It is commonplace to distinguish between propositional justification (having good reasons for believing p) and doxastic justification (believing p on the basis of those good reasons).One necessary requirement for bridging the gap between S’s merely having propositional justification that p and S’s having doxastic justification that p is that S base her belief that p on her reasons (propositional justification).A plausible suggestion for what it takes for S’s belief to be based on her reasons is that her reasons must contribute (...) causally to S’s having that belief. Though this suggestion is plausible, causal accounts of the basing relation that have been proposed have not fared well. In particular, cases involving causal deviancy and cases involving over-determination have posed serious problems for causal accounts of the basing relation. Although previous causal accounts of the basing relation seem to fall before these problems, it is possible to construct an acceptable causal account of the basing relation. That is, it is possible to construct a causal account of the basing relation that not only fits our intuitions about doxastic justification in general, but also is not susceptible to the problems posed by causal deviancy and causal over-determination. The interventionist account of causation provides the tools for constructing such an account. My aim is to make use of the insights of the interventionist account of causation to develop and defend an adequate causal account of the basing relation. (shrink)

This essay offers a history of the development of philosophy of economics from the 1830s until today, with a personal perspective on the developments of the last four decades. It argues that change...

Process theories of causality seek to explicate causality as a property of individual causal processes. This paper examines the capacity of such theories to account for the asymmetry of causation. Three types of theories of asymmetry are discussed; the subjective, the temporal, and the physical, the third of these being the preferred approach. Asymmetric features of the world, namely the entropic and Kaon arrows, are considered as possible sources of causal asymmetry and a physical theory of asymmetry is subsequently developed (...) with special reference to the questions of objectivity and backwards causation. (shrink)

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. (shrink)

This paper offers a defense of backwards in time causation models in quantum mechanics. Particular attention is given to Cramer's transactional account, which is shown to have the threefold virtue of solving the Bell problem, explaining the complex conjugate aspect of the quantum mechanical formalism, and explaining various quantum mysteries such as Schrödinger's cat. The question is therefore asked, why has this model not received more attention from physicists and philosophers? One objection given by physicists in assessing Cramer's theory was (...) that it is not testable. This paper seeks to answer this concern by utilizing an argument that backwards causation models entail a fork theory of causal direction. From the backwards causation model together with the fork theory one can deduce empirical predictions. Finally, the objection that this strategy is questionable because of its appeal to philosophy is deflected. (shrink)

This essay defends two theses that jointly establish a link between causal and explanatory asymmetry. The first thesis is that statements specifying facts about effects, unlike statements specifying facts about causes, are not "independently variable". The second thesis is that independent variability among purportedly explanatory factors is a necessary condition on scientific explanations.

Temporal analyses of causal directionality fail if causes needn't precede their effects. Certain well-known difficulties with alternative (non-temporal) analyses have, in recent accounts, been avoided by attending more carefully to the formal features of relations typically figuring in philosophical discussions of causation. I discuss here a representative of such accounts, offered by David Sanford, according to which a correct analysis of causal priority must issue from viewing the condition relation as nonsymmetrical. The theory is shown first to be an implicitly (...) counterfactual treatment at its base: this provides for an explicit reformulation of several key notions in the theory. An argument is then presented, independent of these modal considerations, for the conclusion that causal priority is possible only given certain implausible assumptions about the asymmetric character of causal laws which, I claim, are not met. The best objection to this argument is shown to fail on several counts, partly in light of the counterfactual results offered earlier. It is concluded that, if laws are symmetric, analyses of the sort discussed must look elsewhere for the source of causal priority; but if laws are not symmetric, resting causal priority so heavily on nomological asymmetry is no analysis at all. (shrink)

The computer’s effect on our understanding of causation has been enormous. By the mid‐1980s, philosophical and social‐scientific work on the topic had left us with (1) no reasonable reductive account of causation and (2) a class of statistical causal models tied to linear regression. At this time, computer scientists were attacking the problem of equipping robots with models of the external that included probabilistic portrayals of uncertainty. To solve the problem of efficiently storing such knowledge, they introduced Bayes Networks and (...) directed graphs. By attaching a causal interpretation to Bayes Networks, the philosophy of causation changed dramatically. We are now able to be extremely general about how causal structure connects to data, and systematic about when causal structures are empirically indistinguishable. In this essay I try to motivate and describe this synthesis. (shrink)