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.

There are two competing interpretations of the modern synthesis theory of evolution: the dynamical (also know as ‘traditional’) and the statistical. The dynamical interpretation maintains that explanations offered under the auspices of the modern synthesis theory articulate the causes of evolution. It interprets selection and drift as causes of population change. The statistical interpretation holds that modern synthesis explanations merely cite the statistical structure of populations. This paper offers a defense of statisticalism. It argues that a change in trait frequencies in a population can be attributed only to selection or drift against the background of a particular statistical description of the population. The traditionalist supposition that selection and drift are description-independent causes of population change leads the dynamical interpretation into a dilemma: it must face a contradiction or accept the loss of explanatory power.

Theorizing in ecology and evolution often proceeds via the construction of multiple idealized models. To determine whether a theoretical result actually depends on core features of the models and is not an artifact of simplifying assumptions, theorists have developed the technique of robustness analysis, the examination of multiple models looking for common predictions. A striking example of robustness analysis in ecology is the discovery of the Volterra Principle, which describes the effect of general biocides in predator-prey systems. This paper details the discovery of the Volterra Principle and the demonstration of its robustness. It considers the classical ecology literature on robustness and introduces two individual-based models of predation, which are used to further analyze the Volterra Principle. The paper also introduces a distinction between parameter robustness, structural robustness, and representational robustness, and demonstrates that the Volterra Principle exhibits all three kinds of robustness.

We maximally extend the quantum-mechanical results of Muller and Saunders (2008) establishing the ‘weak discernibility’ of an arbitrary number of similar fermions in finite-dimensional Hilbert spaces. This confutes the currently dominant view that (A) the quantum-mechanical description of similar particles conflicts with Leibniz's Principle of the Identity of Indiscernibles (PII); and that (B) the only way to save PII is by adopting some heavy metaphysical notion such as Scotusian haecceitas or Adamsian primitive thisness. We take sides with Muller and Saunders (2008) against this currently dominant view, which has been expounded and defended by many.

The controversy regarding the unit of selection is fundamentally a dispute about what is the correct causal structure of the process of evolution by natural selection and its ontological commitments. By characterizing the process as consisting of two essential steps—interaction and transmission—a singular answer to the unit question becomes ambiguous. With such an account on hand, two recent defenses of competing units of selection are considered. Richard Dawkins maintains that the gene is the appropriate unit of selection and Robert Brandon, in response, argues that the individual organism is better suited to the role. This paper argues that by making explicit the underlying questions that each of these views addresses, the apparent conflict can be resolved. Furthermore, such a resolution allows for a more complete and realistic understanding of the process of evolution by natural selection.

Given its importance in modern physics, philosophers of science have paid surprisingly little attention to the subject of symmetries and invariances, and they have largely neglected the subtopic of symmetry breaking. I illustrate how the topic of laws and symmetries brings into fruitful interaction technical issues in physics and mathematics with both methodological issues in philosophy of science, such as the status of laws of physics, and metaphysical issues, such as the nature of objectivity.

The intention of the present essay is to urge a reconsideration of the Realism-Phenomenalism-Issue, mainly and primarily in regard to the interpretation of scientific hypotheses; secondarily also relating to the basic problems of epistemology.

Modifications of current theories of ordinal, interval and extensive measurement are presented, which aim to accomodate the empirical fact that perfectly exact measurement is not possible (which is inconsistent with current theories). The modification consists in dropping the assumption that equality (in measure) is observable, but continuing to assume that inequality (greater or lesser) can be observed. The modifications are formulated mathematically, and the central problems of formal measurement theory—the existence and uniqueness of numerical measures consistent with data—are re-examined. Some results also are given on a problem which does not arise in current theories: namely that of determining limits of accuracy attainable on the basis of observations.

This paper examines in detail two paths that lead to Structural Realism (SR), viz. a substantive philosophical position which asserts that only the structure of the world is knowable. The upward path is any attempt to begin with empiricist premises and reach a sustainable realist position. (It has been advocated by Russell, Weyl, and Maxwell among others.) The downward path is any attempt to start from realist premises and construct a weaker realist position. (It has been recently advocated by Worrall, French, and Ladyman.) This paper unravels and criticizes the metaphysical presuppositions of both paths to SR. It questions its very possibility as a substantive—and viable—realist thesis.

This article analyzes the epistemic value of understanding and offers an account of the role of understanding in science. First, I discuss the objectivist view of the relation between explanation and understanding, defended by Carl Hempel and J. D. Trout. I challenge this view by arguing that pragmatic aspects of explanation are crucial for achieving the epistemic aims of science. Subsequently, I present an analysis of these pragmatic aspects in terms of ‘intelligibility’ and a contextual account of scientific understanding based on this notion.

