Christopher Hitchcock

Explanatory generalizations, part I: A counterfactual account

[Introduction] The nomothetic conception of explanation, according to which all successful explanations must appeal to laws, has dominated the discussion of scientific explanation in the second half of the twentieth century. The best known formulation of the nomothetic conception of explanation is, of course, Hempel’s Deductive-Nomological theory of explanation. While few philosophers today accept the D-N theory of explanation in its original formulation, there is widespread consensus that laws play a central role in explanation, even among prominent critics of the D-N model such as Wesley Salmon (see, e.g., Salmon 1984, p. 262).

Prediction Versus Accommodation and the Risk of Overfitting

When a scientist uses an observation to formulate a theory, it is no surprise that the resulting theory accurately captures that observation. However, when the theory makes a novel prediction—when it predicts an observation that was not used in its formulation—this seems to provide more substantial confirmation of the theory. This paper presents a new approach to the vexed problem of understanding the epistemic difference between prediction and accommodation. In fact, there are several problems that need to be disentangled; in all of them, the key is the concept of overfitting. We float the hypothesis that accommodation is a defective methodology only when the methods used to accommodate the data fail to guard against the risk of overfitting. We connect our analysis with the proposals that other philosophers have made. We also discuss its bearing on the conflict between instrumentalism and scientific realism. 1. Introduction2. Predictivisms—a taxonomy3. Observations4. Formulating the problem5. What might Annie be doing wrong?6. Solutions7. Observations explained8. Mayo on severe tests9. The miracle argument and scientific realism10. Concluding comments Introduction Predictivisms—a taxonomy Observations Formulating the problem What might Annie be doing wrong? Solutions Observations explained Mayo on severe tests The miracle argument and scientific realism Concluding comments

Explanatory generalizations, part II: Plumbing explanatory depth

[Introduction] Some explanations are deep and powerful: Newton’s explanation of the tides, Maxwell’s explanation of the propagation of light, Einstein’s explanation of the advance of the perihelion of Mercury. Other explanations, while deserving of the name, are superficial and shallow: Bob lashed out at Tom because he was angry, the car accelerated because Mary depressed the gas pedal with her foot, the salt dissolved because it was placed in water. We take this intuition to be very natural and widely shared. Yet in the vast philosophical literature on explanation, there have been precious few attempts to give any systematic account of this notion of explanatory depth. In this paper, we will provide such an account from within the framework of the manipulationist account of explanation presented in a companion paper (Woodward and Hitchcock 2003, hereafter referred to as EG1; see also Woodward 1997a, 2000).

Prevention, Preemption, and the Principle of Sufficient Reason

[Introduction] One event, e, counterfactually depends upon another event, c, just in case e would not have occurred had c not occurred. Beginning with the seminal paper of David Lewis in 1973, there has been a lively philosophical tradition of trying to analyze token causation in terms of counterfactual dependence. The simplest possible counterfactual theory of token causation—henceforth the simple theory—would identify token causation with counterfactual dependence: c is a token cause of e just in case e counterfactually depends upon c. This simple account is threatened by counterexamples on both sides. Some authors, but by no means all, take cases of prevention and omission to show that there can be counterfactual dependence without token causation. Cases of preemption have been widely taken to show that there can be token causation without counterfactual dependence; many authors (but not Lewis himself) also consider cases of overdetermination to be counterexamples to the necessity of counterfactual dependence for token causation. There have been many attempts to deal with the problems of preemption and overdetermination, none entirely satisfactory. We will examine the shortcomings of some of these theories in sections 11–13.

The role of contrast in causal and explanatory claims

Following Dretske (1977), there has been a considerable body of literature on the role of contrastive stress in causal claims. Following van Fraassen (1980), there has been a considerable body of literature on the role of contrastive stress in explanations and explanation-requesting why-questions. Amazingly, the two bodies of literature have remained almost entirely disjoint. With an understanding of the contrastive nature of ordinary causal claims, and of the linguistic roles of contrastive stress, it is possible to provide a unified account of both phenomena. I provide such an account from within the framework of a probabilistic theory of causation. Relations of ‘screening-off’, long familiar to researchers in probabilistic causality, play a central role in this account.

