This book is a defense of modal realism; the thesis that our world is but one of a plurality of worlds, and that the individuals that inhabit our world are only a few out of all the inhabitants of all the worlds. Lewis argues that the philosophical utility of modal realism is a good reason for believing that it is true.

Scientific realism is the optimistic view that modern science is on the right track: that the world really is the way our best scientific theories describe it. In his book, Stathis Psillos gives us a detailed and comprehensive study which restores the intuitive plausibility of scientific realism. We see that throughout the twentieth century, scientific realism has been challenged by philosophical positions from all angles: from reductive empiricism, to instrumentalism and to modern sceptical empiricism. _Scientific Realism_ explains that the history (...) of science does not undermine the arguments for scientific realism, but instead makes it reasonable to accept scientific realism as the best philosophical account of science, its empirical success, its progress and its practice. Anyone wishing to gain a deeper understanding of the state of modern science and why scientific realism is plausible, should read this book. (shrink)

A scientific community cannot practice its trade without some set of received beliefs. These beliefs form the foundation of the "educational initiation that prepares and licenses the student for professional practice". The nature of the "rigorous and rigid" preparation helps ensure that the received beliefs are firmly fixed in the student's mind. Scientists take great pains to defend the assumption that scientists know what the world is like...To this end, "normal science" will often suppress novelties which undermine its foundations. Research (...) is therefore not about discovering the unknown, but rather "a strenuous and devoted attempt to force nature into the conceptual boxes supplied by professional education". (shrink)

Thomas S. Kuhn's classic book is now available with a new index.

This classic remains one of Karl Popper's most wide-ranging and popular works, notable not only for its acute insight into the way scientific knowledge grows, but also for applying those insights to politics and to history.

_Conjectures and Refutations_ is one of Karl Popper's most wide-ranging and popular works, notable not only for its acute insight into the way scientific knowledge grows, but also for applying those insights to politics and to history. It provides one of the clearest and most accessible statements of the fundamental idea that guided his work: not only our knowledge, but our aims and our standards, grow through an unending process of trial and error.

Woodward's long awaited book is an attempt to construct a comprehensive account of causation explanation that applies to a wide variety of causal and explanatory claims in different areas of science and everyday life. The book engages some of the relevant literature from other disciplines, as Woodward weaves together examples, counterexamples, criticisms, defenses, objections, and replies into a convincing defense of the core of his theory, which is that we can analyze causation by appeal to the notion of manipulation.

This paper describes a theory of accuracy or approximate truth and applies it to problems in the realist interpretation of scientific theories. It argues not only that realism requires approximate truth, but that an adequate theory of approximation also presupposes some elements of a realist interpretation of theories. The paper distinguishes approximate truth from vagueness, probability and verisimilitude, and applies it to problems of confirmation and deduction from inaccurate premises. Basic results are cited, but details appear elsewhere. Objections are surveyed, (...) including arguments by Miller, Laymon, and Laudan. Comparison is made with Niiniluoto's theory of verisimilitude, and the utility of his theory for realism assessed. (shrink)

Arguably, there is no substantial, general answer to the question of what makes for the approximate truth of theories. But in one class of cases, the issue seems simply resolved. A wide class of applied dynamical theories can be treated as two-component theories—one component specifying a certain kind of abstract geometrical structure, the other giving empirical application to this structure by claiming that it replicates, subject to arbitrary scaling for units etc., the geometric structure to be found in some real-world (...) dynamical phenomenon. In such a case, a theory is approximately true just if the one geometric structure approximately replicates the other (and if problems remain here, they are problems in geometry, of specifying suitable metric approximation relations, not conceptual problems). This article amplifies and defends this simple approach to approximate truth for dynamical theories. (shrink)

The essays in this volume represent an approach to human knowledge that has had a profound influence on many recent thinkers. Popper breaks with a traditional commonsense theory of knowledge that can be traced back to Aristotle. A realist and fallibilist, he argues closely and in simple language that scientific knowledge, once stated in human language, is no longer part of ourselves but a separate entity that grows through critical selection.

What does it take for one proposition to be closer to the truth than another. In this, the first published monograph on the topic, Oddie develops a comprehensive theory that takes the likeness in truthlikeness seriously.