In cognitive psychology, concepts are those bodies of knowledge that are stored in long-term memory and are used by default in human beings’ higher cognitive processes (categorization, inductive and deductive reasoning, etc.). Most psychologists of concepts assume that these mental representations share many scientifically important properties, and the psychology of concepts is expected to describe those properties. Psychologists assume thereby that concepts constitute a natural kind. I call this assumption the natural kind assumption. This article challenges the natural kind assumption. It is argued that a growing body of evidence suggests that concepts do not constitute a natural kind. Hence, the notion of concept is inappropriate, if one aims at formulating scientifically relevant inductive generalizations about the human mind.

This paper contributes to the mathematical foundations of the model for utility theory developed by Richard Jeffrey in The Logic of Decision [5]. In it I discuss the relationship of Jeffrey's to classical models, state and interpret an existence theorem for numerical utilities and subjective probabilities and restate a theorem on their uniqueness.

The positivistic Received View construed scientific theories syntactically as axiomatic calculi where theoretical terms were given a partial semantic interpretation via correspondence rules connecting them to observation statements. This paper assesses what, with hindsight, seem the most important defects in the Received View; surveys the main proposed successor analyses to the Received View—various Semantic Conception versions and the Structuralist Analysis; evaluates how well they avoid those defects; examines what new problems they face and where the most promising require further development or leave unanswered questions; explores implications of recent work on models for understanding theories; and rebuts the few criticisms of the Semantic Conception that have surfaced.

Richard Rudner famously argues that the communication of scientific advice to policy makers involves ethical value judgments. His argument has, however, been rightly criticized. This article revives Rudner's conclusion, by strengthening both his lines of argument: we generalize his initial assumption regarding the form in which scientists must communicate their results and complete his ‘backup’ argument by appealing to the difference between private and public decisions. Our conclusion that science advisors must, for deep-seated pragmatic reasons, make value judgments is further bolstered by reflections on how the scientific contribution to policy is far less straightforward than the Rudner-style model suggests.

Discussions of representation in science tend to draw on examples from art. However, such examples need to be handled with care given a) the differences between works of art and scientific theories and b) the accommodation of these examples within certain philosophies of art. I shall examine the claim that isomorphism is neither necessary nor sufficient for representation and I shall argue that there exist accounts of representation in both art and science involving isomorphism which accommodate the apparent counterexamples and, moreover, allow us to understand how “impossible” artistic objects and inconsistent scientific theories can be said to represent.

A mathematical theory is proposed and exemplified, which covers an extended class of black boxes. Every kind of stimulus and response is pictured by a channel connecting the box with its environment. The input-output relation is given by a postulate schema according to which the response is, in general, a nonlinear functional of the input. Several examples are worked out: the perfectly transmitting box, the damping box, and the amplifying box. The theory is shown to be (a) an extension of the S-matrix theory and the accompanying channel picture as developed in microphysics; (b) abstract and applicable to any problem involving the transactions of a system (physical, biological, social, etc.) with its milieu; (c) superficial, because unconcerned with either the structure of the box or the nature of the stimuli and responses. The motive for building the theory was to show the capabilities and limitations of the phenomenological approach.

In clinical and agricultural trials, there is the danger that an experimental outcome appears to arise from the causal process or treatment one is interested in when, in reality, it was produced by some extraneous variation in the experimental conditions. The remedy prescribed by classical statisticians involves the procedure of randomization, whose effectiveness and appropriateness is criticized. An alternative, Bayesian analysis of experimental design, is shown, on the other hand, to provide a coherent and intuitively satisfactory solution to the problem.

Advocates have sought to prove that underdetermination obtains because all theories have empirical equivalents. But algorithms for generating empirical equivalents simply exchange underdetermination for familiar philosophical chestnuts, while the few convincing examples of empirical equivalents will not support the desired sweeping conclusions. Nonetheless, underdetermination does not depend on empirical equivalents: our warrant for current theories is equally undermined by presently unconceived alternatives as well-confirmed merely by the existing evidence, so long as this transient predicament recurs for each theory and body of evidence we consider. The historical record supports the claim that this recurrent, transient underdetermination predicament is our own.

The goal of the present article is to contribute to the epistemology and methodology of computer simulations. The central thesis is that the process of simulation modeling takes the form of an explorative cooperation between experimenting and modeling. This characteristic mode of modeling turns simulations into autonomous mediators in a specific way; namely, it makes it possible for the phenomena and the data to exert a direct influence on the model. The argumentation will be illustrated by a case study of the general circulation models of meteorology, the major simulation models in climate research.