We statisticians, with our specific concern for uncertainty, are even more liable than other practical men to encounter philosophy, whether we like it or not. For my part, I like it comparatively well. That is why the honor of opening this session of discussion has come to me, though my background makes my knowledge and idiom somewhat different from your own.

A person required to risk money on a remote digit of π would, in order to comply fully with the theory [of personal probability] have to compute that digit, though this would really be wasteful if the cost of computation were more than the prize involved. For the postulates of the theory imply that you should behave in accordance with the logical implications of all that you know. Is it possible to improve the theory in this respect, making allowance within it for the cost of thinking, or would that entail paradox?

Professor Savage has been candid and generous in stating his interest in philosophy, and the philosophers who have heard him are surely grateful for this. His attitude is very far from that of some competent scientists and mathematicans who purport to clear up the questions which philosophers raise concerning their disciplines by means of a battery of technical results of varying relevance—a procedure which can often be appropriately described as “an abominable snow-job.” However, Professor Savage's generosity places a responsibility on philosophers, since the questions he raises are difficult.

This paper contributes to the mathematical foundations of the model for utility theory developed by Richard Jeffrey in The Logic of Decision [5]. In it I discuss the relationship of Jeffrey's to classical models, state and interpret an existence theorem for numerical utilities and subjective probabilities and restate a theorem on their uniqueness.

F. P. Ramsey pointed out in Theories that the observational content of a theory expressed partly in non-observational terms is retained in the sentence resulting from existentially generalizing the conjunction of all sentences of the theory with respect to all nonobservational terms. Such terms are thus avoidable in principle, but only at the cost of forming a single “monolithic” sentence. This paper suggests that communication may be thought of as occurring not only by sentence but by clause, a sentential formula closed except for a special kind of variable. Understanding such clauses requires incorporating them within the scope of one's own Ramsey sentence. Many concepts of deductive and inductive logic carry over without great change. But the concepts of truth and designation are extendible to clauses only in the sense that assertions involving them must, to be understood, in turn be construed as clauses and incorporated into the Ramsey sentence. The behavior of these extended concepts of truth and designation suggests an explication of coherence truth within a correspondence-truth framework.

In both axiomatic theories and the practice of extensive measurement, it is assumed that a series of replicas of any given object can be found. The replicas give rise to a standard series, the “multiples” of the given object. The numerical value assigned to any object is determined, approximately, by comparisons with members of a suitable standard series.

This prescription introduces unspecified errors, if the comparison process is somewhat insensitive, so that “replicas” are not really equivalent. In this paper, it is assumed that the comparison process leads only to a semiorder, which allows for such insensitivity. It is shown that, nevertheless, extensive measurement can be carried out, provided that a certain set of (plausible) axioms is valid. Approximate measures, and their limits of error, can be derived from finite sets of semiorder observations. These approximate measures converge to ratio-scale exact measurement.

It is widely agreed that ‘scientific law’ (or ‘law of nature’) is one of the key scientific terms which any adequate philosophy of science must attempt to clarify or define. The importance of the concept ‘law’ is made evident by the fact that the distinctive functions of science—explanation and prediction—are usually analyzed with reference to laws. Thus events are explained by showing that descriptions of them are deducible from laws (conjoined with suitable statements of “initial conditions”), and laws are utilized in deducing descriptions of unknown future events, thereby permitting their prediction. Moreover, it has recently become clear that the concept ‘law’ is relevant to the analysis of counterfactual conditionals, disposition terms, and the physical modalities. An adequate explication of ‘law’, then, will further the analysis of these important concepts.