In Constructing Quarks (1984) Andrew Pickering discussed the early experiments on atomic parity violation performed at Oxford University and at the University of Washington and published in 1976 and 1977. The results disagreed with the predictions of the Weinberg-Salam (W-S) theory of unified electroweak interactions. Another experiment, performed at the Stanford Linear Accelerator Center in 1978, on the scattering of polarized electrons from deuterons confirmed the theory. Pickering regards the Oxford and Washington experiments as mutants, slain by the SLAC experiment.

By 1979 the W-S theory was regarded by the high-energy physics community as established, despite the fact that as Pickering recounts, “there had been no intrinsic change [emphasis in original] in the status of the Washington-Oxford experiments.” (Pickering 1984, p. 301).

Scientists typically do something other than accept or reject their theories, they pursue them. Throughout the greater part of the nineteenth century numerous chemists devoted their research energy and resources to the development of Daltonian theory, declaring themselves willing to make use of the atomic theory in their research but reluctant or unwilling to accept it. When Frankland, for example, declared that he did not want to be considered a “blind believer” in the atomic theory and could not “accept it as true”, but that he had been—and planned to continue—using it “as a useful ladder”, he had arrived at a decision shared by many of his colleagues that while the theory was not acceptable, it was promising and worthy of pursuit.1 And when Van’t Hoff measured the kinetic-molecular theory by its fruits in the 1880’s, he judged that it barely gave the then-current 4% interest rate, and so was an unpromising theory, unworthy of pursuit (van Nelsen 1960. p. 151).

A great deal of attention has been paid by philosophers to the use of computers in the modelling of human cognitive capacities and in the construction of intelligent artifacts. This emphasis has tended to obscure the fact that most of the high-level computing power in science is deployed in what appears to be a much less exciting activity: solving equations. This apparently mundane set of applications reflects the historical origins of modem computing, in the sense that most of the early computers in Britain and the U.S. were devices built to numerically attack mathematical problems that were hard, if not impossible, to solve non-numerically, especially in the areas of ballistics and fluid dynamics. The latter area was especially important for the development of atomic weapons at Los Alamos, and it is still true that a large portion of the supercomputing capacity of the United States is concentrated at weapons development laboratories such as Los Alamos and Lawrence Livermore.

Until recently, realists and anti-realists alike have assumed that any approximations which appear in explanations and confirmations in the mathematically oriented physical and biological sciences are “mere distractions” (Laymon 1989, p. 353). When approximation techniques must be used, they are typically justified by appeals to their numerical accuracy. However, recent interest in computational complexity in the sciences has revealed that numerical accuracy is not always the only criterion which should be invoked to justify the use of approximations. Cartwright (1983), Franklin (1988) and others have suggested that causal accuracy should be added as a criterion.

Numerical and causal accuracy are important. However, they form a sufficient set of justificational criteria only when certain—often unstated—conditions obtain. These conditions are actually assumptions which are often not satisfied, especially in the computationally complex situations which characterize discovery and exploratory contexts. In these contexts, we need to concentrate on “delineating a justificatory set which is relevant to [the] given epistemic situation” (Duran 1988, p. 273).

The central claim of this paper is that computer simulation provides (though not exclusively) a qualitatively new and different methodology for the physical sciences, and that this methodology lies somewhere intermediate between traditional theoretical physical science and its empirical methods of experimentation and observation. In many cases it involves a new syntax which gradually replaces the old, and it involves theoretical model experimentation in a qualitatively new and interesting way. Scientific activity has thus reached a new milestone somewhat comparable to the milestones that started the empirical approach (Galileo) and the deterministic mathematical approach to dynamics (the old syntax of Newton and Laplace). Computer simulation is consequently of considerable philosophical interest. In view of further technical developments in the near future, computer experts suggest that we are at present only at the very beginning of this new era.

Relations between conditional probabilities, revisions of probabilities in the light of new information, and conditions of ideal rationality are discussed herein. The formal character of conditional probabilities, and their significance for epistemic states of agents is taken up. Then principles are considered that would, under certain conditions, equate rationally revised probabilities on new information with probabilities reached by conditionalizing on this information. And lastly the possibility of kinds of ‘books’ against known non-conditionalizers is explored, and the question is taken up, What, if anything, would be wrong with a person against whom such a book could be made?

1. The standard mathematical treatment takes probability functions as basic, and conditional probabilities defined. If P(-) is a probability function, then is its conditional probability function if and only if P(h/e) is defined only for e such that P(e) > 0, and is then equal to P(e & h)/P(e).

The “Dutch Book” argument, tracing back to Ramsey (1926) and deFinetti (1974), offers prudential grounds for action in conformity with personal probability. Under several structural assumptions about combinations of stakes (that is, assumptions about the combination of wagers), your betting policy is consistent (coherent) only if your fair-odds are probabilities. The central question posed here is the following one: Besides providing an operational test of coherent betting, does the “Book” argument also provide for adequate measurement (elicitation) of the agent’s degrees of beliefs? That is, are an agent’s fair odds also his/her personal probabilities for those events?

We argue the answer is “No!” The problem is created by state-dependent utilities. The methods of elicitation proposed by Ramsey, by deFinetti and by Savage (1954), are inadequate to the challenge of state-dependent values.1

It’s uncontroversial that notions of idealization and approximation are central to understanding computer simulations and their rationale. So, for example, one common form of computer simulation is to abandon a realistic approach that is computationally non-tractable for a more idealized but computationally tractable approach. Many simulations of systems of interacting members can be understood this way. In such simulations, realistic descriptions of individual members are replaced with less realistic descriptions which have the virtue of making interactions computationally tractable. Such simulations can be supplemented with empirically determined correction factors which render the output produced by means of the idealizations more in accord, one hopes, with what the more realistic approach would have produced had it been computationally tractable. Another way to utilize computers is to replace an idealized but analytically tractable account of some phenomenon with a less idealized account which has no closed form or analytical solutions but where the computer can be used generate approximations to the desired solutions.

Philosophers of science have recently been urged by Arthur Fine to collaborate with physicists and with other scientists in constructing scientific theories.2 What I am proposing is a collaboration at the other pole of scientific activity; the pole of experiment.

I consider this effort to be part of a tendency within philosophy to naturalize epistemology. The banner of naturalistic epistemology has attracted such men as Quine and Goldman. I consider the effort as one small part of that program which involves not only theoretical integration of at least portions of the two corpuses of knowledge, but the employment of methodologies which are common to them both.

The theory of inductive logic today is in stasis. A number of highly ingenious and very sophisticated theories of inference vie for primacy. As in the case of many philosophical theses, no closure seems in sight.

In a paper fifteen years ago about the meaning and the possibility of the beginning and end of time, our redoubtable session chair, John Earman, ended up like this:

These remarks are a kind of manifesto of an approach to philosophical questions about space and time dating from the late 1960’s.

Humean accounts of law are at the same time accounts of causation. Accordingly, since laws of nature are nothing but contingent cosmic regularities, to be a cause is just to be an instance of such a law. It follows from this view that it is logically impossible that there be causally related events which are not law-governed. Any particular cause-effect pair instantiates some law of nature, where the law is understood as a regularity. The regularity itself may be understood phenomenalistically, that is, as holding between sense impressions, or realistically, that is, as holding between objective events or event-types. These days even empiricists are realists to some extent, so I will eschew the radically empiricist version and assume that when a Humean talks about regularities, he is referring to objective events, states or processes in nature, not to his subjective experiences.

