In this paper I am going to try to indicate my notion concerning the nature and subject-matter of psychology. I am a behaviorist. I hold that psychology does not seek descriptions and intercommunications concerning immediate experience per se. Such descriptions and attempts at direct intercommunications may be left to the arts and to metaphysics. Psychology seeks, rather, the objectively stateable laws and processes governing behavior. Organisms, human and sub-human, come up against environmental stimulus situations and to these stimulus situations they, after longer or shorter intervals of time, behave. The laws and processes determining this their behavior are stateable in objective terms. Even in the cases where the organism is oneself, these determining causal factors can and must—for the purposes of psychology—be stated objectively. It is true that in these latter instances, in which the animal in question is oneself, one may in one's rôle, not of a psychologist, but of an artist or a metaphysician, attempt to describe and convey to another man one's own facts of immediate experience. But such a description and report of immediate experiences, except in so far as this report is itself a form of behavior and therefore like all other behaviors the basis for an investigation of the objective laws and processes underlying it, essentially new to the picture. Experience qua experience, while of concern and interest to the man in the street, the philosopher and the poet, does not enter as such into the laws and equations of psychology,—in so far, at any rate, as psychology is to be considered as a science.

Many realists have maintained that the success of scientific theories can be explained only if they may be regarded as approximately true. Laurens Laudan has in turn contended that a necessary condition for a theory's being approximately true is that its central terms refer, and since many successful theories of the past have employed central terms which we now understand to be non-referential, realism cannot explain their success. The present paper argues that a realist can adopt a view of reference according to which a theory might plausibly be said to be approximately true even though its central terms do not refer, or alternatively, he may construe reference in such a way as to assign reference to a range of successful older theories which includes Laudan's purported counterexamples.

Recently, several philosophers have challenged the view that evolutionary theory is usefully understood by way of an analogy with Newtonian mechanics. Instead, they argue that evolutionary theory is merely a statistical theory. According to this alternate approach, natural selection and random genetic drift are not even causes, much less forces. I argue that, properly understood, the Newtonian analogy is unproblematic and illuminating. I defend the view that selection and drift are causes in part by attending to a pair of important distinctions—that between process and product and that between natural selection and fitness.

A belief common among philosophers and biologists alike is that Mendelian genetics has been or is in the process of being reduced to molecular genetics, in the sense of formal theory reduction current in the literature. The purpose of this paper is to show that there are numerous empirical and conceptual difficulties which stand in the way of establishing a systematic inferential relation between Mendelian and molecular genetics. These difficulties, however, have little to do with the traditional objections which have been raised to reduction.

John Beatty (1995) and Alexander Rosenberg (1994) have argued against the claim that there are laws in biology. Beatty's main reason is that evolution is a process full of contingency, but he also takes the existence of relative significance controversies in biology and the popularity of pluralistic approaches to a variety of evolutionary questions to be evidence for biology's lawlessness. Rosenberg's main argument appeals to the idea that biological properties supervene on large numbers of physical properties, but he also develops case studies of biological controversies to defend his thesis that biology is best understood as an instrumental discipline. The present paper assesses their arguments.

The work of Tversky, Kahneman and others suggests that people often make use of cognitive heuristics such as availability, salience and representativeness in their reasoning and decision making. Through use of a historical example—the recent plate tectonics revolution in geology—I argue that such heuristics play a crucial role in scientific decision making also. I suggest how these heuristics are to be considered, along with noncognitive factors (such as motivation and social structures) when drawing historical and epistemological conclusions. The normative perspective is community-wide, contextual, and instrumental.

The goal of this paper is to develop a counterfactual theory of explanation (CTE). The CTE provides a monist framework for causal and noncausal explanations, according to which both causal and noncausal explanations are explanatory by virtue of revealing counterfactual dependencies between the explanandum and the explanans. I argue that the CTE is applicable to two paradigmatic examples of noncausal explanations: Euler’s explanation and renormalization group explanations of universality.

Social scientists report difficulties in drawing out testable predictions from the literature on intersectionality theory. We alleviate that difficulty by showing that some characteristic claims of the intersectionality literature can be interpreted causally. The formalism of graphical causal modeling allows claims about the causal effects of occupying intersecting identity categories to be clearly represented and submitted to empirical testing. After outlining this causal interpretation of intersectional theory, we address some concerns that have been expressed in the literature claiming that membership in demographic categories can have causal effects.

