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 article discusses the role of simplicity and the notion of a best balance of simplicity and strength within the best systems account (BSA) of laws of nature. The article explores whether there is anything in scientific practice that corresponds to the notion of simplicity or to the trade-off between simplicity and strength to which the BSA appeals. Various theoretical rationales for simplicity preferences and their bearing on the identification of laws are also explored. It is concluded that there are a number of issues about the role of simplicity within the BSA and its relation to strength that need to be addressed before the BSA can be regarded as an adequate account of laws. 1 Introduction2 The Best Systems Account3 The Trade-Off between Simplicity and Strength: Preliminary Considerations4 Alternative Conceptions of the Relationship between Simplicity and Strength5 Two Roles for Simplicity6 Simplicity in the Best Systems Account: Curve-Fitting7 Simplicity as a Corrective for Overfitting8 Descriptive Simplicity in the Best Systems Account?9 Simplicity as Due to Human Intellectual Limitations10 Summary11 Concluding Remarks

This paper examines a recent attempt by Evan Jobe to account for the asymmetric character of many scientific explanations. It is argued that a purported counterexample to Jobe's account, from Clark Glymour, is inconclusive, but that the account faces independent objections. It is also suggested, contrary to Jobe, that the explanatory relation is not always asymmetric. Sometimes a singular sentence C can figure in a DN derivation of another singular sentence E and E can also figure in a DN derivation of C. Yet while we are inclined to regard the first derivation as an explanation of E, we are not inclined to regard the second derivation as an explanation of C. As Sylvain Bromberger pointed out in a now classic article (1966), one can explain the period of a pendulum by reference to its length and yet, although one can give a DN derivation of the length of a pendulum by reference to its period, this derivation does not seem to represent an explanation. Evan Jobe has recently offered an interesting account of such explanatory asymmetries and Clark Glymour has in turn proposed a counterexample which seems to show that Jobe's account is defective. The aim of this paper is two-fold. I shall attempt to show that (a) Glymour's proposed counterexample can be rejected on the grounds that it violates an independently plausible restriction on the role that equalities may play in DN explanation, and that (b) although Glymour's counterexample can be avoided in this way, Jobe's account is defective in several other respects

This paper attempts to elucidate three characteristics of causal relationships that are important in biological contexts. Stability has to do with whether a causal relationship continues to hold under changes in background conditions. Proportionality has to do with whether changes in the state of the cause “line up” in the right way with changes in the state of the effect and with whether the cause and effect are characterized in a way that contains irrelevant detail. Specificity is connected both to David Lewis’ notion of “influence” and also with the extent to which a causal relation approximates to the ideal of one cause–one effect. Interrelations among these notions and their possible biological significance are also discussed.

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

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 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