James Woodward

Over the past several years Haisch, Rueda, and others have made the claim that the origin of inertial reaction forces can be explained as the interaction of electrically charged elementary particles with the vacuum electromagnetic zero-point field expected on the basis of quantum field theory. After pointing out that this claim, in light of the fact that the inertial masses of the hadrons reside in the electrically chargeless, photon-like gluons that bind their constituent quarks, is untenable, the question of the role of quantum zero-point fields generally in the origin of inertia is explored. It is shown that, although non-gravitational zero-point fields might be the cause of the gravitational properties of normal matter, the action of non-gravitational zero-point fields cannot be the cause of inertial reaction forces. The gravitational origin of inertial reaction forces is then briefly revisited. Recent claims critical of the gravitational origin of inertial reaction forces by Haisch and his collaborators are then shown to be without merit

The explanation of inertia based on “Mach's principle” is briefly revisited and an experiment whereby the gravitational origin of inertia can be tested is described. The test consists of detecting a small stationary force with a sensitive force sensor. The force is presumably induced when a periodic transient Mach effect mass fluctuation is driven in high voltage, high energy density capacitors that are subjected to 50 kHz, 1.3 kV amplitude voltage signal, and threaded by an alternating magnetic flux of the same frequency. An effect of the sort predicted is shown to be present in the device tested. It has the expected magnitude and depends on the relative phase of the Mach effect mass fluctuation and the alternating magnetic flux as expected. The observed effect also displays scaling behaviors that are unique to Mach effects. Other tests for spurious signals suggest that the observed effect is real

The question of the cause of inertial reaction forces and the validity of “Mach's principle” are investigated. A recent claim that the cause of inertial reaction forces can be attributed to an interaction of the electrical charge of elementary particles with the hypothetical quantum mechanical “zero-point” fluctuation electromagnetic field is shown to be untenable. It fails to correspond to reality because the coupling of electric charge to the electromagnetic field cannot be made to mimic plausibly the universal coupling of gravity and inertia to the stress-energy-momentum (i.e., matter) tensor. The gravitational explanation of the origin of inertial forces is then briefly laid out, and various important features of it explored in the last half-century are addressed

Counterfactual theories of causation of the sort presented in Mackie, 1974, and Lewis, 1973 are a familiar part of the philosophical landscape. Such theories are typically advanced primarily as accounts of the metaphysics of causation. But they also raise empirical psychological issues concerning the processes and representations that underlie human causal reasoning. For example, do human subjects internally represent causal claims in terms of counterfactual judgments and when they engage in causal reasoning, does this involves reasoning about counterfactual claims? This paper explores several such issues from a broadly interventionist perspective

'IRS' is our term for the logical empiricist idea that the best way to understand the epistemic bearing of observational evidence on scientific theories is to model it in terms of Inferential Relations among Sentences representing the evidence, and sentences representing hypotheses the evidence is used to evaluate. Developing ideas from our earlier work, including 'Saving the Phenomena'(Phil Review 97, 1988, p.303-52 )we argue that the bearing of observational evidence on theory depends upon causal connections and error characteristics of the processes by which data is produced and used to detect features of phenomena. Neither of these depends upon, or is greatly illuminated by a consideration of, formal relations among observation and theoretical sentences or propositions. By taking causal structures and error characteristics, you too can evade the IRS. In doing so, you can gain insight into Hempel’s raven paradox, theory loading, and other issues from the standard philosophical literature on confirmation theory.

This paper makes use of recent empirical results, mainly from experimental economics, to expore the conditions under which people will cooperate and to assess competing explantions of this cooperation. It is argued that the evidence supports the claim that people differ in type, with some being conditional cooperators and others being motivated by more or less sophisticated forms of self-interest. Stable cooperation requires, among other things, rules and institutions that protect conditional cooperators from myopically self-interested types. Additional empirical features of the behavior of conditional cooperators also imply that rules and institutions are required to produce stable cooperation.

This paper develops an account of explanation in biology which does not involve appeal to laws of nature, at least as traditionally conceived. Explanatory generalizations in biology must satisfy a requirement that I call invariance, but need not satisfy most of the other standard criteria for lawfulness. Once this point is recognized, there is little motivation for regarding such generalizations as laws of nature. Some of the differences between invariance and the related notions of stability and resiliency, due respectively to Sandra Mitchell and Brian Skyrms, are explored.

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.

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.

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.

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 describes an alternative to the common view that explanation in the special sciences involves subsumption under laws. According to this alternative, whether or not a generalization can be used to explain has to do with whether it is invariant rather than with whether it is lawful. A generalization is invariant if it is stable or robust in the sense that it would continue to hold under a relevant if it is stable or robust in the sense that it would continue to hold under a relevant class of changes. Unlike lawfulness, invariance comes in degrees and has other features that are well suited to capture the characteristics of explanatory generalizations in the special sciences. For example, a generalization can be invariant even if it has exceptions or holds only over a limited spatio-temporal interval. The notion of invariance can be used to resolve a number of dilemmas that arise in standard treatments of explanatory generalizations in the special sciences.