Kevin Davey claims that the justification of the second law of thermodynamics as it is conveyed by the “standard story” of statistical mechanics, roughly speaking, that low-entropy microstates tend to evolve to high-entropy microstates, is “unhelpful at best and wrong at worst.” In reply, I demonstrate that Davey’s argument for rejecting the standard story commits him to a form of skepticism that is more radical than the position he claims to be stating and that Davey places unreasonable demands on the notion of justification in the physical sciences.

We describe a simple, flexible exercise that can be implemented in the philosophy of science classroom: students are asked to determine the contents of a closed container without opening it. This exercise has revealed itself as a useful platform from which to examine a wide range of issues in the philosophy of science and may, we suggest, even help us think about improving the public understanding of science.

Realism about progress–that progress consists in the obtaining of some metaphysical relation between a sequence of theories and the world–is often thought to be required by realism about the representational character of theories. The purpose of this paper is to show how one can be a realist about theories without being a realist about progress. The result is a view that cannot be at odds with what the history of science shows.

A large number of definitions of the concept “model” have been given by various authors in recent years. Thirty-seven definitions are listed by A. I. Uyemov in a recent monograph (see [9]). This list is somewhat one-sided since it contains a disproportionate number of references to the work of Soviet authors. However, most of the important definitions given by Western writers are included. I shall give three definitions, all of great generality, so that various types of models, replicas, maps, theories and, most importantly, cybernetic models, are included. The advantage of this high degree of generality, or all-inclusiveness, is that the task of the investigator of uses of models in science, is reduced to classifying the various types of models, their construction, function, and structure, thus avoiding indecisive arguments (historically important, of course) such as the Duhem–Campbell controversy, so perceptively discussed by Mary Hesse ([2], [3]).

What is operations research? What is sufficiently new about it to constitute it a “new science”? And how is it related to philosophy?

1. What it is. MOR's definition, based on Kittel's, runs as follows:

Operations research is a scientific method of providing executive departments with a quantitative basis for decisions regarding the operations under their control (7: 1.)

The nature of the connection between theory and observation has been a major source of difficulty for philosophers of science. It is most vexing for those who would reduce the terms of a theory to those of an observation language, e.g. Carnap, Braithwaite, and Nagel. Carnap's work, particularly his treatment of physical theories as partially interpreted formalisms, forms the point of focus of this paper. Carnap attempted to make the connection between theory and observation through correspondence postulates. It is pointed out that such postulates depend in critical ways upon theoretical truths. This particular type of theoretical dependence produces serious trouble for Carnap's approach. For reasons given it may make it untenable. Furthermore, this problem when generalized creates difficulty for any similar reductionist program. Not only is this kind of theoretical dependence pointed out, but more important, the logical conditions which produce it are revealed. In this way light is shed upon the formal characteristics of the notion of theory dependence, especially upon the way in which observation terms depend upon theories for their meaning.

Professor Everett W. Hall's new book, Modern Science and Human Values, one of the most important to have appeared in the field of Value Theory in the last ten years, shares in rich measure the common characteristic of so many other “prolegomena” to the future discipline of values: it is almost maddeningly frustrating. It sees with crystal clearness the essence of the scientific method and describes it in brilliant detail, from Galileo to Einstein; but it fails to draw a positive moral for value theory. On the contrary, its thesis is thoroughly negative: although value must be known as thoroughly as fact if the world is to survive, the scientific method that has brought us knowledge of fact can never bring us knowledge of value. For fact and value are fundamentally different, fact is known by science in a way that excludes value, and hence, whatever may be the way by which value is to be known, it cannot be science. It is true, science has given the most powerful and incisive formulation to fact while value theory has done nothing of the sort for value. Value theory, therefore, must be brought up to the level of science, otherwise there is danger that we may perish under the impact of science. But how to bring this about, how to construct a value theory as powerful and as representative of value as science is of fact, that is the question which the book can only ask but not answer.

In the preceding article, [3], Peter Machamer states three objections to my recent attempt to define ‘observation term’. While I believe that all Machamer's objections are mistaken, as I will try to show, his discussion does touch on two problems which have forced revisions. Both his first and second objections are that my definition is too restrictive because its second necessary condition for a term ‘O‘ being an observation term rules out too many terms which are obviously observation terms. The condition is :