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Chapter 13 discusses some laboratory experiments to measure the utility of money for individuals on the basis of their preferences between gambles where small amounts of money were at stake. The experiments were based on expected utility theory (EUT) and were conducted in the 1950s at Harvard and Stanford by three groups: statistician Frederick Mosteller and psychologist Philip Nogee (1951), philosophers Patrick Suppes and Donald Davidson with the collaboration of psychologist Sidney Siegel (1957), and Suppes and his student Karol Valpreda Walsh (1959). These scholars were confident about both EUT and the possibility of measuring utility through it. They designed their experiments so as to neutralize some psychological factors that could jeopardize the validity of EUT and spoil the significance of the experimental measurements of utility, and they concluded that their experimental findings supported both the experimental measurability of utility based on EUT and the descriptive validity of the theory.

Chapter 15 offers a conclusion to the history of measurement theory by reconstructing the origins of the representational theory of measurement in the early work of Patrick Suppes. In particular, the chapter shows that Suppes’s superseding of the unit-based understanding of measurement that he had embraced in the early 1950s, his endorsement of a liberal definition of measurement à la Stanley Smith Stevens in the mid-1950s, his conceiving of the project of an axiomatic underpinning of this notion of measurement in the late 1950s, and the realization of this project during the 1960s all have their origins in the utility analysis research he conducted from 1953 to 1957 within the Stanford Value Theory Project. The representational theory of measurement received full-fledged expression in Foundations of Measurement (1971), a book coauthored by Suppes, Duncan Luce, David Krantz, and Amos Tversky, which quickly became the dominant theory of measurement.

Using a standard counterexample to probabilistic theories of causation as an illustration, this chapter argues that there are a number of questions which one might ask about a putative causal relationship: Is it causal at all? What is the direction of the relationship? What is its strength? How does the cause compare with various alternatives? How stable is it under changes in background conditions? What are the pathways responsible for it? Many approaches in philosophy and psychology run these questions together. Together, the answers to these questions can provide a taxonomy of different kinds of causal relationships. By keeping these questions separately, we are able to clarify both philosophical applications of causation, and psychological claims about causal learning.

A new realistic account of an ontology of extensive magnitudes is developed, formulated in Seven Principles. The principles are defended by the role of magnitudes in scientific explanation and in counterfactuals. Scientific laws can be formulated using this ontology of magnitudes. A metaphysics-first view of the perception of magnitudes is then defended by using this metaphysics of magnitudes. The metaphysics-first treatment permits explanation of features of the perception of extensive magnitudes. Notions of analogue computation, analogue representation, and analogue content are explained using this apparatus. Deployment of the resulting theory allows the development, against Kuhn, of a case for the objectivity of analogue perceptual content.