This book on the philosophy of science argues for an empiricism, opposed to the tradition of David Hume, in which singular rather than general causal claims are primary; causal laws express facts about singular causes whereas the general causal claims of science are ascriptions of capacities or causal powers, capacities to make things happen. Taking science as measurement, Cartwright argues that capacities are necessary for science and that these can be measured, provided suitable conditions are met. There are case studies (...) from both econometrics and quantum mechanics. (shrink)

In this new edition, Arthur Fine looks at Einstein's philosophy of science and develops his own views on realism. A new Afterword discusses the reaction to Fine's own theory. "What really led Einstein . . . to renounce the new quantum order? For those interested in this question, this book is compulsory reading."--Harvey R. Brown, American Journal of Physics "Fine has successfully combined a historical account of Einstein's philosophical views on quantum mechanics and a discussion of some of the philosophical (...) problems associated with the interpretation of quantum theory with a discussion of some of the contemporary questions concerning realism and antirealism. . . . Clear, thoughtful, [and] well-written."--Allan Franklin, Annals of Science "Attempts, from Einstein's published works and unpublished correspondence, to piece together a coherent picture of 'Einstein realism.' Especially illuminating are the letters between Einstein and fellow realist Schrodinger, as the latter was composing his famous 'Schrodinger-Cat' paper."--Nick Herbert, New Scientist "Beautifully clear. . . . Fine's analysis is penetrating, his own results original and important. . . . The book is a splendid combination of new ways to think about quantum mechanics, about realism, and about Einstein's views of both."--Nancy Cartwright, Isis. (shrink)

There is currently no viable alternative to the Bayesian analysis of scientific inference, yet the available versions of Bayesianism fail to do justice to several aspects of the testing and confirmation of scientific hypotheses. Bayes or Bust? provides the first balanced treatment of the complex set of issues involved in this nagging conundrum in the philosophy of science. Both Bayesians and anti-Bayesians will find a wealth of new insights on topics ranging from Bayes’s original paper to contemporary formal learning theory.In (...) a paper published posthumously in 1763, the Reverend Thomas Bayes made a seminal contribution to the understanding of "analogical or inductive reasoning." Building on his insights, modem Bayesians have developed an account of scientific inference that has attracted numerous champions as well as numerous detractors. Earman argues that Bayesianism provides the best hope for a comprehensive and unified account of scientific inference, yet the presently available versions of Bayesianisin fail to do justice to several aspects of the testing and confirming of scientific theories and hypotheses. By focusing on the need for a resolution to this impasse, Earman sharpens the issues on which a resolution turns. John Earman is Professor of History and Philosophy of Science at the University of Pittsburgh. (shrink)

There is currently no viable alternative to the Bayesian analysis of scientific inference, yet the available versions of Bayesianism fail to do justice to several aspects of the testing and confirmation of scientific hypotheses. Bayes or Bust? provides the first balanced treatment of the complex set of issues involved in this nagging conundrum in the philosophy of science. Both Bayesians and anti-Bayesians will find a wealth of new insights on topics ranging from Bayes's original paper to contemporary formal learning theory. (...) In a paper published posthumously in 1763, the Reverend Thomas Bayes made a seminal contribution to the understanding of "analogical or inductive reasoning." Building on his insights, modem Bayesians have developed an account of scientific inference that has attracted numerous champions as well as numerous detractors. Earman argues that Bayesianism provides the best hope for a comprehensive and unified account of scientific inference, yet the presently available versions of Bayesianisin fail to do justice to several aspects of the testing and confirming of scientific theories and hypotheses. By focusing on the need for a resolution to this impasse, Earman sharpens the issues on which a resolution turns. John Earman is Professor of History and Philosophy of Science at the University of Pittsburgh. (shrink)