Darwinians are realists about the force of selection, but there has been surprisingly little discussion about what form this realism should take. Arguments about the units of selection in general and genic selectionism in particular reveal two realist assumptions: (1) for any selection process, there is a uniquely correct identification of the operative selective forces and the level at which each impinges; and (2) selective forces must satisfy the Pareto-style requirement of probabilistic causation. I argue that both assumptions are false; we must temper realism about the force of selection and revise the way we think about probabilistic causation.

There is a takeover movement fast gaining influence in development economics, a movement that demands that predictions about development outcomes be based on randomized controlled trials. The problem it takes up—of using evidence of efficacy from good studies to predict whether a policy will be effective if we implement it—is a general one, and affects us all. My discussion is the result of a long struggle to develop the right concepts to deal with the problem of warranting effectiveness predictions. Whether I have it right or not, these are questions of vast social importance that philosophers of science can, and should, help answer.

The question of coherence of rules for changing degrees of belief in the light of new evidence is studied, with special attention being given to cases in which evidence is uncertain. Belief change by the rule of conditionalization on an appropriate proposition and belief change by “probability kinematics“ on an appropriate partition are shown to have like status.

Ecological fitness has been suggested to provide a unifying definition of fitness. However, a metric for this notion of fitness was in most cases unavailable except by proxy with differential reproductive success. In this article, I show how differential persistence of lineages can be used as a way to assess ecological fitness. This view is inspired by a better understanding of the evolution of some clonal plants, colonial organisms, and ecosystems. Differential persistence shows the limitation of an ensemblist noncausal understanding of evolution. Causal explanations are necessary to understand the evolution by natural selection of these biological systems.

We show that previous results from epistemic network models by Kevin J. S. Zollman and Erich Kummerfeld showing the benefits of decreased connectivity in epistemic networks are not robust across changes in parameter values. Our findings motivate discussion about whether and how such models can inform real world epistemic communities.

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.

David Marr's theory of vision has been widely cited by philosophers and psychologists. I have three projects in this paper. First, I try to offer a perspicuous characterization of Marr's theory. Next, I consider the implications of Marr's work for some currently popular philosophies of psychology, specifically, the “hegemony of neurophysiology view”, the theories of Jerry Fodor, Daniel Dennett, and Stephen Stich, and the view that perception is permeated by belief. In the last section, I consider what the phenomenon of vision must be like for Marr's project to succeed.

Quine and others have recommended principles of charity which discourage judgments of irrationality. Such principles have been proposed to govern translation, psychology, and economics. After comparing principles of charity of different degrees of severity, we argue that the stronger principles are likely to block understanding of human behavior and impede progress toward improving it. We support a moderate principle of charity which leaves room for empirically justified judgments of irrationality.

Recently, several authors have argued that scientific understanding should be a new topic of philosophical research. In this article, I argue that the three most developed accounts of understanding—Grimm's, de Regt's, and de Regt and Dieks's—can be replaced by earlier ideas about scientific explanation without loss. Indeed, in some cases, such replacements have clear benefits.

The growing availability of computer power and statistical software has greatly increased the ease with which practitioners apply statistical methods, but this has not been accompanied by attention to checking the assumptions on which these methods are based. At the same time, disagreements about inferences based on statistical research frequently revolve around whether the assumptions are actually met in the studies available, e.g., in psychology, ecology, biology, risk assessment. Philosophical scrutiny can help disentangle ‘practical’ problems of model validation, and conversely, a methodology of statistical model validation can shed light on a number of issues of interest to philosophers of science.

The question of the influence of genes on behavior raises difficult philosophical and social issues. In this paper I delineate what I call the Developmentalist Challenge (DC) to assertions of genetic influence on behavior, and then examine the DC through an indepth analysis of the behavioral genetics of the nematode, C. elegans, with some briefer references to work on Drosophila. I argue that eight “rules” relating genes and behavior through environmentally-influenced and tangled neural nets capture the results of developmental and behavioral studies on the nematode. Some elements of the DC are found to be sound and others are criticized. The essay concludes by examining the relations of this study to Kitcher's antireductionist arguments and Bechtel and Richardson's decomposition and localization heuristics. Some implications for human behavioral genetics are also briefly considered.

Several authors have argued that causes differ in the degree to which they are ‘specific’ to their effects. Woodward has used this idea to enrich his influential interventionist theory of causal explanation. Here we propose a way to measure causal specificity using tools from information theory. We show that the specificity of a causal variable is not well defined without a probability distribution over the states of that variable. We demonstrate the tractability and interest of our proposed measure by measuring the specificity of coding DNA and other factors in a simple model of the production of mRNA.