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How fixed are the happenings in Nature and how are they fixed? These lectures address what our scientific successes at predicting and manipulating the world around us suggest in answer. One—very orthodox—account teaches that the sciences offer general truths that we combine with local facts to derive our expectations about what will happen, either naturally or when we build a device to design, be it a laser, a washing machine, an anti-malarial bed net, or an auction for the airwaves. In these three 2017 Carus Lectures Nancy Cartwright offers a different picture, one in which neither we, nor Nature, have such nice rules to go by. Getting real predictions about real happenings is an engineering enterprise that makes clever use of a great variety of different kinds of knowledge, with few real derivations in sight anywhere. It takes artful modeling. Orthodoxy would have it that how we do it is not reflective of how Nature does it. It is, rather, a consequence of human epistemic limitations. That, Cartwright argues, is to put our reasoning just back to front. We should read our image of what Nature is like from the way our sciences work when they work best in getting us around in it, non plump for a pre-set image of how Nature must work to derive what an ideal science, freed of human failings, would be like. Putting the order of inference right way around implies that like us, Nature too is an artful modeler. Lecture 1 is an exercise in description. It is a study of the practices of science when the sciences intersect with the world and, then, of what that world is most likely like given the successes of these practices. Millikan's famous oil drop experiment, and the range of knowledge pieced together to make it work, are used to illustrate that events in the world do not occur in patterns that can be properly described in so-called "laws of nature." Nevertheless, they yield to artful modeling. Without a huge leap of faith, that, it seems, is the most we can assume about the happenings in Nature. Lecture 2 is an exercise in metaphysics. How could the arrangements of happenings come to be that way? In answer, Cartwright urges an ontology in which powers act together in different ways depending on the arrangements they find themselves in to produce what happens. It is a metaphysics in which possibilia are real because powers and arrangement are permissive—they constrain but often do not dictate outcomes (as we see in contemporary quantum theory). Lecture 3, based on Cartwright's work on evidence-based policy and randomized controlled trials, is an exercise in the philosophy of social technology: How we can put our knowledge of powers and our skills at artful modeling to work to build more decent societies and how we can use our knowledge and skills to evaluate when our attempts are working. The lectures are important because: They offer an original view on the age-old question of scientific realism in which our knowledge is genuine, yet our scientific principles are neither true nor false but are, rather, templates for building good models. Powers are center-stage in metaphysics right now. Back-reading them from the successes of scientific practice, as Lecture 2 does, provides a new perspective on what they are and how they function. There is a loud call nowadays to make philosophy relevant to "real life." That's just what happens in Lecture 3, where Cartwright applies the lesson of Lectures 1 and 2 to argue for a serious rethink of the way that we are urged—and in some places mandated—to use evidence to predict the outcomes of our social policies.
Over the last twenty or so years, it has become standard to require policy makers to base their recommendations on evidence. That is now uncontroversial to the point of triviality--of course, policy should be based on the facts. But are the methods that policy makers rely on to gather and analyze evidence the right ones? In Evidence-Based Policy, Nancy Cartwright, an eminent scholar, and Jeremy Hardie, who has had a long and successful career in both business and the economy, explain that the dominant methods which are in use now--broadly speaking, methods that imitate standard practices in medicine like randomized control trials--do not work. They fail, Cartwright and Hardie contend, because they do not enhance our ability to predict if policies will be effective. The prevailing methods fall short not just because social science, which operates within the domain of real-world politics and deals with people, differs so much from the natural science milieu of the lab. Rather, there are principled reasons why the advice for crafting and implementing policy now on offer will lead to bad results. Current guides in use tend to rank scientific methods according to the degree of trustworthiness of the evidence they produce. That is valuable in certain respects, but such approaches offer little advice about how to think about putting such evidence to use. Evidence-Based Policy focuses on showing policymakers how to effectively use evidence, explaining what types of information are most necessary for making reliable policy, and offers lessons on how to organize that information.
It is often supposed that the spectacular successes of our modern mathematical sciences support a lofty vision of a world completely ordered by one single elegant theory. In this book Nancy Cartwright argues to the contrary. When we draw our image of the world from the way modern science works - as empiricism teaches us we should - we end up with a world where some features are precisely ordered, others are given to rough regularity and still others behave in their own diverse ways. This patchwork makes sense when we realise that laws are very special productions of nature, requiring very special arrangements for their generation. Combining classic and newly written essays on physics and economics, The Dappled World carries important philosophical consequences and offers serious lessons for both the natural and the social sciences.
