A number of philosophers of medicine have attempted to provide analyses of health and disease in which the role that values play in those concepts is restricted. There are three ways in which values can be restricted in the concepts of health and disease. They can be: (i) eliminated, (ii) tamed or (iii) corralled. These three approaches correspond, respectively, to the work of Boorse, Lennox, and Wakefield. The concern of each of these authors is that if unrestricted values are allowed (...) to infect our concepts of health and disease, then anything could be construed as healthy or diseased. They believe that, if at all possible, such a result should be avoided. Unfortunately, as I argue, this result is unavoidable and such attempts to limit values in these concepts are destined to fail. I argue for this position by showing how each of these three attempts to provide value-restricted analyses of health and disease fail as analyses of the concepts of health and disease and that they fail because of their attempts to restrict the role of values in their accounts. I also show how, despite their best efforts, each of these analyses are, themselves, value-driven and value-laden. This leads to the conclusion that values infect our concepts of health and disease at all levels. (shrink)

This paper is a response to Forster and Sober's [1994] solution to the curve-fitting problem. If their solution is correct, it will provide us with a solution to the New Riddle of Induction as well as provide a basis for choosing realism over conventionalism. Examining this solution is also important as Forster and Sober incorporate it in much of their other philosophical work (see Forster [1995a, b, 1994] and Sober [1996, 1995, 1993]). I argue that Forster and Sober's solution is (...) subject precisely to the problem they seek to solve. They provide a method of choosing among hypotheses but only at the cost of requiring that we have a method of choosing between different ways of conceptualizing the world. Thus the solution raises a new problem--the world-fitting problem. (shrink)

In The Chances of Explanation, Paul Humphreys presents a metaphysical analysis of causation. In this paper, I argue that this analysis is flawed. Humphreys' model of Causality incorporates three completeness requirements. I show that these completeness requirements, when applied in the world, force us to take causally irrelevant factors to be causally relevant. On this basis, I argue that Humphreys' analysis should be rejected.

In The Chances of Explanation, Paul Humphreys presents a metaphysical analysis of causation. In this paper, I argue that this analysis is flawed. Humphreys' model of Causality incorporates three completeness requirements. I show that these completeness requirements, when applied in the world, force us to take causally irrelevant factors to be causally relevant. On this basis, I argue that Humphreys' analysis should be rejected.

Within the last decade a new crop of theories of probabilistic causality has taken root. While these theories differ from each other in small ways, the basic principles underlying them are the same. These common principles form what I call the received view of probabilistic causality. ;In the first four chapters of the dissertation I examine and criticize the work of three proponents of the received view: Nancy Cartwright, Ellery Eells, and Paul Humphreys. Due to a number of epistemic and (...) pragmatic problems that each of these theories face, I argue that they are inadequate theories of probabilistic causality. ;In chapter six I examine the minimal set of principles that underlie these three theories--the received view of probabilistic causality. I show that the received view is an inadequate basis for a theory of probabilistic causality. The central problem for the received view is due to the interpretation of probability that the received view adopts--a physical-propensity interpretation of the probability calculus. I show that there are four problems with using the propensity interpretation of probability in a theory of probabilistic causality. I also argue that a theory of probabilistic causality should use relative frequencies in place of propensities. ;In the final chapter of the dissertation, I sketch an epistemic theory of probabilistic causality that has a number of advantages over the received view. First, the epistemic theory takes seriously and responds to the epistemic and pragmatic problems raised against Cartwright, Eells, and Humphreys' theories of probabilistic causality. Second, the epistemic theory adopts a relative frequency interpretation of probability and avoids the problems associated with using a propensity interpretation of probability. Finally, the epistemic theory provides an account of how we can make justified inferences regarding causal relations. ;I support my theory with examples from contemporary medical science. In particular, I provide a detailed historical examination of the attempt by medical scientists to determine whether Helicobacter pylori is a causal factor for various forms of gastric illness. (shrink)