Many standard philosophical accounts of scientific practice fail to distinguish between modeling and other types of theory construction. This failure is unfortunate because there are important contrasts among the goals, procedures, and representations employed by modelers and other kinds of theorists. We can see some of these differences intuitively when we reflect on the methods of theorists such as Vito Volterra and Linus Pauling on the one hand, and Charles Darwin and Dimitri Mendeleev on the other. Much of Volterra's and (...) Pauling's work involved modeling; much of Darwin's and Mendeleev's did not. In order to capture this distinction, I consider two examples of theory construction in detail: Volterra's treatment of post-WWI fishery dynamics and Mendeleev's construction of the periodic system. I argue that modeling can be distinguished from other forms of theorizing by the procedures modelers use to represent and to study real-world phenomena: indirect representation and analysis. This differentiation between modelers and non-modelers is one component of the larger project of understanding the practice of modeling, its distinctive features, and the strategies of abstraction and idealization it employs. (shrink)

An early, very preliminary edition of this book was circulated in 1962 under the title Set-theoretical Structures in Science. There are many reasons for maintaining that such structures play a role in the philosophy of science. Perhaps the best is that they provide the right setting for investigating problems of representation and invariance in any systematic part of science, past or present. Examples are easy to cite. Sophisticated analysis of the nature of representation in perception is to be found already (...) in Plato and Aristotle. One of the great intellectual triumphs of the nineteenth century was the mechanical explanation of such familiar concepts as temperature and pressure by their representation in terms of the motion of particles. A more disturbing change of viewpoint was the realization at the beginning of the twentieth century that the separate invariant properties of space and time must be replaced by the space-time invariants of Einstein's special relativity. Another example, the focus of the longest chapter in this book, is controversy extending over several centuries on the proper representation of probability. The six major positions on this question are critically examined. Topics covered in other chapters include an unusually detailed treatment of theoretical and experimental work on visual space, the two senses of invariance represented by weak and strong reversibility of causal processes, and the representation of hidden variables in quantum mechanics. The final chapter concentrates on different kinds of representations of language, concluding with some empirical results on brain-wave representations of words and sentences. (shrink)

Philosophers of science increasingly recognize the importance of idealization: the intentional introduction of distortion into scientific theories. Yet this recognition has not yielded consensus about the nature of idealization. e literature of the past thirty years contains disparate characterizations and justifications, but little evidence of convergence towards a common position.

Throughout, this book questions our accepted definitions and biases, showing the self-reflective nature of scientific activity within society.

It is argued that rather than a well defined F-Twist, Milton Friedman’s “Methodology of positive economics” offers an F-Mix: a pool of ambiguous and inconsistent ingredients that can be used for putting together a number of different methodological positions. This concerns issues such as the very concept of being unrealistic, the goal of predictive tests, the as-if formulation of theories, explanatory unification, social construction, and more. Both friends and foes of Friedman’s essay have ignored its open-ended unclarities. Their removal may (...) help create new common ground for more focused debate in economics. Here I show how F53 can be reread/rewritten as a socially constructivist fallibilist, and realist statement – in contrast to the received instrumentalist interpretation. (shrink)

In this essay, I argue for four related claims. First, Richard Levins’ classic “The Strategy of Model Building in Population Biology” was a statement and defense of theoretical population biology growing out of collaborations between Robert MacArthur, Richard Lewontin, E. O. Wilson, and others. Second, I argue that the essay served as a response to the rise of systems ecology especially as pioneered by Kenneth Watt. Third, the arguments offered by Levins against systems ecology and in favor of his own (...) methodological program are best construed as “pragmatic”. Fourth, I consider limitations of Levins’ arguments given contemporary population biology. (shrink)

In this article, the author offers a discussion of the evidential role of the Galilean constant in the history of physics. The author argues that measurable constants help theories constrain data. Theories are engines for research, and this helps explain why the Duhem-Quine thesis does not undermine scientific practice. The author connects his argument to discussion of two famous papers in the history of economic methodology, Milton Friedman's 'Methodology of Positive Economics', which appealed to example of Galilean Law of Fall (...) in its argument; and Vernon Smith's 'Economics in the Laboratory'. While the author offers some criticism of Friedman and Smith, most of the article is a friendly reinterpretation of their insights. (shrink)

This paper is an interpretation and defense of Richard Levins’ “The Strategy of Model Building in Population Biology,” which has been extremely influential among biologists since its publication 40 years ago. In this article, Levins confronted some of the deepest philosophical issues surrounding modeling and theory construction. By way of interpretation, I discuss each of Levins’ major philosophical themes: the problem of complexity, the brute-force approach, the existence and consequence of tradeoffs, and robustness analysis. I argue that Levins’ article is (...) concerned, at its core, with justifying the use of multiple, idealized models in population biology. (shrink)

In this article, the author offers a discussion of the evidential role of the Galilean constant in the history of physics. The author argues that measurable constants help theories constrain data. Theories are engines for research, and this helps explain why the Duhem-Quine thesis does not undermine scientific practice. The author connects his argument to discussion of two famous papers in the history of economic methodology, Milton Friedman’s “Methodology of Positive Economics,” which appealed to example of Galilean Law of Fall (...) in its argument; and Vernon Smith’s “Economics in the Laboratory.” While the author offers some criticism of Friedman and Smith, most of the article is a friendly reinterpretation of their insights. (shrink)