, whereby some causes are deemed more important than others, are ubiquitous in historical studies. Drawing from influential recent work on causation, I develop a definition of causal-explanatory strength. This makes clear exactly which aspects of explanatory weighting are subjective and which objective. It also sheds new light on several traditional issues, showing for instance that: underlying causes need not be more important than proximate ones; several different causes can each be responsible for most of an effect; small causes need (...) not be less important than big ones; and non-additive interactive effects between causes present no particular difficulty. Key Words: causation • explanation • history • interaction • proximate • underlying. (shrink)

The modern history of verisimilitude can be divided into three periods. The first began in 1960, when Karl Popper proposed his qualitative definition of what it is for one theory to be more truthlike than another theory, and lasted until 1974, when David Miller and Pavel Trich published their refutation of Popper's definition. The second period started immediately with the attempt to explicate truthlikeness by means of relations of similarity or resemblance between states of affairs (or their linguistic representations); the (...) work within this similarity approach was summarized in the books of Graham Oddie [1986] and Ilkka Niiniluoto [1987]. During the subsequent third period, studies in verisimilitude have been actively continued, and interesting results and applications have been achieved, but not many dramatic novelties. While it is now obsolete to claim that truthlikeness with reasonable properties cannot be defined at all, there is still a lot of controversy about the best and least arbitrary approach to doing this. (shrink)

In this bold work of broad scope and rich erudition, Richard W. Miller sets out to reorient the philosophy of science.

Traditional theories construe approximate truth or truthlikeness as a measure of closeness to facts, singular facts, and idealization as an act of either assuming zero of otherwise very small differences from facts or imagining ideal conditions under which scientific laws are either approximately true or will be so when the conditions are relaxed. I first explain the serious but not insurmountable difficulties for the theories of approximation, and then argue that more serious and perhaps insurmountable difficulties for the theory of (...) idealization force us to sever its close tie to approximation. This leads to an appreciation of lawlikeness as a measure of closeness to laws, which I argue is the real measure of idealization whose main purpose is to carve nature at its joints. (shrink)

Laudan constructs a fresh approach to a longtime problem for the philosopher of science: how to explain the simultaneous and widespread presence of both agreement and disagreement in science. Laudan critiques the logical empiricists and the post-positivists as he stresses the need for centrality and values and the interdependence of values, methods, and facts as prerequisites to solving the problems of consensus and dissent in science.

This book provides a post-positivist theory of deterministic and probabilistic causality that supports both quantitative and qualitative explanations. Features of particular interest include the ability to provide true explanations in contexts where our knowledge is incomplete, a systematic interpretation of causal modeling techniques in the social sciences, and a direct realist view of causal relations that is compatible with a liberal empiricism. The book should be of wide interest to both philosophers and scientists. Originally published in 1989. The Princeton Legacy (...) Library uses the latest print-on-demand technology to again make available previously out-of-print books from the distinguished backlist of Princeton University Press. These editions preserve the original texts of these important books while presenting them in durable paperback and hardcover editions. The goal of the Princeton Legacy Library is to vastly increase access to the rich scholarly heritage found in the thousands of books published by Princeton University Press since its founding in 1905. (shrink)

Following Dretske (1977), there has been a considerable body of literature on the role of contrastive stress in causal claims. Following van Fraassen (1980), there has been a considerable body of literature on the role of contrastive stress in explanations and explanation-requesting why-questions. Amazingly, the two bodies of literature have remained almost entirely disjoint. With an understanding of the contrastive nature of ordinary causal claims, and of the linguistic roles of contrastive stress, it is possible to provide a unified account (...) of both phenomena. I provide such an account from within the framework of a probabilistic theory of causation. Relations of screening-off, long familiar to researchers in probabilistic causality, play a central role in this account. (shrink)

An updated and extended second edition supporting the findings of its well-known predecessor which claimed that courts employ common-sense notions of causation in determining legal responsibility.

The auctions of the Federal Communication Commission, designed in 1994 to sell spectrum licences, are one of the few widely acclaimed and copied cases of economic engineering to date. This paper includes a detailed narrative of the process of designing, testing and implementing the FCC auctions, focusing in particular on the role played by game theoretical modelling and laboratory experimentation. Some general remarks about the scope, interpretation and use of rational choice models open and conclude the paper.

