what factors determine the line between low-normal function and dysfunction. I call the challenge of doing so the line-drawing problem. Previous approaches emphasize facts involving the action of natural selection (Wakefield 1992a, 1999a, 1999b) or the statistical distribution of levels of functioning in the current population (Boorse 1977, 1997). I point out limitations of these two approaches and present a solution to the line-drawing problem that builds on the second one.

According to the semantic view of scientific theories, theories are classes of models. I show that this view—if taken literally—leads to absurdities. In particular, this view equates theories that are distinct, and it distinguishes theories that are equivalent. Furthermore, the semantic view lacks the resources to explicate interesting theoretical relations, such as embeddability of one theory into another. The untenability of the semantic view—as currently formulated—threatens to undermine scientific structuralism.

A remarkable hypothesis has recently been advanced by Libet and promoted by Eccles which claims that there is standardly a backwards referral of conscious experiences in time, and that this constitutes empirical evidence for the failure of identity of brain states and mental states. Libet's neurophysiological data are critically examined and are found insufficient to support the hypothesis. Additionally, it is argued that even if there is a temporal displacement phenomenon to be explained, a neurophysiological explanation is most likely.

Functionalism faces a problem in accounting for the semantic powers of beliefs and other mental states. Simple causal considerations will not solve this problem, nor will any appeal to the social utility of semantic interpretations. The correct analysis of semantic representation is a teleological one, in terms of the biological purposes of mental states: whereas functionalism focuses, so to speak, only on the structure of the cognitive mechanism, the semantic perspective requires in addition that we consider the purposes of the cognitive mechanism's parts.

Traditionally, cognitive values have been thought of as a collective pool of considerations in science that frequently trade against each other. I argue here that a finer-grained account of the value of cognitive values can help reduce such tensions. I separate the values into groups, minimal epistemic criteria, pragmatic considerations, and genuine epistemic assurance, based in part on the distinction between values that describe theories per se and values that describe theory-evidence relationships. This allows us to clarify why these values are central to science and what role they should play, while reducing the tensions among them.

It has been repeatedly argued, most recently by Nicholas Maxwell, that the special theory of relativity is incompatible with the view that the future is in some degree undetermined; and Maxwell contends that this is a reason to reject that theory. In the present paper, an analysis is offered of the notion of indeterminateness (or “becoming”) that is uniquely appropriate to the special theory of relativity, in the light of a set of natural conditions upon such a notion; and reasons are given for regarding this conception as (not just formally consistent with relativity theory, but also) philosophically reasonable. The bearings upon Maxwell's program for quantum theory are briefly considered.

Among the liveliest disputes in evolutionary biology today are disputes concerning the role of chance in evolution—more specifically, disputes concerning the relative evolutionary importance of natural selection vs. so-called “random drift”. The following discussion is an attempt to sort out some of the broad issues involved in those disputes. In the first half of this paper, I try to explain the differences between evolution by natural selection and evolution by random drift. On some common construals of “natural selection”, those two modes of evolution are completely indistinguishable. Even on a proper construal of “natural selection”, it is difficult to distinguish between the “improbable results of natural selection” and evolution by random drift.

In the second half of this paper, I discuss the variety of positions taken by evolutionists with respect to the evolutionary importance of random drift vs. natural selection. I will then consider the variety of issues in question in terms of a conceptual distinction often used to describe the rise of probabilistic thinking in the sciences. I will argue, in particular, that what is going on here is not, as might appear at first sight, just another dispute about the desirability of “stochastic” vs. “deterministic” theories. Modern evolutionists do not argue so much about whether evolution is stochastic, but about how stochastic it is.