Some of what is true about the world is thought, by some, to be true of necessity. Other truths about the world are merely contingently true, it is said. Next we get a familiar distinguishing of necessity into its various kinds. Anything whose contrary would contradict the laws of logic is logically necessary. Anything compatible with these laws is logically contingent. There are, of course, grave problems in finding a principled way of discriminating the logical truths from all the others. Some propositions are not logically necessary but are metaphysically necessary. For Kant, I suppose, the alleged facts that every event had a cause, and that in any change a substance remained unchanged would be such facts. So, I suppose, would be the necessary but synthetic truths of geometry and arithmetic. For more contemporary philosophers genuine identity statements, either singular or general, might have such a status.

How are causes and laws related? Some attempt to analyze causal relations in terms of laws, others view causal explanation as quite distinct from explanation using laws. My analysis of the relations between causes and laws focuses on cases such as the simple pendulum law where asymmetries in causal relations between quantities are not reflected in the functional dependencies in the law equations. The asymmetry puzzle has elicited a variety of accounts which reflect quite different views on the relation between causes and laws and their roles in scientific explanation. Finding none of the usual accounts satisfying, I offer an explication based on some distinctions in the analysis of the relevant causes that are not commonly heeded. I criticize the very notion of causal law and examine some implications of my account for ceteris paribus problems which arise in attempts to give realist interpretations of scientific theories.

This essay will survey various considerations that arise when a branch of physics requires formulation in terms of partial differential equations (or some facsimile thereof). My examples will derive almost exclusively from classical continuum (=smeared out matter) mechanics. Although the relevant formal facts are well known, it is difficult to find coherent discussions of how the underlying phenomena ought to be viewed. In this paper, I will give an introduction to some of the issues, although I will confess at the outset that I am not certain how these matters should be finally adjudicated. Certainly it would be helpful if philosophy paid more attention to the underlying issues.

Some of the points I will discuss bear upon some of Professor Sklar’s observations. Although my attention will be largely directed towards the status of boundary conditions (and related forms of singular surface), many of my examples can be adapted, mutatis mutandis, to initial conditions as well.

The question of how scientific hypotheses and theories should be evaluated in light of evidence has been a central question in philosophy of science. Far less attention has been given to the questions of how evidence is developed and is itself evaluated. From this neglect, one might assume that the processes by which scientists develop and evaluate evidence are unproblematic. An examination of the actual practice of experimental scientists, however, reveals that they are far from unproblematic. Much of the evidence used to assess scientific theories is gathered with elaborate instruments. At a given time many instruments used in a particular science are noncontroversial. The techniques for using them are agreed upon so that, in a fairly routine way, scientists are able to generate evidence to settle empirical or theoretical disputes. To capture the fact that such instruments and techniques are not questioned, Latour (1987) refers to them as black boxes.

Electron microscopy, and in particular low dose electron microscopy, offers interesting cases of experimental techniques where the theory of the phenomena studied and the theory of the apparatus used, are intertwined. A single primary exposure usually does not give an interpretable image, and computerized image enhancement techniques are used to create from multiple exposures a single, visually meaningful image. Some of the enhancement programs start from informed guesses at the structure of the specimen and use the primary exposures in a series of corrections to arrive at a image that can be read by trained observers.

In this paper I describe in the general deterministic case the possible relations between phenomena theory and instrument theory. I give a Bayesian criterion for when an experiment is a test of the theory of the apparatus, rather than a test of the theory of the phenomena, and describe strategies used to ensure that tests of the theory of the phenomena are possible.

In experimental scientific research, such as that conducted in High-Energy Physics (HEP), there are a number of problems which are unique to the experimental endeavor in contrast to theoretical research. The preparation of a sample of data to be analyzed requires a number of complicated and interrelated procedures to insure the purity or quality of the data. Thus, for example, in an experimental study of meson-baryon scattering, the separation of events of one type of scattering from others of similar configuration (see the discussion of different configurations in section II) requires intricate and sophisticated procedures along with the application of a number of criteria and standards of analysis. In the case of theoretical research, there are a number of philosophical discussions which formulate certain criteria or norms that theorists usually invoke in their evaluation of theories as well as in the actual choice of one theory over another.