Online research in philosophy

Approaches to explanation -- Causal and explanatory relevance -- The kairetic account of /D making -- The kairetic account of explanation -- Extending the kairetic account -- Event explanation and causal claims -- Regularity explanation -- Abstraction in regularity explanation -- Approaches to probabilistic explanation -- Kairetic explanation of frequencies -- Kairetic explanation of single outcomes -- Looking outward -- Looking inward.

Nancy Cartwright relies upon an inference pattern known as inference to the best causal explanation (IBCE) to support a limited form of entity realism, according to which we are warranted in believing in entities that purportively cause observable effects. IBCE, as usually understood, is valid, even though all other forms of inference to the best explanation (IBE) are usually understood to be invalid. We argue that IBCE and IBE are in the same boat with respect to their ability to support realist conclusions. Either rule can be interpreted as valid, this is a matter of semantic convention. However, doing so deprives the rule of the empirical content the realist needs, requiring the realist to find independent warrant for a strong (theoretical or causal) premise. We then examine the proposed means of obtaining this warrant, and find them as inadequate in the case of IBCE as they are in the case of IBE.

Cartwright argues for being a realist about theoretical entities but non-realist about theoretical laws. Her reason is that while the former involves causal explanation, the latter involves theoretical explanation; and inferences to causes, unlike inferences to theories, can avoid the redundancy objection--that one cannot rule out alternatives that explain the phenomena equally well. I sketch Cartwright's argument for inferring the most probable cause, focusing on Perrin's inference to molecular collisions as the cause of Brownian motion. I argue that either the inference she describes fails to be a genuinely causal one, or else it too is open to the redundancy objection. However, I claim there is a way to sustain Cartwright's main insight: that it is possible to avoid the redundancy objection in certain cases of causal inference from experiments (e.g., Perrin). But, contrary to Cartwright, I argue that in those cases one is able to infer causes only by inferring some theoretical laws about how they produce experimental effects.

Many cosmological arguments for the existence of a first cause or a necessary being rely on a premise which denies the possibility of an infinite regress ofsome particular sort. Adequate and satisfying support for this premise, however, is not always provided. In this paper I attempt to address this gap in the literature. After discussing the notion of a causal explanation (section I), I formulate three principles which govern any successful causal explanation (section II). I then introduce the notions of a caused being, a causal network, and a causal chain, and argue that (roughly) an infinite causal chain cannot be explained merely by reference to the causal activities of the members of that chain (section III). In a sequel to the present paper, I employ this result to construct two closely related arguments for the existence of a necessary being.

In the literature on scientific explanation two types of pluralism are very common. The first concerns the distinction between explanations of singular facts and explanations of laws: there is a consensus that they have a different structure. The second concerns the distinction between causal explanations and uni.cation explanations: most people agree that both are useful and that their structure is different. In this article we argue for pluralism within the area of causal explanations: we claim that the structure of a causal explanation depends on the causal structure of the relevant fragment of the world and on the interests of the explainer.

I advance a new theory of causal relevance, according to which causal claims convey information about conditional probability functions. This theory is motivated by the problem of disjunctive factors, which haunts existing probabilistic theories of causation. After some introductory remarks, I present in Section 3 a sketch of Eells's (1991) probabilistic theory of causation, which provides the framework for much of the discussion. Section 4 explains how the problem of disjunctive factors arises within this framework. After rejecting three proposed solutions, I offer in Section 6 a new approach to causation that avoids the problem. Decision-theoretic considerations also support the new approach. Section 8 develops the consequences of the new theory for causal explanation. The resulting theory of causal explanation incorporates the new insights while respecting important work on scientific explanation by Salmon (1971), Railton (1981), and Humphreys (1989). My conclusions are enumerated in Section 9.

This paper is an empirical critique of causal accounts of scientific explanation. Drawing on explanations which rely on nonlinear dynamical modeling, I argue that the requirement of causal relevance is both too strong and too weak to be constitutive of scientific explanation. In addition, causal accounts obscure how the process of mathematical modeling produces explanatory information. I advance three arguments for the inadequacy of causal accounts. First, I argue that explanatorily relevant information is not always information about causes, even in cases where the explanandum has an identifiable causal history. Second, I argue that treating theoretical explanations as reductions from general causal laws does not accurately describe the types of "top-down" explanations typical of dynamical modeling. Finally, I argue that causal/mechanical accounts of explanation are intrinsically vulnerable to the irrelevance problem.

Hacking (1983) introduces an attempt to defend scientific realism on the basis of the reality of theoretical entities. This position, which is called entity realism, is based on disconnecting the reality of theoretical entities from the truth and explanatory power of theories that account for them. In this way, two problems can be avoided. First if theories about theoretical entities are rejected, the entities themselves do not have to go with them, and the realist thesis that we can have knowledge of what exists in the world can be sustained. Second, theoretical entities, which will replace theories as the grounds for the realist position, would be protected from attacks on the validity of the inference to the best explanation which underlies classical or "theory" realism. In other words, theoretical entities would be able to survive the collapse of the inference to the best explanation. The subject of this paper is a critique of this line of defending realism.

One of Nancy Cartwright's arguments for entity realism focuses on the non-redundancy of causal explanation. In How the Laws of Physics Lie she uses an example from laser theory to illustrate how we can have a variety of theoretical treatments governing the same phenomena while allowing just one causal story. In the following I show that in the particular example Cartwright chooses causal explanation exhibits the same kind of redundancy present in theoretical explanation. In an attempt to salvage Cartwright's example the causal explanation could be reinterpreted as a capacity claim, as outlined in her recent work Nature's Capacities and Their Measurement. However, I argue that capacities cannot be isolated in the way that Cartwright suggests and consequently these capacity claims also fail to provide a unique causal story. We can, however, make sense of capacities by characterizing them in a relational way and I offer some ideas as to how this approach would retain our intuitions about capacities while denying their ontological priority as dormant powers.

In this paper I develop five worries concerning Cartwright’s realism about entities and capacities. The first is that while she was right to insist on the ontic commitment that flows from causal explanation, she was wrong to tie these commitments solely to the entities that do the causal explaining. This move obscured the nature of causal explanation and its connection to laws. The second worry is that when she turned her attention to causal inference, by insisting on the motto of ‘the most likely cause’, she underplayed her powerful argument for realism. For she focused her attention on an extrinsic feature of causal inference (or, indeed, of any ampliative inference), that is the demand of high probability, leaving behind the intrinsic qualities that causal explanation should have in order to provide the required understanding. The third worry is that her objections to Inference to the Best Explanation were unnecessarily tied to her objections about the falsity of fundamental laws. The fourth worry is that though her argument for positing capacities and being realist about them was supposed to take strength from its parallel with Sellars’s powerful argument for the indispensable explanatory role of positing unobservable entities, there are important disanalogies between the two arguments which cast doubt on the indispensability of capacities. The final (fifth) worry is that laws—perhaps brute regularities—might well have to come back from the front door, since they are still the most plausible candidates for explaining why objects have the capacities to do what they can do.