An examination of how scientists deliberately and justifiably use pervasive distortions of relevant features to explain and understand natural phenomena. A fundamental rule of logic is that in order for an argument to provide good reasons for its conclusion, the premises of the argument must be true. In this book, Collin Rice shows how the practice of science repeatedly, pervasively, and deliberately violates this principle. Rice argues that scientists strategically use distortions that misrepresent relevant features of natural phenomena in order to explain and understand--and that they use these distortions deliberately and justifiably in order to discover truths that would be otherwise inaccessible. Countering the standard emphasis on causation, accurate representation, and decomposition of science into its accurate and inaccurate parts, Rice shows that science's epistemic achievements can still be factive despite their being produced through the use of holistically distorted scientific representations. Indeed, he argues, this distortion is one of the most widely employed and fruitful tools used in scientific theorizing. Marshalling a range of case studies, Rice contends that many explanations in science are noncausal, and he presents an alternate view of explanation that captures the variety of noncausal explanations found across the sciences. He proposes an alternative holistic distortion view of idealized models, connecting it to physicists' concept of a universality class; shows how universality classes can overcome some of the challenges of multiscale modeling; and offers accounts of explanation, idealization, modeling, and understanding.

"What does it mean to be a realist about science if one takes seriously the view that scientific knowledge is always perspectival, namely historically and culturally situated? In this book, Michela Massimi articulates an original answer to this question. The book begins with an exploration of how scientific communities often resort to several models and a plurality of practices in some areas of inquiry, drawing on examples from nuclear physics, climate science, and developmental psychology. Taking this plurality in science as a starting point, Massimi explains the perspectival nature of scientific representation, the role of scientific models as inferential blueprints, and the variety of scientific realism that naturally accompanies such a view. Perspectival realism is realism about phenomena (rather than about theories or unobservable entities). The book defends this novel realist view, which places epistemic communities and their situated knowledge center stage. The result is a portrait of scientific knowledge as a collaborative inquiry, where the reliability of science is made possible by a plurality of historically and culturally situated scientific perspectives. Along the way, Massimi offers insights into the nature of scientific modelling, scientific knowledge qua modal knowledge, data-to-phenomena inferences, and natural kinds as sortal concepts. Perspectival realism is ultimately realism that takes the multicultural nature of science seriously and couples it with cosmopolitan duties about how one ought to think about scientific knowledge and the distribution of the benefits resulting from scientific advancements"--

Models and theories are of central importance in science, and scientists spend substantial amounts of time building, testing, comparing and revising models and theories. It is therefore not surprising that the nature of scientific models and theories has been a widely debated topic within the philosophy of science for many years. The product of two decades of research, this book provides an accessible yet critical introduction to the debates about models and theories within analytical philosophy of science since the 1920s. Roman Frigg surveys and discusses key topics and questions, including: What are theories? What are models? And how do models and theories relate to each other? The linguistic view of theories (also known as the syntactic view of theories), covering different articulations of the view, its use of models, the theory-observation divide and the theory-ladenness of observation, and the meaning of theoretical terms. The model-theoretical view of theories (also known as the semantic view of theories), covering its analysis of the model-world relationship, the internal structure of a theory, and the ontology of models. Scientific representation, discussing analogy, idealisation and different accounts of representation. Modelling in scientific practice, examining how models relate to theories and what models are, classifying different kinds of models, and investigating how robustness analysis, perspectivism, and approaches committed to uncertainty-management deal with multi-model situations. Models and Theories is the first comprehensive book-length treatment of the topic, making it essential reading for advanced undergraduates, researchers, and professional philosophers working in philosophy of science and philosophy of technology. It will also be of interest to philosophically minded readers working in physics, computer sciences and STEM fields more broadly.

