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. 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. 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. Bayes or Bust? provides the first balanced treatment of the complex set of issues involved in this nagging conundrum in the philosophy of science. 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. Reviewīayes or Bust? provides the first balanced treatment of the complex set of issues involved in this nagging conundrum in the philosophy of science. John Earman is Professor of History and Philosophy of Science at the University of Pittsburgh. By focusing on the need for a resolution to this impasse, Earman sharpens the issues on which a resolution turns. I then explain why the Principal Principle has, incorrectly, not traditionally been regarded as an inductive assumption.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. The principal source of modern Bayesianism's positive judgments of inductive relevance is not the Bayesian machinery itself, but rather what David Lewis calls the Principal Principle.Modern Bayesianism is more of a positive confirmation theory than Howson suggests, but that.To what extent is Bayesianism a positive confirmation theory, delivering particular judgements as to how evidence bears on scientific theories, and to what extent is it, as Colin Howson ( Hume's Problems) has recently claimed, more like a framework for confirmation theory capable of accommodating any kind of substantive inductive assumption about the proper relation between evidence and theory? I ask these questions of what is perhaps the most popular version of Bayesian confirmation theory, that presented recently in Howson and Urbach's Scientific Reasoning and Earman's Bayes or Bust?, which I call, after Earman, modern Bayesianism. Inductive Logic or Mere Inductive Framework?
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