Models as Mediators discusses the ways in which models function in modern science, particularly in the fields of physics and economics. Models play a variety of roles in the sciences: they are used in the development, exploration and application of theories and in measurement methods. They also provide instruments for using scientific concepts and principles to intervene in the world. The editors provide a framework which covers the construction and function of scientific models, and explore the ways in which they (...) enable us to learn about both theories and the world. The contributors to the volume offer their own individual theoretical perspectives to cover a wide range of examples of modelling, from physics, economics and chemistry. These papers provide ideal case-study material for understanding both the concepts and typical elements of modelling, using analytical approaches from the philosophy and history of science. (shrink)

During the last two centuries, the way economic science is done has changed radically: it has become a social science based on mathematical models in place of words. This book describes and analyses that change - both historically and philosophically - using a series of case studies to illuminate the nature and the implications of these changes. It is not a technical book; it is written for the intelligent person who wants to understand how economics works from the inside out. (...) This book will be of interest to economists and science studies scholars. But it also aims at a wider readership in the public intellectual sphere, building on the current interest in all things economic and on the recent failure of the so-called economic model, which has shaped our beliefs and the world we live in. (shrink)

Deidealization as a topic in its own right has attracted remarkably little philosophical interest despite the extensive literature on idealization. One reason for this is the often implicit assumption that idealization and deidealization are, potentially at least, reversible processes. We question this assumption by analyzing the challenges of deidealization within a menu of four broad categories: deidealizing as recomposing, deidealizing as reformulating, deidealizing as concretizing, and deidealizing as situating. On closer inspection, models turn out much more inflexible than the reversal (...) thesis would have us believe, and deidealization emerges as a creative part of modeling. (shrink)

Facts often acquire a life of their own; the stories in this book explain why.

This paper addresses the problem of how scientific knowledge, which is always locally generated, becomes accepted in other sites. The analysis suggests that there are a small number of strategies that enable scientists to resituate knowledge and that these strategies are generic: they are not restricted to specific disciplines or modes of doing science but rather are found in a variety of different forms across the sciences.

This article explores the characteristics of research sites that scientists have called “natural experiments” to understand and develop usable distinctions for the social sciences between “Nature’s or Society’s experiments” and “natural experiments.” In this analysis, natural experiments emerge as the retro-fitting by social scientists of events that have happened in the social world into the traditional forms of field or randomized trial experiments. By contrast, “Society’s experiments” figure as events in the world that happen in circumstances that are already sufficiently (...) “controlled” to be open for direct analysis without reconstruction work. (shrink)

Critiques of case studies as an epistemic genre usually focus on the domain of justification and hinge on comparisons with statistics and laboratory experiments. In this domain, case studies can be defended by the notion of “infirming”: they use many different bits of evidence, each of which may independently “infirm” the account. Yet their efficacy may be more powerful in the domain of discovery, in which these same different bits of evi- dence must be fully integrated to create an explanatory (...) account with internal validity. (shrink)

The provocative paper by John Forrester ‘If p, Then What? Thinking in Cases’ opened up the question of case thinking as a separate mode of reasoning in the sciences. Case-based reasoning is certainly endemic across a number of sciences, but it has looked different according to where it has been found. This article investigates this mode of science – namely thinking in cases – by questioning the different interpretations of ‘If p?’ and exploring the different interpretative responses of what follows (...) in ‘Then What?’. The aim is to characterize how ‘reasoning in, within, with, and from cases’ forms a mode of scientific investigation for single cases, for runs of cases, and for comparative cases, drawing on materials from a range of different fields in which case-based reasoning appears. (shrink)

A long-standing tradition presents economic activity in terms of the flow of fluids. This metaphor lies behind a small but influential practice of hydraulic modelling in economics. Yet turning the metaphor into a three-dimensional hydraulic model of the economic system entails making numerous and detailed commitments about the analogy between hydraulics and the economy. The most famous 3-D model in economics is probably the Phillips machine, the central object of this paper.

Philosophers of science studying scientific practice often consider it a methodological requirement that their conceptualization of "model" closely connects with the understanding and use of models by practicing scientists. Occasionally, this connection has been explicitly made (Hutten 1954, Suppes 1961, Morgan and Morrison 1999, Bailer-Jones 2002, Lehtinen and Kuorikoski 2007, Kuorikoski 2007, Morgan 2012a). These studies have been dominated by a focus on the—relatively similar forms of—mathematical models in physics and economics. Yet it has become increasingly evident that the way (...) models are conceptualized is very different in some other sciences, where philosophers' accounts of models' characteristics and .. (shrink)

Modelling became one of the primary tools of mathematical economic research in the twentieth century, but when we look at examples of how nonanalogical models were first built in economics, both the process of making representations and aspects of the representing relation remain opaque. Like early astronomers, economists have to imagine how the hidden parts of their world are arranged and to make images, that is, create models, to represent how they work. The case of the Edgeworth Box, a model (...) widely used for theoretical work in twentieth-century economics, provides a good example to explore the process of making mathematical representations of the economy. It shows how, in making these new representations, conceptual elements were developed which could not have been represented in the older verbal forms of economics. (shrink)