This volume assembles cutting-edge scholarship on scientific understanding, scientific representation, and their delicate interplay. Featuring several articles in an engaging ‘critical conversation’ format, the volume integrates discussions about understanding and representation with perennial issues in the philosophy of science, including the nature of scientific knowledge, idealizations, scientific realism, scientific inference, and scientific progress. In the philosophy of science, questions of scientific understanding and scientific representation have only recently been put in dialogue with each other. The chapters advance these discussions from a variety of fresh perspectives. They range from case studies in physics, chemistry, and neuroscience to the representational challenges of machine learning models; from special forms of representation such as maps and topological models to the relation between understanding and explanation; and from the role of idealized representations to the role of representation and understanding in scientific progress. Scientific Understanding and Representation will appeal to scholars and advanced students working in philosophy of science, philosophy of physics, philosophy of mathematics, and epistemology.

This book illustrates the dramatic recent transformations in capital markets worldwide. Market making by humans in centralized markets has been replaced by super computers and algorithms in often highly fragmented markets. This book discusses how this impacts public policy objectives and how market governance could be strengthened.

Through a collection of works from key thinkers in natural philosophy, the second edition of The Scientific Background to Modern Philosophy illuminates the central role scientific writing played in developing modern philosophical thought. This revised and expanded edition includes many new translations and incorporates works by foundational eighteenth- and nineteenth-century thinkers not in the first edition, including selections from works by Jean-Baptiste, le Rond d’Alembert, Denis Diderot, Émilie Du Châtelet, Jean-Jacques Rousseau, Joseph Priestley, Immanuel Kant, Carl Linnaeus, William Paley, and Charles Robert Darwin. These new additions provide students with a more comprehensive understanding of the scientific context in which the major philosophical works of the modern era were written and complement the selections from works by Nicolaus Copernicus, Francis Bacon, Galileo Galilei, René Descartes, Robert Boyle, Christiaan Huygens, and Isaac Newton that are retained from the first edition.

The Pragmatist Challenge lays out a programmatic view for taking a pragmatist approach to topics in philosophy of science and metaphysics. Pragmatism involves a collection of specific views as well as comprising a general approach that can be applied to multiple topics. For topics at the intersection of philosophy of science and metaphysics, pragmatism as explored in this volume is an effective way to take entrenched debates and re-frame them in ways that move past old dichotomies and offer more fruitful paths forward. Each chapter explores a dual vision of pragmatism: specific pragmatist views are developed, demonstrating how to take a distinctively pragmatist approach to some particular issue or subfield; and the general shape of what it means to take a pragmatist approach is elucidated as well. The chapters thus tend to be synoptic in scope. Collectively, they offer a new approach that can be taken up in constructively reframing other discussions, ready to be applied to new specific topics. Pragmatism is an especially potent tool that sits at the interface between methodological and applied questions coming directly from sciences, and the underlying ontological or metaphysical commitments that are implied by or support the methodological discussions. The goal of the volume is to articulate a variety of ways to be a pragmatist without having to commit to a single specific set of -isms in order to make use of it, while highlighting the common themes that manifest across different discussions. The chapters offer a heterogenous yet programmatic approach to pragmatism.

Vol. 3 also issed as rev. 3rd ed. ; rev. 3rd edition of other vols. not planned.

How biases, the desire for a good narrative, reliance on citation metrics, and other problems undermine confidence in modern science. Modern science is built on experimental evidence, yet scientists are often very selective in deciding what evidence to use and tend to disagree about how to interpret it. In The Matter of Facts, Gareth and Rhodri Leng explore how scientists produce and use evidence. They do so to contextualize an array of problems confronting modern science that have raised concerns about its reliability: the widespread use of inappropriate statistical tests, a shortage of replication studies, and a bias in both publishing and citing “positive” results. Before these problems can be addressed meaningfully, the authors argue, we must understand what makes science work and what leads it astray. The myth of science is that scientists constantly challenge their own thinking. But in reality, all scientists are in the business of persuading other scientists of the importance of their own ideas, and they do so by combining reason with rhetoric. Often, they look for evidence that will support their ideas, not for evidence that might contradict them; often, they present evidence in a way that makes it appear to be supportive; and often, they ignore inconvenient evidence. In a series of essays focusing on controversies, disputes, and discoveries, the authors vividly portray science as a human activity, driven by passion as well as by reason. By analyzing the fluidity of scientific concepts and the dynamic and unpredictable development of scientific fields, the authors paint a picture of modern science and the pressures it faces.