William L. Harper

Newton's methodology emphasized propositions "inferred from phenomena." These rest on systematic dependencies that make phenomena measure theoretical parameters. We consider the inferences supporting Newton's inductive argument that gravitation is proportional to inertial mass. We argue that the support provided by these systematic dependencies is much stronger than that provided by bootstrap confirmation; this kind of support thus avoids some of the major objections against bootstrapping. Finally we examine how contemporary testing of equivalence principles exemplifies this Newtonian methodological theme

The Akaike Information Criterion can be a valuable tool of scientific inference. This statistic, or any other statistical method for that matter, cannot, however, be the whole of scientific methodology. In this paper some of the limitations of Akaikean statistical methods are discussed. It is argued that the full import of empirical evidence is realized only by adopting a richer ideal of empirical success than predictive accuracy, and that the ability of a theory to turn phenomena into accurate, agreeing measurements of causally relevant parameters contributes to the evidential support of the theory. This is illustrated by Newton's argument from orbital phenomena to the inverse-square law of gravitation.

Newton's methodology is significantly richer than the hypothetico-deductive model. It is informed by a richer ideal of empirical success that requires not just accurate prediction but also accurate measurement of parameters by the predicted phenomena. It accepts theory-mediated measurements and theoretical propositions as guides to research. All of these enrichments are exemplified in the classical response to Mercury's perihelion problem. Contrary to Kuhn, Newton's method endorses the radical transition from his theory to Einstein's. The richer themes of Newton's method are strikingly realized in a challenge to general relativity from a new problem posed by Mercury's perihelion. †To contact the author, please write to: Talbot College, University of Western Ontario, London, Ontario, Canada N6A 3K7; e-mail: [email protected].

We argue that causal decision theory is no worse off than evidential decision theory in handling entanglement, regardless of one’s preferred interpretation of quantum mechanics. In recent works, Ahmed and Ahmed and Caulton : 4315–4352, 2014) have claimed the opposite; we argue that they are mistaken. Bell-type experiments are not instances of Newcomb problems, so CDT and EDT do not diverge in their recommendations. We highlight the fact that a Causal Decision Theorist should take all lawlike correlations into account, including potentially acausal entanglement correlations. This paper also provides a brief introduction to CDT with a motivating “small” Newcomb problem. The main point of our argument is that quantum theory does not provide grounds for favouring EDT over CDT.

As van Fraassen pointed out in his opening remarks, Henry Kyburg's lottery paradox has long been known to raise difficulties in attempts to represent full belief as a probability greater than or equal to p, where p is some number less than 1. Recently, Patrick Maher has pointed out that to identify full belief with probability equal to 1 presents similar difficulties. In his paper, van Fraassen investigates ways of representing full belief by personal probability which avoid the difficulties raised by Maher's measure-theoretic version of the lottery paradox. Van Fraassen's more subtle representation dissolves the simple identification of full belief with maximal personal probability. His investigation exploits the richer resources for representing opinion provided by taking conditional, rather than unconditional, personal probability as fundamental. It has interesting implications for equivalent alternative approaches based on non-Archimedean probability, as well as for equivalent approaches in which assumption contexts representing full belief relative to suppositions are taken as fundamental.

This paper explores how the Bayesian program benefits from allowing for objective chance as well as subjective degree of belief. It applies David Lewis’s Principal Principle and David Christensen’s principle of informed preference to defend Howard Raiffa’s appeal to preferences between reference lotteries and scaling lotteries to represent degrees of belief. It goes on to outline the role of objective lotteries in an application of rationality axioms equivalent to the existence of a utility assignment to represent preferences in Savage’s famous omelet example of a rational choice problem. An example motivating causal decision theory illustrates the need for representing subjunctive dependencies to do justice to intuitive examples where epistemic and causal independence come apart. We argue to extend Lewis’s account of chance as a guide to epistemic probability to include De Finetti’s convergence results. We explore Diachronic Dutch book arguments as illustrating commitments for treating transitions as learning experiences. Finally, we explore implications for Martingale convergence results for motivating commitment to objective chances

I attempt to persuade the reader that externalism admits of no plausible interpretation. I argue that reliability is a concept with very different contours from epistemic justification, and that attempts to explicate justification in terms of reliability must fail. I address several other forms of externalism, and also mixed forms of justification. I then argue that externalist theories of justification cannot close the gap between mere true belief and knowledge. I suggest that a fourth condition on knowledge is required, regardless of whether justification is internalist or externalist. I argue that with such a fourth condition a strong internalist theory of justification is adequate to the task that remains in making true belief knowledge. Additionally, strong internalism is more satisfying to our intuitions than externalism and mixed forms of justification.

This is a very important book. It has already become required reading for researchers on the relation between the exact sciences and Kant’s philosophy. The main theme is that Kant’s continuing program to find a metaphysics that could provide a foundation for the science of his day is of crucial importance to understanding the development of his philosophical thought from its earliest precritical beginnings in the thesis of 1747, right through the highwater years of the critical philosophy, to his last unpublished writings in the Opus postumum. In the course of articulating this theme, Friedman has made extensive use of detailed historical information about their scientific and mathematical background to illuminate Kant’s texts. Over and over again, such information is used to suggest interesting and quite subtle interpretations for texts that may have seemed puzzling or just wrong-headed.

Consider your right hand and a mirror image duplicate of it. Kant calls such pairs incongruent counterparts. According to him they have the following puzzling features. The relation and situation of the parts of your hand with respect to one another are not sufficient to distinguish it from its mirror duplicate. Nevertheless, there is a spatial difference between the two. Turn and twist them how you will, you cannot make one of them occupy the exact boundaries now occupied by the other. In his 1768 paper, ‘Concerning the Ultimate Foundations of the Differentiation of Regions in Space’, Kant uses these claims to argue against relational accounts of space and goes on to argue that the difference between incongruent counterparts depends on a relation to absolute space as a whole. In his 1770 Inaugural Dissertation he argued that this difference could not be captured by concepts alone but required appeal to intuition. In the Prolegomena (1783) and again in the Metaphysical Foundations of Natural Science (1786) Kant appealed to these puzzling features of incongruent counterparts to support his transcendental idealism about space.

The Akaike Information Criterion can be a valuable tool of scientific inference. This statistic, or any other statistical method for that matter, cannot, however, be the whole of scientific methodology. In this paper some of the limitations of Akaikean statistical methods are discussed. It is argued that the full import of empirical evidence is realized only by adopting a richer ideal of empirical success than predictive accuracy, and that the ability of a theory to turn phenomena into accurate, agreeing measurements of causally relevant parameters contributes to the evidential support of the theory. This is illustrated by Newton's argument from orbital phenomena to the inverse-square law of gravitation.