This comment on 'Economic theories and their Dueling interpretations' questions the descriptive adequacy of the ‘sociology of economics' proposed by Gilboa, Postlewaite, Samuelson, and Schmeidler (GPSS) (2022). We ask whether economists still perceive the role of microeconomic theory as central as do GPSS. In particular, is present-day economics unified by the principles of maximising, subject to constraints and equilibrium analysis? We argue that this is not the case. GPSS’ appeal to the interpretative flexibility of economic theories appears apologetic, especially the (...) suggestion that theories and models, which once were considered positive descriptions or predictive instruments, are now cast as analytical or methodological exercises. We conclude on a more constructive note, drawing from the recent philosophical discussion of modelling which, quite paradoxically, grants highly idealized and simplified models a more important role than GPSS appear to allow. (shrink)

I PSYCHOLOGY 5 The Probabilistic Revolution in Psychology--an Overview Gerd Gigerenzer 7 1 Probabilistic Thinking and the Fight against Subjectivity Gerd Gigerenzer 11 2 Statistical Method and the Historical Development of Research Practice in American Psychology Kurt Danziger 35 3 Survival of the Fittest Probabilist: Brunswik, Thurstone, and the Two Disciplines of Psychology Gerd Gigerenzer 49 4 A Perspective for Viewing the Integration of Probability Theory in Psychology David J. Murray 73 II SOCIOLOGY 101 5 The Two Empirical Roots of (...) Social Theory and the Probability Revolution Anthony Oberschall 103 III ECONOMICS 133 The Probabilistic Revolution in Economics--an Overview Mary S. Morgan 135 6 Why Was There No Probabilistic Revolution in Economic Thought? Claude Mènard 139 7 The Rise of Macroeconomic Calculations in Economic Statistics Robert A. Horváth 147 8 Statistics without Probability and Haavelmo’s Revolution in Econometrics Mary S. Morgan 171 IV PHYSIOLOGY 199 9 Experimental Physiology and Statistical Inference: The Therapeutic Trial in Nineteenth-Century Germany William Coleman 201 V EVOLUTIONARY BIOLOGY 227 The Probabilistic Revolution in Evolutionary Biology--an Overview John H. Beatty 229 10 Natural Selection as a Causal, Empirical, and Probabilistic Theory M. J. S. Hodge 233 11 Dobzhansky and Drift: Facts, Values, and Chance in Evolutionary Biology John H. Beatty 271 12 Random Genetic Drift, R. A. Fisher, and the Oxford School of Ecological Genetics John R. G. Turner 313 13 On the Prior Probability of the Existence of Life Bernd-Olaf Küppers 355 VI PHYSICS 371 The Probabilistic Revolution in Physics--an Overview Lorenz Krüger 373 14 Probabilistic Physics the Classical Way Jan von Plato 379 15 Max Born and the Reality of Quantum Probabilities Nancy Cartwright 409 16 Philosophical Problems of Quantum Theory: The Response of American Physicists Nancy Cartwright. (shrink)

Mary Hesse's well-known work on models and analogies gives models a creative role to play in science, which rests on developing certain analogical properties considered neutral between the two fields. Case study material from Irving Fisher's work (The Purchasing Power of Money, 1911), in which he used analogies to construct models of monetary relations and the monetary system, highlights certain omissions in Hesse's account. The analysis points to the importance of taking account of the negative properties in the analogies and (...) to certain differences between "ready-made" analogies (models of systems based on existing analogical structures) and "designed" analogies (models built up from separate analogical features). (shrink)

Graeme Earl's paper on computer graphic modeling in archaeology raises many themes of interest for the philosopher of science, although, as is to be expected of complex social and technical disciplinary practices, these philosophical issues are not to be easily separated or neatly labeled. On the one hand, the modeling practices and concerns of the archaeologists dispute (or even disrupt) the philosophers' traditional notions, while the formers' reective commentaries offer sophisticated analyses that go beyond the latters' traditional reflections on models. (...) On the other hand, the paper raises new questions about how human and social scientists—as humans with social lives—engage with models in their different .. (shrink)

Narrative Science examines the use of narrative in scientific research over the last two centuries. It brings together an international group of scholars who have engaged in intense collaboration to find and develop crucial cases of narrative in science. Motivated and coordinated by the Narrative Science project, funded by the European Research Council, this volume offers integrated and insightful essays examining cases that run the gamut from geology to psychology, chemistry, physics, botany, mathematics, epidemiology, and biological engineering. Taking in shipwrecks, (...) human evolution, military intelligence, and mass extinctions, this landmark study revises our understanding of what science is, and the roles of narrative in scientists' work. This title is also available as Open Access. (shrink)

Over the last 40 years or so, economics has become a modelling science: a science in which models have become one of the main epistemological tools both for theoretical and applied work. But providing an account of how models work and what they do for the economist is not easy. For the philosopher of economics like me, struggling with this question, John Sutton's views on the nature and design of economic models and how they work is indeed thought provoking. Because (...) of my own interests, my review of Sutton's book: Marshall's Tendencies: What Can Economists Know? will focus on three related issues that I found especially intriguing in his treatment of the role of models in modern economics. The first is the way that Sutton's account fits with my own reading of the history of twentieth-century economics, namely that the focus of economic explanation has moved during the last century from and to and . The second is to understand the epistemological connotations of Sutton's view. The third is to explore what Sutton means when he says a model . These three questions roughly coincide with the material presented in Chapters 1, 3 and 2 respectively of the book. As we shall see, Sutton gives us a practitioner account of applied economics which can fit within the standard terms used by philosophers of economics on theory-testing, but which reveals a number of novel elements for philosophical analysis. (shrink)