Causal Exclusion and Causal Bayes Nets

In this paper I reconstruct and evaluate the validity of two versions of causal exclusion arguments within the theory of causal Bayes nets. I argue that supervenience relations formally behave like causal relations. If this is correct, then it turns out that both versions of the exclusion argument are valid when assuming the causal Markov condition and the causal minimality condition. I also investigate some consequences for the recent discussion of causal exclusion arguments in the light of an interventionist theory of causation such as Woodward's ( 2003 ) and discuss a possible objection to my causal Bayes net reconstruction.     

Causal inference

Conclusion We have examined only a few of the basic questions about causal inference that result from Reichenbach's two principles. We have not considered what happens when the probability distribution is a mixture of distributions from different causal structures, or how unmeasured common causes can be detected, or what inferences can reliably be drawn about causal relations among unmeasured variables, or the exact advantages that experimental control offers. A good deal is known about these questions, and there is a good deal more to find out.We thank the Office of Naval Research and the Navy Personnel Research and Development Center for supporting this research. Proofs of theorems will be found in Spirtes, Glymour, and Scheines (1991).     

Causal reasoning

The main focus of this paper is the question as to what it is for an individual to think of her environment in terms of a concept of causation, or causal concepts, in contrast to some more primitive ways in which an individual might pick out or register what are in fact causal phenomena. I show how versions of this question arise in the context of two strands of work on causation, represented by Elizabeth Anscombe and Christopher Hitchcock, respectively. I then describe a central type of reasoning that, I suggest, a subject has to be able to engage in, if we are to credit her with causal concepts. I also point out that this type of reasoning turns on the idea of a physical connection between cause and effect, as articulated in recent singularist approaches of causation.     

Causal Probability

Examples growing out of the Newcomb problem have convinced many people that decision theory should proceed in terms of some kind of causal probability. I endorse this view and define and investigate a variety of causal probability. My definition is related to Skyrms' definition, but proceeds in terms of objective probabilities rather than subjective probabilities and avoids taking causal dependence as a primitive concept.     

Causal Closure,Causal Exclusion,and Supervenience Physicalism

This article considers the recent defense of the supervenience approach to physicalism due to Jaegwon Kim. Kim argues that supervenience supports physical causal closure, and that causal closure supports physicalism – indeed, a kind of reductive physicalism – and thus that supervenience suffices for physicalism. After laying out Kim's argument, I ask whether its success would truly vindicate the role of supervenience in defining physicalist positions. I argue that it would not, and that insofar as Kim's defense of supervenience physicalism succeeds, it does so by showing that supervenience physicalism is not a unique, nonredundant way to be a physicalist.     

Abstracta Are Causal

Philosophia - Many philosophers think all abstract objects are causally inert. Here, focusing on novels, I argue that some abstracta are causally efficacious. First, I defend a straightforward...     

Causal decision theory

On the dominant view of vagueness, if it is vague whether Harry is bald, then it is unsettled, not merely epistemically, but metaphysically, whether Harry is bald. In other words, vagueness is a type of indeterminacy. On the standard alternative, vagueness is a type of ignorance: if it is vague whether Harry is bald, then, even though it is metaphysically settled whether Harry is bald, we cannot know whether Harry is bald. On my view, vagueness is neither a type of indeterminacy nor a type of ignorance. Rather, it is sui generis.     

The Causal Exclusion Argument

Jaegwon Kim’s causal exclusion argument says that if all physical effects have sufficient physical causes, and no physical effects are caused twice over by distinct physical and mental causes, there cannot be any irreducible mental causes. In addition, Kim has argued that the nonreductive physicalist must give up completeness, and embrace the possibility of downward causation. This paper argues first that this extra argument relies on a principle of property individuation, which the nonreductive physicalist need not accept, and second that once we get clear on overdetermination, there is a way to reject the exclusion principle upon which the causal exclusion argument depends, but third that this should not lead to the belief that mental causation is easily accounted for in terms of counterfactual dependencies.     

Super-learning of Causal Judgements

In three experiments, participants learned which of a variety of foods were capable of causing an allergic reaction in a hypothetical patient during training in which a compound of a treatment and a target food cue was paired with the reaction. In Experiment 1 the causal ratings of the target cue were increased if the treatment cue was pretrained as a preventative cause of the reaction. Experiments 2 and 3 demonstrated that the magnitude of this superlearning is unaffected by the order of compound and treatment cue training. The final study also showed that forward super-learning is not induced solely by simple exposure to the treatment cue prior to compound training but, rather, depends upon training the treatment cue as a preventative cause, whereas retrospective super-learning may be due merely to exposure of the treatment cue. These results are problematic for contingency-based accounts of causal induction but accord with modified and extended associative theories.