Discussion : Salmon on explanatory relevance

One of the motivations for Salmons (1984) causal theory of explanation was the explanatory irrelevance exhibited by many arguments conforming to Hempels covering-law models of explanation. However, the nexus of causal processes and interactions characterized by Salmon is not rich enough to supply the necessary conception of explanatory relevance. Salmons (1994) revised theory, which is briefly criticized on independent grounds, fares no better. There is some possibility that the two-tiered structure of explanation described by Salmon (1984) may be pressed into service, but more work would have to be done. Ironically, Salmons difficulties are similar to those suffered by his seventeenth-century predecessors.

Graded Causation and Defaults

Recent work in psychology and experimental philosophy has shown that judgments of actual causation are often influenced by consideration of defaults, typicality, and normality. A number of philosophers and computer scientists have also suggested that an appeal to such factors can help deal with problems facing existing accounts of actual causation. This article develops a flexible formal framework for incorporating defaults, typicality, and normality into an account of actual causation. The resulting account takes actual causation to be both graded and comparative. We then show how our account would handle a number of standard cases. 1 Introduction 2 Causal Models 3 The HP Definition of Actual Causation 4 The Problem of Isomorphism 5 Defaults, Typicality, and Normality 6 Extended Causal Models 7 Examples   7.1 Omissions   7.2 Knobe effects   7.3 Causes versus background conditions   7.4 Bogus prevention   7.5 Causal chains   7.6 Legal doctrines of intervening causes   7.7 Pre-emption and short circuits 8 Conclusion 1 Introduction 2 Causal Models 3 The HP Definition of Actual Causation 4 The Problem of Isomorphism 5 Defaults, Typicality, and Normality 6 Extended Causal Models 7 Examples   7.1 Omissions   7.2 Knobe effects   7.3 Causes versus background conditions   7.4 Bogus prevention   7.5 Causal chains   7.6 Legal doctrines of intervening causes   7.7 Pre-emption and short circuits   7.1 Omissions   7.2 Knobe effects   7.3 Causes versus background conditions   7.4 Bogus prevention   7.5 Causal chains   7.6 Legal doctrines of intervening causes   7.7 Pre-emption and short circuits 8 Conclusion

Of Humean Bondage

There are many ways of attaching two objects together: for example, they can be connected, linked, tied or bound together; and the connection, link, tie or bind can be made of chain, rope, or cement. Every one of these binding methods has been used as a metaphor for causation. What is the real significance of these metaphors? They express a commitment to a certain way of thinking about causation, summarized in the following thesis: ‘In any concrete situation, there is an objective fact of the matter as to whether two events are in fact bound by the causal relation. It is the aim of philosophical inquiry to analyze this objective relation.’ Through a variety of examples, I hope to cast doubt on this seemingly innocuous thesis. The problem lies not with the word ‘objective’, but with the word ‘the’. The goal of a philosophical account of causation should not be to capture the causal relation, but rather to capture the many ways in which the events of the world can be bound together. 1 The metaphors 2 Unpacking the metaphors 3 Theories of causation 4 The two assassins 5 The birth control pills 6 The smoker‐protector gene 7 The bicycle thief 8 Further examples 8.1 Indeterminism 8.2 Probability‐lowering causes 8.3 Parts vs wholes 8.4 Symmetric overdetermination 8.5 Delayers 8.6 Causation by omission 8.7 Double prevention/disconnection 8.8 Preemptive prevention 8.9 Quantitative variables 9 Conclusion

Beauty and the Bets

In the Sleeping Beauty problem, Beauty is uncertain whether the outcome of a certain coin toss was heads or tails. One argument suggests that her degree of belief in heads should be 1/3, while a second suggests that it should be 1/2. Prima facie, the argument for 1/2 appears to be stronger. I offer a diachronic Dutch Book argument in favor of 1/3. Even for those who are not routinely persuaded by diachronic Dutch Book arguments, this one has some important morals.

A Generalized Probabilistic Theory of Causal Relevance

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 Eellss (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.