Knowledge and Reference in Empirical Science is a fascinating study of the bounds between science and language: in what sense, and of what, does science provide knowledge? Is science an instrument only distantly related to what's real? Can the language of science be used to adequately describe the truth? In this book, Jodi Azziouni investigates the technology of science - the actual forging and exploiting of causal links, between ourselves and what we endeavor to know and understand.
Knowledge and Reference in Empirical Science is a fascinating study of the bounds between science and language: in what sense, and of what, does science provide knowledge? