This article contributes to the underdeveloped field of experimental philosophy of science. We examine variability in the philosophical views of scientists. Using data from Toolbox Dialogue Initiative, we analyze scientists’ responses to prompts on philosophical issues (methodology, confirmation, values, reality, reductionism, and motivation for scientific research) to assess variance in the philosophical views of physical scientists, life scientists, and social and behavioral scientists. We find six prompts about which differences arose, with several more that look promising for future research. We then evaluate the difference between the natural and social sciences and the challenge of interdisciplinary integration across scientific branches.

Thought experiments are ubiquitous in science and especially prominent in domains in which experimental and observational evidence is scarce. One such domain is the causal analysis of singular events in history. A long-standing tradition that goes back to Max Weber addresses the issue by means of ‘what-if’ counterfactuals. In this paper I give a descriptive account of this widely used method and argue that historians following it examine difference makers rather than causes in the philosopher's sense. While difference making is neither necessary nor sufficient for causation, to establish difference makers is more consistent with the historians’ more ultimate purposes.

The works of Paul K. Feyerabend, Norwood Russell Hanson and Thomas S. Kuhn have come to occupy a central place in the annals of contemporary philosophy of science. Some of their contemporaries, ([1], [14], [20]), tend to regard them as the vanguard of a new “revolutionary” intellectual movement. Reacting against the views of their positivist predecessors, they embrace and propagate the idea that “pervasive presuppositions” are fundamental to scientific investigations. Thus, Feyerabend thinks that, “... scientific theories are ways of looking at the world; and their adoption affects our general beliefs and expectations, and thereby also our experiences and our conception of reality” ([5], p. 29). This is in stark contrast to the positivist view that the aim of science is the systematization of experience that exists independently of any scientific theories ([12], p. 178). This new view of scientific theories also involves a “radical” conception of the nature of theoretical change. Rejecting the positivist notion of any constant element (experience, observation language, etc.) through such change, Kuhn regards a basic theoretical change as a conceptual revolution and “wants to say that after a revolution scientists are responding to a different world” ([14], p. 110). Hanson uses the phrase ‘theory-loaded’ to give expression to a view of the semantic content of observation statements that follows from this general position ([11], pp. 19 ff.).

At the center of quantum chaos research is a particular family of models known as quantum maps. These maps illustrate an important “horizontal” dimension to model construction that has been overlooked in the literature on models. Three ways in which quantum maps are being used to clarify the relationship between classical and quantum mechanics are examined. This study suggests that horizontal models may provide a new and fruitful framework for exploring intertheoretic relations.

Although on opposite sides of the logic of discovery debate, Laudan and Simon share a thesis of divorce between discovery (invention) and justification (appraisal); but unlike some other authors, they do not base their respective versions of the divorce-thesis on the empirical/logical distinction. Laudan argues that, in contemporary science, invention is irrelevant to appraisal, and that this irrelevance renders epistemically pointless the inventionist program. Simon uses his divorce-thesis to defend his account of invention, which he claims to be non-inductive—so evading the problem of induction. Underlying both authors' positions are inadequate conceptions of inductive inference. Laudan here ignores the role in contemporary science of plausibility arguments, which provide a crucial link between invention and appraisal, and thence an epistemic rationale for inventionism. Simon's account of invention does covertly call upon inductive principles from the context of appraisal, and this is what gives his program epistemic import; otherwise he would be vulnerable to Laudan's “no rationale” critique. The tensions in both authors reveal the falsity of the divorce-thesis, and the essential function of induction in both appraisal and invention of hypotheses.

A common type of inductive problem is to predict the nature of an unobserved finite sample of a given population on the basis of an observed finite sample of the same population. More precisely, given a class of events A, we examine a sample Sn having n members, of which mi belong to the class Bi. On the basis of our knowledge that mi/n of Sn have been Bi, we attempt to predict the ratio of members of Bi to members of A in a sample Sr containing r unobserved members of A. This type of inference has been called “predictive inference” by Carnap. It is not necessary to argue that all inductive problems reduce to this form; we merely observe that such problems frequently arise, and that they have practical and theoretical importance. In The Short Run I suggested that this kind of problem could be handled by first determining the long run probability P(A, Bi) of Bi, relative to A (presumably on the basis of the relative frequency Fn(A, Bi) of Bi, to A in the observed sample Sn) and then predicting that the relative frequency of Bi within the unobserved sample Sr (the short run) will approximate P(A, Bi) sufficiently for practical purposes. The foregoing procedure requires a rule of each of two types: a rule for the ascertainment of the values of long run probabilities, and a rule for the application of knowledge of long run probabilities to predictions in the short run. The Short Run was not concerned with the nature and justification of rules of the first type, but rather sought to justify a rule of the second type on the assumption that we already possess knowledge of long run probabilities.