Perfect for the beginning plastic modeler who wants to learn more advanced techniques, this photo-driven guide includes an introduction to airbrushing and sections on brush painting, spray painting, weathering, and applying finishes.
This 1983 book is a lively and clearly written introduction to the philosophy of natural science, organized around the central theme of scientific realism. It has two parts. 'Representing' deals with the different philosophical accounts of scientific objectivity and the reality of scientific entities. The views of Kuhn, Feyerabend, Lakatos, Putnam, van Fraassen, and others, are all considered. 'Intervening' presents the first sustained treatment of experimental science for many years and uses it to give a new direction to debates about realism. Hacking illustrates how experimentation often has a life independent of theory. He argues that although the philosophical problems of scientific realism can not be resolved when put in terms of theory alone, a sound philosophy of experiment provides compelling grounds for a realistic attitude. A great many scientific examples are described in both parts of the book, which also includes lucid expositions of recent high energy physics and a remarkable chapter on the microscope in cell biology.
This text illustrates the roles of statistical methods, coordinate transformations, and mathematical analysis in mapping complex, unpredictable dynamical systems. It describes the benefits and limitations of the available modeling tools, showing engineers and scientists how any system can be rendered simpler and more predictable. Written by a well-known authority in the field, this volume employs practical examples and analogies to make models more meaningful. The more universal methods appear in considerable detail, and advanced dynamic principles feature easy-to-understand examples. The text draws careful distinctions between mathematical abstractions and observable realities. Additional topics include the role of pure mathematics, the limitations of numerical methods, forecasting in the presence of chaos and randomness, and dynamics without calculus. Specialized techniques and case histories are coordinated with a carefully selected and annotated bibliography. The original edition was a Library of Science Main Selection in May, 1991. This new Dover edition features corrections by the author and a new Preface.
This is the most comprehensive book ever published on philosophical methodology. A team of thirty-eight of the world's leading philosophers present original essays on various aspects of how philosophy should be and is done. The first part is devoted to broad traditions and approaches to philosophical methodology (including logical empiricism, phenomenology, and ordinary language philosophy). The entries in the second part address topics in philosophical methodology, such as intuitions, conceptual analysis, and transcendental arguments. The third part of the book is devoted to essays about the interconnections between philosophy and neighbouring fields, including those of mathematics, psychology, literature and film, and neuroscience.
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 (historians, sociologists and philosophers of science). 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.
This book is an account of modeling and idealization in modern scientific practice, focusing on concrete, mathematical, and computational models. The main topics of this book are the nature of models, the practice of modeling, and the nature of the relationship between models and real-world phenomena. In order to elucidate the model/world relationship, Weisberg develops a novel account of similarity called weighted feature matching.
An innovative, multifaceted approach to scientific experiments as designed by and shaped through interaction with the modeling process The role of scientific modeling in mediation between theories and phenomena is a critical topic within the philosophy of science, touching on issues from climate modeling to synthetic models in biology, high energy particle physics, and cognitive sciences. Offering a radically new conception of the role of data in the scientific modeling process as well as a new awareness of the problematic aspects of data, this cutting-edge volume offers a multifaceted view on experiments as designed and shaped in interaction with the modeling process. Contributors address such issues as the construction of models in conjunction with scientific experimentation; the status of measurement and the function of experiment in the identification of relevant parameters; how the phenomena under study are reconceived when accounted for by a model; and the interplay between experimenting, modeling, and simulation when results do not mesh. Highlighting the mediating role of models and the model-dependence (as well as theory-dependence) of data measurement, this volume proposes a normative and conceptual innovation in scientific modeling--that the phenomena to be investigated and modeled must not be precisely identified at the start but specified during the course of the interactions arising between experimental and modeling activities. Contributors: Nancy D. Cartwright, U of California, San Diego; Anthony Chemero, U of Cincinnati; Ronald N. Giere, U of Minnesota; Jenann Ismael, U of Arizona; Tarja Knuuttila, U of South Carolina; Andrea Loettgers, U of Bern, Switzerland; Deborah Mayo, Virginia Tech; Joseph Rouse, Wesleyan U; Paul Teller, U of California, Davis; Michael Weisberg, U of Pennsylvania; Eric Winsberg, U of South Florida.