An invisible hand seems to play an important role in science. In this paper I set out the general structure of invisible-hand explanations, counter some objections that have been raised to them, and detail the role that they play in science. The most important issue is the character of the mechanisms that are supposed to bring about invisible-hand effects.

The failure of the attempt by Michael Polanyi to capture the social organization of science by comparing it to the operation of a market bears salutary lessons for modern philosophers of science in their rush to appropriate market models and metaphors. In this case, an initially plausible invisible hand argument ended up as crude propaganda for the uniquely privileged social support of science.

Goldman joins the ranks of epistemologists, philosophers, and science studies scholars trying to use economic models of science. For Goldman, these models are part of social rather than individual epistemics. His hope is that these models will illustrate that non-epistemic goals of individual scientists such as professional success do not necessarily undermine epistemic aims of science such as the acquisition of truth. This paper shows that there are inconsistencies between Goldman's individual and social epistemics, that these models do not live up to Goldman's standards of evaluation, and that the economic models that Goldman uses are not social.

Assessing the hydrogeological modeling at the Yucca Mountain and Maxey Flats nuclear repositories reveals a number of important ways in which theory choice can go wrong. The two cases suggest that there are at least six important criteria for evaluating the suitability of scientific models to be used for predictions intended to serve public policy. More generally, the paper argues that applied philosophy of science, as practiced in environmental policymaking, requires one to employ ethical rationality as well as scientific rationality, to heed the advice of the moral philosopher, not merely that of the epistemologist or philosopher of science.

The problem of hunger is a problem of the inequitable distribution of food entitlements. I argue that ‘modern’ science is implicated in the current form of this problem and that it can only contribute to its resolution, rather than exacerbation, if the forms of its implication are acknowledged. But this requires acceptance of the claim that science is not value-neutral. In part this paper is also an examination, in a particular problem context, of some dimensions of disputes over the value neutrality of science.

Each of the three papers offers a different model for the role philosophers of science might play in consideration of the relations of science to society. These comments address common themes in the three papers, articulate further questions for each, and suggest some historical shifts that require different forms of philosophical engagement now than in the early part of the century.

This short paper serves as an introduction to a debate between representatives of two fundamentally different points of view regarding the nature of scientific inference. Colin Howson and Peter Urbach represent a Bayesian point of view and Deborah Mayo represents a version of classical statistics called error statistics. The paper begins by reviewing earlier versions of the same two points of view due to Rudolf Carnap and Hans Reichenbach, respectively. After a few remarks about philosophical approaches to understanding scientific reasoning between 1960 and 1980, I turn to substantive differences between the two approaches.

The Bayesian theory is outlined and its status as a logic defended. In this it is contrasted with the development and extension of Neyman-Pearson methodology by Mayo in her recently published book (1996). It is shown by means of a simple counterexample that the rule of inference advocated by Mayo is actually unsound. An explanation of why error-probablities lead us to believe that they supply a sound rule is offered, followed by a discussion of two apparently powerful objections to the Bayesian theory, one concerning old evidence and the other optional stopping.

The error statistical account of testing uses statistical considerations, not to provide a measure of probability of hypotheses, but to model patterns of irregularity that are useful for controlling, distinguishing, and learning from errors. The aim of this paper is (1) to explain the main points of contrast between the error statistical and the subjective Bayesian approach and (2) to elucidate the key errors that underlie the central objection raised by Colin Howson at our PSA 96 Symposium.

The frequencies with which photons pass through half-silvered mirrors in the forward direction of time is always approximately 1/2, whereas the frequencies with which photons pass through mirrors in the backward direction in time can be highly time-dependent. I argue that whether one should infer from this time-asymmetric phenomenon that time has an objective direction will depend on one's interpretation of quantum mechanics.

This paper searches for an explicit expression of the so-called problem of the direction of time. I argue that the traditional version of the problem is an artifact of a mistaken view in the foundations of statistical mechanics, and that to the degree it is a problem, it is really one general to all the special sciences. I then search the residue of the traditional problem for any remaining difficulty particular to time's arrow and find that there is a special puzzle for some types of scientific realist.

Physics takes for granted that interacting systems without common history are independent, before interaction. This principle is time asymmetric, for no such restriction applies to systems without common future, after interaction. The time asymmetry is normally attributed to boundary conditions. I argue that there are two such independence principles at work in contemporary physics, one of which cannot be attributed to boundary conditions, and therefore conflicts with the assumed T-symmetry of microphysics. I note that this may have interesting ramifications in quantum mechanics.

My paper draws on examples from molecular biology, the details of which I have developed elsewhere (Rheinberger 1992, 1993, 1995, 1997). Here, I can give only a brief outline of my argument. Reduction of complexity is a prerequisite for experimental research. To make sense of the universe of living beings, the modern biologist is bound to divide his world into fragments in which parameters can be defined, quantities measured, qualities identified. Such is the nature of any “experimental system.” Ontic complexity has to be reduced in order to make experimental research possible. The complexity of the research object, however, is epistemically retained in the rich context of an experimental landscape, where the eruption of “volcanic systems” can change the scenery dramatically as the result of particular, unprecedented findings.