Bayesian psychology, in what is perhaps its most familiar version, is incomplete: Jeffrey conditionalization is not a complete account of rational belief change. Jeffrey conditionalization is sensitive to the order in which the evidence arrives. This order effect can be so pronounced as to call for a belief adjustment that cannot be understood as an assimilation of incoming evidence by Jeffrey's rule. Hartry Field's reparameterization of Jeffrey's rule avoids the order effect but fails as an account of how new evidence should be assimilated.

This article argues for a representational semantic conception (RSC) of scientific theories, which respects the bare claim of any semantic view, namely, that theories can be characterized as sets of models. RSC must be sharply distinguished from structural versions that assume a further identity of ‘models’ and ‘structures’, which we reject. The practice turn in the recent philosophical literature suggests instead that modeling must be understood in a deflationary spirit, in terms of the diverse representational practices in the sciences. These insights are applied to some mathematical models, thus showing that the mathematical sciences are not in principle counterexamples to RSC.

This paper distinguishes and critiques several forms of pluralism about the levels of selection, and introduces a novel way of thinking about the biological properties and processes typically conceptualized in terms of distinct levels. In particular, “levels” should be thought of as being entwined or fused. Since the pluralism discussed is held by divergent theorists, the argument has implications for many positions in the debate over the units of selection. And since the key points on which the paper turns apply beyond this specific issue, the paper may prove of general interest in thinking about the metaphysics of science

Recent discussion of the statistical character of evolutionary theory has centered around two positions: (1) Determinism combined with the claim that the statistical character is eliminable, a subjective interpretation of probability, and instrumentalism; (2) Indeterminism combined with the claim that the statistical character is ineliminable, a propensity interpretation of probability, and realism. I point out some internal problems in these positions and show that the relationship between determinism, eliminability, realism, and the interpretation of probability is more complex than previously assumed in this debate. Furthermore, I take some initial steps towards a more adequate account of the statistical character of evolutionary theory.

Cooperation and the allocation of common resources are core features of social behavior. Games idealizing both interactions have been studied separately. But here, rather than examining the dynamics of the individual games, the interactions are combined so that players first choose whether to cooperate, and then, if they jointly cooperate, they bargain over the fruits of their cooperation. It is shown that the dynamics of the combined game cannot simply be reduced to the dynamics of the individual games and that both cooperation and fair division are more likely in the combined game than in the constituent games taken separately.

When in the course of our work we are uncertain, we sometimes become more concerned with our methods than with the content of our problems. We then try to clarify our conceptions and tighten our procedures. And as we re-examine studies that we feel have turned out well, we create conscious models of inquiry with which we try to guide our own work-in-progress.

In attempting to assess the legacy of Paul Feyerabend's philosophical work, matters are complicated by the fact that there was a change in his basic orientation towards the philosophy of science around the end of the 1960s. Here I shall indicate one aspect of Feyerabend's divided legacy. My main aims are to sketch the principal themes in his (fairly extensive but little-known) 1990s output, to situate that later output insofar as it bears on the realism/antirealism debate, and (rather precipitously, perhaps) to identify what I take to be the single common premise of his entire philosophical work.

This essay considers the nature of conceptual frameworks in science, and suggests a reconsideration of the role played by philosophy in radical conceptual change. On Kuhn's view of conceptual conflict, the scientist's appeal to philosophical principles is an obvious symptom of incommensurability; philosophical preferences are merely “subjective factors” that play a part in the “necessarily circular” arguments that scientists offer for their own conceptual commitments. Recent work by Friedman has persuasively challenged this view, revealing the roles that philosophical concerns have played in preparing the way for conceptual change, creating an enlarged conceptual space in which alternatives to the prevailing framework become intelligible and can be rationally discussed. If we shift our focus from philosophical themes or preferences to the process of philosophical analysis, however, we can see philosophy in a different and much more significant historic role: not merely as an external source of general heuristic principles and new conceptual possibilities, but, at least in the most important revolutionary developments, as an objective tool of scientific inquiry. I suggest that this approach offers some insight into the philosophical significance of Newton's and Einstein's revolutionary work in physics, and of the interpretation of their work by (respectively) Kant and the logical positivists. It also offers insight into the connections between modern philosophy of science and some traditional philosophical concerns about the nature of a priori knowledge.

