Diachronic Dutch book arguments, or Dutch strategy arguments, have been used to recommend the rule of conditionalization (C) Jeffrey’s rule for fallible learning (J), and the principle of reflection (R). The arguments have been criticized in a variety of ways—more ways than can be discussed in this paper. Here we will look at two of the criticisms. As we proceed, it will become apparent how some criticisms not explicitly raised can be met; others will go unexamined. The criticisms are these: First, Dutch strategy arguments are said to fail as defenses of rules J and C, and principle R, because rational agents may violate each of those constraints, yet avoid vulnerability to a Dutch strategy; their knowledge of Dutch strategy arguments enables them to do this. Second, it is said to be no wonder that the arguments fail, because there are counter-examples to each of these purportedly general constraints on rational belief.

This paper will be a mirror image of Huw Price's paper. Like Price, I shall first introduce the “fork asymmetry”, then consider objections to using it to analyse causal asymmetry, and finally examine the relation between causation and human agency. But where Price rejects analyses of causal asymmetry in terms of the fork asymmetry, and so turns to human agency to ground an alternative account of both the causal and fork asymmetries, I defend the fork asymmetry analysis of causation, and correspondingly want to explain agency in terms of the fork asymmetry, rather than vice versa.

Logicism as a philosophical enterprise died a sudden and unnatural death in the early 1930s. The logicist program was an attempt to secure our mathematical knowledge in the indubitable bedrock of our a priori logical intuitions. It was a program very much impressed by the remarkable achievements in formal logic and axiomatics in the early century. While that program is well dead and gone, a research program within artificial intelligence (AI) has come to be known by the same name, sharing with its homonymous predecessor at least that program’s esteem for logic.

Logicism in AI, briefly, is the view that prerequisite to developing an artificially intelligent system we must find means for representing and reasoning with a vast store of prepositional knowledge and that the only viable candidates for representing prepositional knowledge are formal logics (and their associated formal languages).

Our present concern originales with two uncontroversial observations about causation: the causal relation is asymmetric, so that if Ais a cause of B then B is not a cause of A; and effects never (or almost never) occur before their causes. Uncontroversial as they may be, these features of causation are far from unproblematic. A philosophical theory of causation thus has these two non-trivial tasks, among others: to explicate the difference between cause and effect-to reveal the true content of the “arrow” of causation, so to speak-and to explain why the arrow of causation is so well aligned with the arrow of time.

Thought experiments present an enormous challenge to empiricism. So much so that some of us have (cheerfully) thrown in the towel and embraced good old fashioned platonism. I'll try to explain why, or at least, why one brand of empiricism won't work.

Nancy Cartwright’s new book Nature’s Capacities and their Measurement (1989)2 attempts to achieve something remarkable: refute Hume’s most crucial theses concerning causation and let in capacities largely through methodological arguments. The two central theses of Hume which Cartwright challenges are:

1. (1) Generic causal facts (e.g., causal laws) are reducible to regularities.

2. (2) Singular causal facts are true in virtue of generic causal facts.

Cartwright’s arguments against (1) and (2) are methodological in the sense that she arrives at her conclusions by considering our best methods for studying the relationship between probability and causation. Cartwright rejects (1) on the grounds that if we look at the way in which probabilities are related to causal relations as expressed in her principle CC, or if we carefully study the methodology of causal modelling employed in the social, behavioral, and life sciences, we see that to get certain causal information from probabilities we must presuppose the truth of other generic causal facts.

The priority of mathematics in the construction and deployment of the physical sciences has recently come under attack. Empiricism in the philosophy of mathematics, an offshoot of the trend towards naturalized epistemologies, subordinates formal disciplines to empirical facts (conceived variously as experience or experiment). (Kitcher 1983 and Maddy 1991) When allied with structuralism (Chihara 1973 and Resnik 1981,1982,1990), which denies to mathematics any specific subject matter of its own, it displaces intelligibility, heuristic force, and explanatory power away from mathematics into the realm of “fact”.

In this essay, I will argue that mathematics, and mechanics conceived as a formal science, do have their own proper subject matters, their own proper unities.

A thought experiment requires neither instrumentation nor embodied actors. Nor does it appear to introduce new empirical information about the world in which it is performed (Kuhn 1962, p. 241). Nevertheless, it presents some previously un-recognized property of that world with a logical force that no real experiment can match. Thought experiments are easy to replicate—this confers an important advantage over real ones, though the real advantage is thought to be that there is no need to conduct a real experiment in place of a thought experiment From a rationalist position such as Jim Brown's (1991, 1993) thought experiments are either mysterious or eise explicable in terms of our ability to intuit natural kinds directly. Empiricists such as John Norton (1991) regard them as disguised deductive arguments whose performance-reconstituted as formal arguments—discloses in the form of prernises, information we must already have.

After a lang period of neglect there has been a recent wave of interest in thought experiments in science, in mathematics, and in philosophy (See, e.g., Horowitz & Massey, 1991). I will restrict my analysis to thought experiments as they function in science, although I believe the account has implications for thought experiments, generally. The two most influential views on the topic in philosophy and history of science in this century represent the extremes of empiricism and rationalism. Pierre Duhem dismissed all thought experiments as bogus precisely because they are “not only not realized but incapable of being realized” (Duhem 1914, p.202).

Recently, several authors have attempted to characterise causation by identifying causal connections with physical processes. While this approach may not live up to providing a complete analysis of causation in all its contexts, it has raised some significant points regarding the causal role played by various entities described in natural laws. To date, much of the discussion has involved the attempted identification of physical terms or concepts that necessarily or sufficiently characterise causal processes, and has centered around three main contentions:

1. Cl. Causal processes involve the presence of forces, and that forces are themselves a species of primitive causes (e.g., Bigelow, et al. 1988).

