A twofold taxonomy for emergence is presented into which a variety of contemporary accounts of emergence fit. The first taxonomy consists of inferential, conceptual, and ontological emergence; the second of diachronic and synchronic emergence. The adequacy of weak emergence, a computational form of inferential emergence, is then examined and its relationship to conceptual emergence and ontological emergence is detailed.

I challenge the usual approach of defining emergence in terms of properties of wholes “emerging” upon properties of parts. This approach indeed fails to meet the requirement of nontriviality, since it renders a bunch of ordinary properties emergent; however, by defining emergence as the incompressibility of a simulation process, we have an objective meaning of emergence because the difference between the processes satisfying the incompressibility criterion and the other processes does not depend on our cognitive abilities. Finally, this definition fulfills the nontriviality and the scientific-adequacy requirements better than the combinatorial approach, emergence here being a predicate of processes rather than of properties.

Rather than taking the ontological fundamentality of an ideal microphysics as a starting point, this article sketches an approach to the problem of levels that swaps assumptions about ontology for assumptions about inquiry. These assumptions can be implemented formally via computational modeling techniques that will be described below. It is argued that these models offer a way to save some of our prominent commonsense intuitions concerning levels. This strategy offers a way of exploring the individuation of higher level properties in a systematic and formally constrained manner.

Until recently, economics was generally understood to be a nonexperimental science with a hypothetico-deductive methodology. This article considers how the methodology of economics has changed with the spread of experimental methods. Initially, most experimental economists saw their work as testing pre-existing theories. However, a method of systematic inductive enquiry in which theory plays a less central role is now evolving. This method is structured around the discovery and progressive refinement of regularities. “Exhibits”—experimental designs that generate significant regularities—are taking over some of the functions formerly performed by theoretical models.

The growing acceptance and success of experimental economics has increased the interest of researchers in tackling philosophical and methodological challenges to which their work increasingly gives rise. I sketch some general issues that call for the combined expertise of experimental economists and philosophers of science, of experiment, and of inductive-statistical inference and modeling.

This article explores some issues having to do with the use of experimental results from one-shot games to reach conclusions about the existence of social preferences that are taken to figure in the explanation of cooperation in repeated interactions in real life.

The Ultimatum Game is one of the most successful experimental designs in the history of the social sciences. In this article I try to explain this success—what makes it a “paradigmatic experiment”—stressing in particular its versatility. Despite the intentions of its inventors, the Ultimatum Game was never a good design to test economic theory, and it is now mostly used as a heuristic tool for the observation of nonstandard preferences or as a “social thermometer” for the observation of culture-specific norms.

In two recent papers Barry Loewer (2001, 2004) has suggested to interpret probabilities in statistical mechanics as chances in David Lewis's (1994) sense. I first give a precise formulation of this proposal, then raise two fundamental objections, and finally conclude that these can be overcome only at the price of interpreting these probabilities epistemically.

The Boltzmann and Gibbs approaches to statistical mechanics have very different definitions of equilibrium and entropy. The problems associated with this are discussed, and it is suggested that they can be resolved, to produce a version of statistical mechanics incorporating both approaches, by redefining equilibrium not as a binary property (being/not being in equilibrium) but as a continuous property (degrees of equilibrium) measured by the Boltzmann entropy and by introducing the idea of thermodynamic-like behavior for the Boltzmann entropy. The Kac ring model is used as an example to test the proposals.

In this article I consider the challenges for exporting causal knowledge raised by complex biological systems. In particular, James Woodward's interventionist approach to causality identified three types of stability in causal explanation: invariance, modularity, and insensitivity. I consider an example of robust degeneracy in genetic regulatory networks and knockout experimental practice to pose methodological and conceptual questions for our understanding of causal explanation in biology.

Leading philosophical accounts presume that Thomas H. Morgan's transmission theory can be understood independently of experimental practices. Experimentation is taken to be relevant to confirming, rather than interpreting, the transmission theory. But the construction of Morgan's theory went hand in hand with the reconstruction of the chief experimental object, the model organism Drosophila melanogaster. This raises an important question: when a theory is constructed to account for phenomena in carefully controlled laboratory settings, what knowledge, if any, indicates the theory's relevance to phenomena outside highly controlled settings? The answer, I argue, is found within the procedural knowledge embedded within laboratory practice.

After sorting different structuralist claims, I argue that structural realist ideas are instantiated in the social sciences, providing both clarification of social science research and support for some components of structural realism. My main focus is on three distinct ways that the social sciences can be about structural relations—exemplified by claims about social structure, reduced form structures in causal modeling, and equilibrium explanations—and on the implication of structuralist ideas for thinking about issues concerning causal explanation and nonreductive pictures of the unity of the science.

Ontic structural realism (OSR) is crucially motivated by empirical discoveries of fundamental physics. To this extent its potential to furnish a general metaphysics for science may appear limited. However, OSR also provides a good account of the progress that has been achieved over the decades in a formalized special science, economics. Furthermore, this has a basis in the ontology presupposed by economic theory, and is not just an artifact of formalization.

The primacy of physics generates a philosophical problem that the naturalist must solve in order to be entitled to an egalitarian acceptance of the ontological commitments he or she inherits from the special sciences and fundamental physics. The problem is the generalized causal exclusion argument. If there is no genuine causation in the domains of the special sciences but only in fundamental physics then there are grounds for doubting the existence of macroscopic objects and properties, or at least the concreteness of them. The aim of this paper is to show that the causal exclusion problem derives its force from a false dichotomy between Humeanism about causation and a notion of productive or generative causation based on a defunct model of the physical world.

There is sufficient evidence that intellectual property rights are corrupting medical research. One could respond to this from a moral or from an epistemic point of view. I take the latter route. Often in the sciences factual discoveries lead to new methodological norms. Medical research is an example. Surprisingly, the methodological change required will involve political change. Instead of new regulations aimed at controlling the problem, the outright socialization of research seems called for, for the sake of better science. I appeal to an analogy between socialized medicine and socialized research.

Among philosophers of science nearly a century ago the dominant attitude was that (in Rudolph Carnap's words) philosophy of science was “like science itself, neutral with respect to practical aims, whether they are moral aims for the individual, or political aims for a society.” The dominant attitude today is not much different: our aim is still to articulate scientific rationality, and our understanding of that rationality still excludes the moral and political. I contrast this with the growing entanglements within the sciences of the ethical and the epistemic, and I suggest ways in which philosophers of science can usefully respond.

Janet Kourany argues that philosophers of science should place more emphasis on the moral and political aspects of scientific research. As a possible site for philosophical intervention she discusses professional codes of ethics. James Brown describes various systemic problems in pharmaceutical research and proposes that socializing medical research is the best way to remedy the situation. I criticize each of their examples, but concur with many overall aspects of their expanded agenda for philosophy of science.

Newton's equations of motion tell us that a mass at rest at the apex of a dome with the shape specified here can spontaneously move. It has been suggested that this indeterminism should be discounted since it draws on an incomplete rendering of Newtonian physics, or it is “unphysical,” or it employs illicit idealizations. I analyze and reject each of these reasons.