Game theory has played a critical role in elucidating the evolutionary origins of social behavior. Sober and Wilson (1999) model altruism as a prisoner's dilemma and claim that this model indicates that altruism arose from group selection pressures. Sober and Wilson also suggest that the prisoner's dilemma model can be used to characterize punishment; hence, punishment too originated from group selection pressures. However, empirical evidence suggests that a group selection model of the origins of altruistic punishment may be insufficient. I argue that examining dominance hierarchies and coalition formation in chimpanzee societies suggests that the origins of altruistic punishment may be best captured by individual selection models. I suggest that this shows the necessity of coupling of game-theoretic models with a conception of what our actual social structure may have been like to best model the origins of our own behavior.

1. Terminological Considerations. Since Russell enunciated the principle, “Wherever possible logical constructions are to be substituted for inferred entities,” or “Wherever possible, substitute constructions out of known entities for inferences to unknown entities,” the terminological situation has become confused. Russell defined neither “construction” nor “inferred entity.” “Construct” soon came to be used for “construction,” perhaps to avoid the ambiguity whereby the latter term was used to refer to both a process and a result. But many writers now use “construction” or “construct” to refer to what Russell called the “inferred entity.” This seems to be the usage of Margenau, Ramsperger, Benjamin, Bures, and many others. Again, some of the same writers in other places (e.g., Benjamin) remain closer to Russell's usage. And I find it difficult to determine exactly the relation of the usage of some writers to that of Russell because of the differences between their contexts and Russell's. I experience this difficulty in reading, for instance, both Miss Stebbing and Werkmeister. The terminological difficulties have been evaded by some other writers who have formulated new terms to refer to Russell's inferred entities. Thus Northrop speaks of the “theoretic component” and Miller has coined the word, “interphenomena.” The terms reflecting Russell's rule in psychology have become so confused that a set of explicit definitions has recently been proposed.

After precisely specifying the thesis of the causal theory of time, Grünbaum's program developed to support this thesis is examined. Four objections to his definition of temporal order in terms of a more primitive causal relation are put and held to be conclusive. Finally, the philosophical arguments that Grünbaum has proposed supporting the desirability of establishing a causal theory of time are shown to be either invalid or inconclusive.

This paper is an attempt to spell out what makes the scientific study of pain so distinctive from a philosophical perspective. Using the IASP definition of ‘pain’ (1986) as our guide, we raise a number of questions about the philosophical assumptions underlying the scientific study of pain. We argue that unlike the study of ordinary perception, the study of pain focuses from the very start on the experience itself and its qualities, without making deep assumptions about whether pain experiences are perceptual. This in turn puts scientific explanation in a curious position due to pain's inherently subjective epistemic nature. The reason for this focus on the experience itself and its qualities, we argue, has to do with pain's complex phenomenology involving an affective/motivational dimension. We argue for the scientific legitimacy of first-person phenomenological studies and attempts to correlate phenomenology with neural events. We argue that this methodological procedure is inevitable and has no anti-physicalist ontological implications when properly understood. We end the paper by commenting on a discussion between two prominent pain scientists in the field, Don Price and Howard Fields, about the need to distinguish more dimensions in the phenomenology of pain and how to classify them vis-à-vis the recent scientific findings. Our interest in this discussion is not only to introduce some clarifications but also to show how “neurophenomenology” has already been shaping the scientific research and to back our claim about why this methodology is inevitable with an example.

This paper attacks the perennial philosophical and scientific quest for a simple and unified vision of the world. Without denying the attraction of this vision, I argue that such a goal often seriously distorts our understanding of complex phenomena. The argument is illustrated with reference to simplistic attempts to provide extremely general views of biology, and especially of human nature, through the theory of evolution. Although that theory is a fundamental ingredient of our scientific world view, it provides only one of a number of perspectives that are required for an understanding of biology in general, and human behaviour in paticular. The argument is connected to the replacement of views of science in terms of universal laws with views that emphasise ranges of models more locally suited to specific phenomena.

What sort of subject is the philosophy of science? It would be difficult to find any sort of agreement on the answer to this question. There are a large number of physicists who have promoted the idea that the subject is a kind of cosmic journalism: any new major discoveries in physics warrant an up-to-the-minute, catch-as-catch-can analysis of the boundaries of scientific knowledge. On the other hand, the Oxonian sirens of ordinary language tell us that any careful scrutiny of technical scientific matters is not proper philosophical activity. I want to argue that the philosopher of science need be neither a journalist of science nor merely an acute man of common sense eternally restricted to contemplating the general meaning of such notions as those of mind, free will, cause and determinism.