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Preface1: Learning from Error 2: Ducks, Rabbits, and Normal Science: Recasting the Kuhn's-Eye View of Popper 3: The New Experimentalism and the Bayesian Way 4: Duhem, Kuhn, and Bayes 5: Models of Experimental Inquiry 6: Severe Tests and Methodological Underdetermination7: The Experimental Basis from Which to Test Hypotheses: Brownian Motion8: Severe Tests and Novel Evidence 9: Hunting and Snooping: Understanding the Neyman-Pearson Predesignationist Stance10: Why You Cannot Be Just a Little Bit Bayesian 11: Why Pearson Rejected the Neyman-Pearson (Behavioristic) Philosophy and a Note on Objectivity in Statistics12: Error Statistics and Peircean Error Correction 13: Toward an Error-Statistical Philosophy of Science ReferencesIndex Copyright © Libri GmbH. All rights reserved.
The aim of Thinking through Error: The Moving Target of Knowledge is to describe knowledge as it works in our everyday attitude and behavior. Often in life, when making decisions and choices, we do not need to test the truth of our beliefs, so there must be another way to guide ourselves. With this in mind, Antomarini presents ‘thinking through error’ instead of ‘excluding error’. That is, we act through a slow process of guess-work, followed by quick gestures. By using our own uncertainty and our exploratory abilities, we face unpredictable situations and at the same time we acknowledge the constant presence of error in our thinking. Every decision we make continuously determines and replaces an entire universe within which that decision is plausible. Our everyday knowledge is a balance between a feeling of the truth and its negation.
In the past thirty years, historians have broadened the scope of their discipline to include many previously neglected topics and perspectives. They have chronicled language, madness, gender, and sexuality and have experimented with new forms of presentation. They have turned to the histories of non-Western peoples and to the troubled relations between “the West” and the rest. Allan Megill welcomes these developments, but he also suggests that there is now confusion among historians about what counts as a justified account of the past. In Historical Knowledge, Historical Error, Megill dispels some of the confusion. Here, he discusses issues of narrative, objectivity, and memory. He attacks what he sees as irresponsible uses of evidence while accepting the art of speculation, which incomplete evidence forces upon historians. Along the way, he offers succinct accounts of the epistemological road historians have traveled from Herodotus and Thucydides through Leopold von Ranke and Alexis de Tocqueville, and on to Hayden White, Natalie Zemon Davis, and Lynn Hunt.
This open access book – as the title suggests – explores some of the historical roots and epistemological ramifications of perspectivism. Perspectivism has recently emerged in philosophy of science as an interesting new position in the debate between scientific realism and anti-realism. But there is a lot more to perspectivism than discussions in philosophy of science so far have suggested. Perspectivism is a much broader view that emphasizes how our knowledge (in particular our scientific knowledge of nature) is situated; it is always from a human vantage point (as opposed to some Nagelian "view from nowhere"). This edited collection brings together a diverse team of established and early career scholars across a variety of fields (from the history of philosophy to epistemology and philosophy of science). The resulting nine essays trace some of the seminal ideas of perspectivism back to Kant, Nietzsche, the American Pragmatists, and Putnam, while the second part of the book tackles issues concerning the relation between perspectivism, relativism, and standpoint theories, and the implications of perspectivism for epistemological debates about veritism, epistemic normativity and the foundations of human knowledge.
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Although both philosophers and scientists are interested in how to obtain reliable knowledge in the face of error, there is a gap between their perspectives that has been an obstacle to progress. By means of a series of exchanges between the editors and leaders from the philosophy of science, statistics and economics, this volume offers a cumulative introduction connecting problems of traditional philosophy of science to problems of inference in statistical and empirical modelling practice. Philosophers of science and scientific practitioners are challenged to reevaluate the assumptions of their own theories - philosophical or methodological. Practitioners may better appreciate the foundational issues around which their questions revolve and thereby become better 'applied philosophers'. Conversely, new avenues emerge for finally solving recalcitrant philosophical problems of induction, explanation and theory testing.
Science is continually confronted by new and difficult social and ethical problems. Some of these problems have arisen from the transformation of the academic science of the prewar period into the industrialized science of the present. Traditional theories of science are now widely recognized as obsolete. In Scientific Knowledge and Its Social Problems (originally published in 1971), Jerome R. Ravetz analyzes the work of science as the creation and investigation of problems. He demonstrates the role of choice and value judgment, and the inevitability of error, in scientific research. Ravetz's new introductory essay is a masterful statement of how our understanding of science has evolved over the last two decades.
Experts estimate that as many as 98,000 people die in any given year from medical errors that occur in hospitals. That's more than die from motor vehicle accidents, breast cancer, or AIDSâ€"three causes that receive far more public attention. Indeed, more people die annually from medication errors than from workplace injuries. Add the financial cost to the human tragedy, and medical error easily rises to the top ranks of urgent, widespread public problems. To Err Is Human breaks the silence that has surrounded medical errors and their consequenceâ€"but not by pointing fingers at caring health care professionals who make honest mistakes. After all, to err is human. Instead, this book sets forth a national agendaâ€"with state and local implicationsâ€"for reducing medical errors and improving patient safety through the design of a safer health system. This volume reveals the often startling statistics of medical error and the disparity between the incidence of error and public perception of it, given many patients' expectations that the medical profession always performs perfectly. A careful examination is made of how the surrounding forces of legislation, regulation, and market activity influence the quality of care provided by health care organizations and then looks at their handling of medical mistakes. Using a detailed case study, the book reviews the current understanding of why these mistakes happen. A key theme is that legitimate liability concerns discourage reporting of errorsâ€"which begs the question, "How can we learn from our mistakes?" Balancing regulatory versus market-based initiatives and public versus private efforts, the Institute of Medicine presents wide-ranging recommendations for improving patient safety, in the areas of leadership, improved data collection and analysis, and development of effective systems at the level of direct patient care. To Err Is Human asserts that the problem is not bad people in health careâ€"it is that good people are working in bad systems that need to be made safer. Comprehensive and straightforward, this book offers a clear prescription for raising the level of patient safety in American health care. It also explains how patients themselves can influence the quality of care that they receive once they check into the hospital. This book will be vitally important to federal, state, and local health policy makers and regulators, health professional licensing officials, hospital administrators, medical educators and students, health caregivers, health journalists, patient advocatesâ€"as well as patients themselves. First in a series of publications from the Quality of Health Care in America, a project initiated by the Institute of Medicine
“The Knowledge Illusion is filled with insights on how we should deal with our individual ignorance and collective wisdom.” —Steven Pinker We all think we know more than we actually do. Humans have built hugely complex societies and technologies, but most of us don’t even know how a pen or a toilet works. How have we achieved so much despite understanding so little? Cognitive scientists Steven Sloman and Philip Fernbach argue that we survive and thrive despite our mental shortcomings because we live in a rich community of knowledge. The key to our intelligence lies in the people and things around us. We’re constantly drawing on information and expertise stored outside our heads: in our bodies, our environment, our possessions, and the community with which we interact—and usually we don’t even realize we’re doing it. The human mind is both brilliant and pathetic. We have mastered fire, created democratic institutions, stood on the moon, and sequenced our genome. And yet each of us is error prone, sometimes irrational, and often ignorant. The fundamentally communal nature of intelligence and knowledge explains why we often assume we know more than we really do, why political opinions and false beliefs are so hard to change, and why individual-oriented approaches to education and management frequently fail. But our collaborative minds also enable us to do amazing things. The Knowledge Illusion contends that true genius can be found in the ways we create intelligence using the community around us.