Recent interest in the problem of verisimilitude stemmed originally from Popper's desire to provide a non-inductive criterion of merit that will select between two false theories) But the problem has also been taken up by others who are not committed to Popper's anti-inductivism. Indeed Ilkka Niiniluoto has argued that the estimated degree of truthlikeness of a generalisation g which is compatible with evidence e can be equated with the inductive probability of g on e, wherever g is a constituent in (...) Hintikka's sense. It might therefore be worth while to approach the problem afresh, in order to determine quite generally whether a measure of verisimilitude is what is principally needed for the evaluation of scientific progress. I shall argue that it is not. (shrink)

This paper is both a survey and a review of the current state of the debate concerning verisimilitude. As a survey it is intended for the interested outsider who wants both easy access to and some comparison between the respective approaches. As a review it covers the first three books on the topic: those of Oddie. Niiniluoto and Kuipers.

Ever since David Hume, empiricists have barred powers and capacities from nature. In this book Cartwright argues that capacities are essential in our scientific world, and, contrary to empiricist orthodoxy, that they can meet sufficiently strict demands for testability. Econometrics is one discipline where probabilities are used to measure causal capacities, and the technology of modern physics provides several examples of testing capacities (such as lasers). Cartwright concludes by applying the lessons of the book about capacities and probabilities to the (...) explanation of the role of causality in quantum mechanics. (shrink)

I argue that scientific progress is precisely the accumulation of scientific knowledge.

D. Miller's demonstrations of the language dependence of truthlikeness raise a profound problem for the claim that scientific progress is objective. In two recent papers (Barnes 1990, 1991) I argue that the objectivity of progress may be grounded on the claim that the aim of science is not merely truth but knowledge; progress thus construed is objective in an epistemic sense. In this paper I construct a new solution to Miller's problem grounded on the notion of "approximate causal explanation" which (...) allows for linguistically invariant progress outside an epistemic context. I suggest that the notion of "approximate causal explanation" provides the resources for a more robust theory of progress than that provided by the notion of "approximate truth.". (shrink)

What sort of claims do scientific models make and how do these claims then underwrite empirical successes such as explanations and reliable policy interventions? In this paper I propose answers to these questions for the class of models used throughout the social and biological sciences, namely idealized deductive ones with a causal interpretation. I argue that the two main existing accounts misrepresent how these models are actually used, and propose a new account. *Received July 2006; revised August 2008. †To contact (...) the author, please write to: Department of Philosophy, University of Missouri, St. Louis, 599 Lucas Hall (MC 73), One University Blvd., St. Louis, MO 63121-4400; e-mail: [email protected]. (shrink)

Written by one of the preeminent researchers in the field, this book provides a comprehensive exposition of modern analysis of causation. It shows how causality has grown from a nebulous concept into a mathematical theory with significant applications in the fields of statistics, artificial intelligence, economics, philosophy, cognitive science, and the health and social sciences. Judea Pearl presents and unifies the probabilistic, manipulative, counterfactual, and structural approaches to causation and devises simple mathematical tools for studying the relationships between causal connections (...) and statistical associations. Cited in more than 2,100 scientific publications, it continues to liberate scientists from the traditional molds of statistical thinking. In this revised edition, Judea Pearl elucidates thorny issues, answers readers' questions, and offers a panoramic view of recent advances in this field of research. Causality will be of interest to students and professionals in a wide variety of fields. Dr Judea Pearl has received the 2011 Rumelhart Prize for his leading research in Artificial Intelligence and systems from The Cognitive Science Society. (shrink)

First published in 2002. Routledge is an imprint of Taylor & Francis, an informa company.

Causality offers the first comprehensive coverage of causal analysis in many sciences, including recent advances using graphical methods. Pearl presents a unified account of the probabilistic, manipulative, counterfactual and structural approaches to causation, and devises simple mathematical tools for analyzing the relationships between causal connections, statistical associations, actions and observations. The book will open the way for including causal analysis in the standard curriculum of statistics, artificial intelligence, business, epidemiology, social science and economics.