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).

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).

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

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.

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.

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.

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.