2. C2. Causal processes necessarily involve transfer of a physically measurable quantity, such as energy-momentum (e.g., Aronson 1982 and Fair 1979).

3. C3. Causal processes necessarily involve microscopic interactions between “fundamental” entities, such as is described by quantum field theory (e.g., Heathcote 1989).

I believe that thought experiments do not have a life of their own. The tide of opinion is going the other way. That is evident from the ample citations provided by our three speakers. They include for example the outstanding collection ofpapers, edited by Tamara Horowitz and Gerald Massey (1991) with its wonderful editorial introduction that really does say what is in each paper. There are David Gooding's chapters (1990, chs. 8-10) on the relationships between Faraday's thought experiments and real experiments. There is James Brown's book (1991).

The overall character of the ideas Thomas S. Kuhn has offered concerning the nature of scientific inquiry has been generally misunderstood, or, rather, misconstrued. (See Kuhn 1957,1970.) Kuhn’s ideas do not add up to a fully articulated analysis of the structure of the scientific process. Kuhn does not offer a theory of science which should be evaluated in the same way as, e.g., the hypothetico-deductive model of science or the inductivist one. What Kuhn does is best viewed as calling our attention to certain salient phenomena which a philosophical theorist of science must try to understand and to account for. We do injustice to Kuhn if we deal with his views as if they were finished products of philosophical theorizing. They are not. Rather, they are starting-points for such theorizing; they pose problems to be solved by a genuine theory of science.

Criticisms of the effects of Western sciences and their technologies on Third World societies are not new to Westemers. For decades both Third World and Western authors have analyzed and protested the frequent ill effects in the Third World of Western asswnptions, concepts, paradigms and practices in health care, ecology, militarism, socalled economic “development” and its associated technology transfers.

The theory-ladenness of perception argument is not an argument at all. It is two clusters of arguments. The first cluster is empirical. These arguments typically begin with a discussion of one or more of the following psychological phenomena: (a) the conceptual penetrability of the visual system, (b) voluntary perceptual reversal of ambiguous figures, (c) adaptation to distorting lenses, or (d) expectation effects. From this evidence, proponents of theory-ladenness typically conclude that perception is in some sense “laden” with theory. The second cluster attempts to extract deep epistemological lessons from this putative fact Some philosophers conclude that science is not (in any traditional sense) a rational activity (Feyerabend 1975); while others conclude that we must radically reconceptualize what scientific rationality involves (Kuhn 1970; Churchland 1979).

I argue here that for the past thirty years there has been a persistent misreading of Thomas Kuhn’s The Structure of Scientific Revolutions. Not everybody has participated in this misreading, but its persistence is remarkable. So one of my tasks is to diagnose the reasons for its continuance. It is also an important misreading, because it attributes to Kuhn a view that is from most people’s perspective highly untenable, that scientists in some strong sense construct the world by choosing a paradigm.

To avoid repeating work done by Gutting and many others (see Gutting 1980) I will focus on Kuhn’s constructivist metaphysical program, as seen by commentators.

When we think of the relationship between women and science, many of us think of a wholesome array of benefits bestowed on women by science: safer and less painful childbirth and lower infant mortality rates, labor-saving conveniences for the home like washing machines, froren foods, and no-iron fabrics, the exposure and criticism of unhelpful superstitions and prejudices, and the like. For some time now, however, ferninists have been pointing an accusing finger at science, urging that the relationship between women and science has been far from a beneficial one for women.

Variation is the fuel of evolution, but as is well known, not all variation will drive Darwin’s engine along. Within population genetics, “additivity” is one concept used to characterize the salient type of variation. The characterization of variation (variance) in terms of additivity originates with R.A. Fisher (1918), and Fisher’s “fundamental theorem of natural selection” (1930) states that the rate of evolutionary change is proportional to the additive variance in fitness in the population at that time. Evolution proceeds until the additive variance is exhausted.

It would not be surprising if a concept so important in the mathematical structure of evolutionary theory had philosophical significance. In two important works, William Wimsatt (1981) and Elisabeth Lloyd (1988) have claimed that additivity can be used to give a criterion for deciding the “unit of selection” in an evolutionary process.

The invitation to participate in this symposium was accompanied by a proposal indicating that the symposium topic was “Can we do philosophy of science without taking lnto account the gender, race, and class of scientists?” My own views on the relation of gender, race, class, and science contain an answer to this question, but in the main they run slightly aslant of it. Since my previous work bringing together philosophy of science and questions of gender has consisted in using philosophy to illuminate the role gender and associated ideologies play in certain selected research programs, I took the question as a challenge to articulate a closer relation between gender questions and the philosophy of science or—better—between gender questions and my own approach to the philosophy of science.

I want to discuss Sandra Harding's claims to the effect that issues conceming race and gender lead, or should lead philosophy of science in new directions. In particular I wish to concentrate on her attempt to extend her previous feminist critique of science to include concems about racism as weil. That attempt is best found in her recent book Whose Science? Whose Knowledge? (1991, page numbers without further attribution will refer to this book) and in her contribution to this symposium.

Ever since the publication of his biophilosophical ideas in the early seventies, Jacques Monod has always been criticized quite severely for his old-fashioned philosophical reductionism. These numerous critiques have created a picture of an eminent scientist whose philosophical considerations are founded on the mechanistic worldview of Cartesian metaphysics, a view which is completely unacceptable to contemporary philosophers. Today it is the usual practice to cite Monod as one of the strongest and most radical reductionists in modem biology.

Monod’s biophilosophical conception arose at a moment when vigorous discussions on reductionism followed the great successes of molecular biology. His ideas were criticized namely for their strongly reductionistic interpretation of biological knowledge, and for their mechanistic model of life which, as Monod believed, reflected the spirit of modem science.