Robert Hudson’s book is a contribution to the recent debate on robustness analysis in scientific practice, with a specific focus on the empirical sciences. In this context, robustness analysis is defined as a way to increase the probability of a certain hypothesis by showing that the same result is obtained from several, alternative methods. The rationale underlying this practice is that it would be highly unlikely if different, independent means of observation provided the same wrong outcome.We do not believe in (...) miracles; hence, the probability of the initial hypothesis being true increases if the same result occurs across conditions.Simple as this notion sounds, according to Hudson, the various attempts that have been offered in the literature to formalize it have proved to be unsuccessful. Hudson’s skeptical argument is formulated at the outset of the book and illustrated throughout by means of several episodes from the recent history of science, mainly from physics and biology. Met .. (shrink)

This paper is an essay review of Steven French and Harmke Kamminga (eds.), Correspondence, Invariance and Heuristics. Essays in Honour of Heinz Post (Dordrecht: Kluwer, 1993). I distinguish a varity of correspondence relations between scientific theories (exemplified by cases from the book under review) and examine how one can make sense of the the prevailing continuity in scientific theorizing.

Effective field theories have been a very popular tool in quantum physics for almost two decades. And there are good reasons for this. I will argue that effective field theories share many of the advantages of both fundamental theories and phenomenological models, while avoiding their respective shortcomings. They are, for example, flexible enough to cover a wide range of phenomena, and concrete enough to provide a detailed story of the specific mechanisms at work at a given energy scale. So will (...) all of physics eventually converge on effective field theories? This paper argues that good scientific research can be characterised by a fruitful interaction between fundamental theories, phenomenological models and effective field theories. All of them have their appropriate functions in the research process, and all of them are indispensable. They complement each other and hang together in a coherent way which I shall characterise in some detail. To illustrate all this I will present a case study from nuclear and particle physics. The resulting view about scientific theorising is inherently pluralistic, and has implications for the debates about reductionism and scientific explanation. (shrink)

If you believe more things you thereby run a greater risk of being in error than if you believe fewer things. From the point of view of avoiding error, it is best not to believe anything at all, or to have very uncommitted beliefs. But considering the fact that we all in fact do entertain many specific beliefs, this recommendation is obviously in flagrant dissonance with our actual epistemic practice. Let us call the problem raised by this apparent conflict the (...) Addition Problem. In this paper we will find reasons to reject a particular premise used in the formulation of the Addition Problem, namely, the fundamental premise according to which believing more things increases the risk of error. As we will see, acquiring more beliefs need not decrease the probability of the whole, and hence need not increase the risk of error. In fact, more beliefs can mean an increase in the probability of the whole and a corresponding decrease in the risk of error. We will consider the Addition Problem as it arises in the context of the coherence theory of epistemic justification, while keeping firmly in mind that the point we wish to make is of epistemological importance also outside the specific coherentist dispute. The problem of determining exactly how the probability of the whole system depends on such factors as coherence, reliability and independence will be seen to open up an interesting area of research in which the theory of conditional independence structures is a helpful tool. (shrink)

We develop a probabilistic criterion for belief expansion that is sensitive to the degree of contextual fit of the new information to our belief set as well as to the reliability of our information source. We contrast our approach with the success postulate in AGM-style belief revision and show how the idealizations in our approach can be relaxed by invoking Bayesian-Network models.