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

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).

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)

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

This collection of essays is dedicated to 'Joe' Karel Lambert. The contributors are all personally affected to Joe in some way or other, but they are definitely not the only ones. Whatever excuses there are - there are some -, the editors apologize to whomever they have neglected. But even so the collection displays how influential Karel Lambert has been, personally and through his teaching and his writings. The display is in alphabetical order - with one exception: Bas van Fraassen, being about the earliest student of Karel Lambert, opens the collection with some reminiscences. Naturally, one of the focal points of this volume is Lambert's logical thinking and (or: freed of) ontological thinking. Free logic is intimately connected with description theory. Bas van Fraassen gives a survey of the development of the area, and Charles Daniels points to difficulties with definite descriptions in modal contexts and stories. Peter Woodruff addresses the relation between free logic and supervaluation semantics, presenting a novel condition which recovers desirable metatheoretic properties for free logic under that semantics. Terence Parsons shows how free logic can be utilized in interpreting sentences as purporting to denote events (true ones succeed and false ones fail) and how this helps to understand natural language.

Probability kinematics is the theory of how subjective probabilities change with time, in response to certain constraints . Rules are classified by the imposed constraints for which the rules prescribe a procedure for updating one's opinion. The first is simple conditionalization , and the second Jeffrey conditionalization . It is demonstrated by a symmetry argument that these rules are the unique admissible rules for those constraints, and moreover, that any probability kinematic rule must be equivalent to a conditionalization preceded by a determination of the values x i to be given to the members of such a partition. Next two rival rules which can go beyond such conditionalization are described. INFOMIN and MTP . Their properties are investigated and compared

Vague subjective probability may be modeled by means of a set of probability functions, so that the represented opinion has only a lower and upper bound. The standard rule of conditionalization can be straightforwardly adapted to this. But this combination has difficulties which, though well known in the technical literature, have not been given sufficient attention in probabilist or Bayesian epistemology. Specifically, updating on apparently irrelevant bits of news can be destructive of one’s explicitly prior expectations. Stability of vague subjective opinion appears to need a more complex model.