James Woodward

expose some gaps and difficulties in the argument for the causal Markov condition in our essay ‘Independence, Invariance and the Causal Markov Condition’ ([1999]), and we are grateful for the opportunity to reformulate our position. In particular, Cartwright disagrees vigorously with many of the theses we advance about the connection between causation and manipulation. Although we are not persuaded by some of her criticisms, we shall confine ourselves to showing how our central argument can be reconstructed and to casting doubt on Cartwright's claim that the causal Markov condition typically fails when there are indeterministic by-products. Why believe the causal Markov condition? Causation and manipulation The argument Indeterministic by-products and the causal Markov condition The chemical factory counterexample and PM2 Conclusions: causation and manipulability.

This article defends the use of interventionist counterfactuals to elucidate causal and explanatory claims against criticisms advanced by James Bogen and Peter Machamer. Against Bogen, I argue that counterfactual claims concerning what would happen under interventions are meaningful and have determinate truth values, even in a deterministic world. I also argue, against both Machamer and Bogen, that we need to appeal to counterfactuals to capture the notions like causal relevance and causal mechanism. Contrary to what both authors suppose, counterfactuals are not "unscientific" - a substantial tradition within statistics and the causal modelling literature makes heavy use of them.

This paper explores some issues about the choice of variables for causal representation and explanation. Depending on which variables a researcher employs, many causal inference procedures and many treatments of causation will reach different conclusions about which causal relationships are present in some system of interest. The assumption of this paper is that some choices of variables are superior to other choices for the purpose of causal analysis. A number of possible criteria for variable choice are described and defended within a broadly interventionist approach to causation

This paper is an assessment of an attempt, by James Greeno, to measure the explanatory power of statistical theories by means of the notion of transmitted information (It). It is argued that It has certain features that are inappropriate in a measure of explanatory power. In particular, given a statistical theory T with explanans variables St and explanandum variables Mj, it is argued that no plausible measure of explanatory power should depend on the probability P(Si) of occurrence of initial conditions in the systems to which T applies or the magnitudes of the conditional probabilities P(Mj/Si), in the manner in which Ir does

We argue that Koch’s postulates are best understood within an interventionist account of causation, in the sense described in Woodward. We show how this treatment helps to resolve interpretive puzzles associated with Koch’s work and how it clarifies the different roles the postulates play in providing useful, yet not universal criteria for disease causation. Our paper is an effort at rational reconstruction; we attempt to show how Koch’s postulates and reasoning make sense and are normatively justified within an interventionist framework and more difficult to understand within alternative frameworks for thinking about causation.

It is noted that Popper separates the creation of concepts, conjectures, hypotheses and theories—the context of invention—from the testing thereof—the context of justification—arguing that only the latter is susceptible of rigorous logical analysis. Efforts on the part of others to shift or eradicate the demarcation established by this distinction are discussed and the relationship of these considerations to the claims of “strong artificial intelligence” is pointed out. It is argued that the mode of education of scientists, as well as reports of celebrated scientists, support Popper's judgement in this matter. An historical episode from Faraday's later career is used to illustrate the historiographical strength of Lakatos' “methodology of research programs.”

This paper explores some issues concerning the nature and structure of causal explanation in psychiatry and psychology from the point of view of the “interventionist” theory defended in my book, Making Things Happen. Among the issues is explored is the extent to which candidate causal explanations involving “upper level” or relatively coarse-grained or macroscopic variables such as mental/psychological states (e.g. highly self critical beliefs or low self esteem) or environmental factors (e.g. parental abuse) compete with explanations that instead appeal to underlying, “lower level” or more fine gained neural, genetic, or biochemical mechanisms.

My focus in this essay is on those singular causal explanations which purport to explain the occurrence of some particular event by means of a claim of the following general sort The occurrence of event caused the occurrence of event.Examples include sentences like The short circuit caused the fire’ and The impact of the hammer caused the shattering of the glass,’ Many philosophers hold that there is a sharp distinction to be drawn between singular causal explanations and those sentences which simply report causal connections. While singular causal sentences are said to typically relate events, and to be extensional, singular causal explanations are held to relate items which are sentential or fact-like in structure and to be non-extensional.1 Singular causal explanations are held on this view to always be explanations of why events or other objects belong to certain kinds or possess certain properties.

This paper explores the idea that laws express relationships between properties or universals as defended in Michael Tooley's recent book Causation: A Realist Approach. I suggest that the most plausible version of realism will take a different form than that advocated by Tooley. According to this alternative, laws are grounded in facts about the capacities and powers of particular systems, rather than facts about relations between universals. The notion of lawfulness is linked to the notion of invariance, rather than to the metaphysical notion of a necessary connection.

In this paper I criticize the commonly accepted idea that the generalizations of the special sciences should be construed as ceteris paribus laws. This idea rests on mistaken assumptions about the role of laws in explanation and their relation to causal claims. Moreover, the major proposals in the literature for the analysis of ceteris paribus laws are, on their own terms, complete failures. I sketch a more adequate alternative account of the content of causal generalizations in the special sciences which I argue should replace the ceteris paribus conception.