Bas C. Van Fraassen

This is surely a bit of Socrates' famous irony. He draws the analogy to explain how his friends should regard poetry as they regretfully banish it from the ideal state. But lovers were no more sensible then than they are now. The advice to banish poetry, undermined already by Plato's own delight and skill in drama, is perhaps undermined still further by this evocation of a 'sensible' lover who counts love so well lost. Yet Socrates' image is one of avowed rationality and prudence. The sensible lover imitates the older literary example of Ulysses' tying himself to the mast. (The example belongs therefore to the class of problems treated in Elster (1979)). Both this lover and Ulysses foresee that under certain possible future conditions, their opinions, values and preferences will or would differ from what they are now, in a very definite fashion. To what extent is such foresight possible? Correspondingly (when we do not claim foreknowledge) to what extent is such opinion reasonable, rational, coherent, or consistent in some suitably broad sense? It is not easy to understand exactly what is possible or even logically permissible in this respect. In an earlier paper, "Belief and the Will", I argued for a principle ("Reflection") to govern such deliberation. Here I will both generalize the treatment of opinion in "Belief and the Will" and respond to criticism. Critical examples mainly resembled the story of Ulysses who foresaw a period of dysfunction (at the sound 2 of the sirens) in his epistemic and/or doxastic future. Other criticism focused on the model of opinion used (precise numerical subjective probability) and on the merits of Dutch Book arguments. The present argument will not rely on Dutch Book arguments and strategies, and the Reflection principle will be formulated so as to apply also to vague opinion

This chapter examines and criticizes the main arguments offered for scientific realism, here identified as the following view: Science aims to give us, in its theories, a literally true story of what the world is like; and acceptance of a scientific theory involves the belief that it is true. In contrast, constructive empiricism, which also opts for a literal understanding of scientific language, is the following view: Science aims to give us theories which are empirically adequate; and acceptance of a theory involves as belief only that it is empirically adequate. Topics examined include the ’theory/observation dichotomy’, observable versus unobservable entities, epistemology and the epistemic community, inference to the best explanation, principle of the common cause, and fictionalism. The views of Smart, Sellars, Reichenbach, Putnam, and Dummett are considered. It is argued that the arguments offered for scientific realism, though telling against logical positivism, do not support it over and against constructive empiricism.

Foundational research focuses on the theory, but theories are to be related also to other theories, experiments, facts in their domains, data, and to their uses in applications, whether of prediction, control, or explanation. A theory is to be identified through its class of models, but not so narrowly as to disallow these roles. The language of science is to be studied separately, with special reference to the relations listed above, and to the consequent need for resources other than for theoretical description. Peculiar to the foundational level are questions of completeness (specifically in the representation of measurement), and of interpretation (a topic beset with confusions of truth and evidence, and with inappropriate metalinguistic abstraction)

Probabilism in epistemology does not have to be of the Bayesian variety. The probabilist represents a person''s opinion as a probability function; the Bayesian adds that rational change of opinion must take the form of conditionalizing on new evidence. I will argue that this is the correct procedure under certain special conditions. Those special conditions are important, and instantiated for example in scientific experimentation, but hardly universal. My argument will be related to the much maligned Reflection Principle (van Fraassen, 1984, 1995), and partly inspired by the work of Brian Skyrms (1987).

The question of David Armstrong's recent book, What Is a Law of Nature? would seem to have little point unless there really are laws of nature. However that may be, so much philosoFhical thinking has utilized this concept, that an inquiry of this sort was needed whether there are or not. The book begins with a devastating attack on so-called Regularity views of law, and then proceeds with an exposition of Armstrong's own answer to the question. I wish to raise here some difficulties for Armstrong's answer, concentrating on his account of probabilistic laws where I see the severest problems. To locate myself with respect to his approach, however, I shall first enter some lesser demurrals.

What is empiricism? There can be no authoritative answer to any such question. A historian of philosophy can at best try to call what is common to philosophers who either identified themselves, or have traditionally been identified, as empiricists. But what has set those philosophers apart from others, and especially from those whom they criticized, may not be captured in common views or doctrines. The historian may, in trying to fix the label, rely tacitly on a view of what philosophical positions are and how they are to be identified. Finally, it is typical of philosophers who decide to range themselves under some pre-existing banner ("empiricism", "pragmatism", "phenomenology") to change the very philosophy they take on, as much as did their historical heroes in their day. I will here try to give a sustained argument about what empiricism cannot be, and then enter upon a tentative exploration of what it should be (taken to be).

Experimental modeling is the construction of theoretical models hand in hand with experimental activity. As explained in Section 1, experimental modeling starts with claims about phenomena that use abstract concepts, concepts whose conditions of realization are not yet specified; and it ends with a concrete model of the phenomenon, a model that can be tested against data. This paper argues that this process from abstract concepts to concrete models involves judgments of relevance, which are irreducibly normative. In Section 2, we show, on the basis of several case studies, how these judgments contribute to the determination of the conditions of realization of the abstract concepts and, at the same time, of the quantities that characterize the phenomenon under study. Then, in Section 3, we compare this view on modeling with other approaches that also have acknowledged the role of relevance judgments in science. To conclude, in Section 4, we discuss the possibility of a plurality of relevance judgments and introduce a distinction between locally and generally relevant factors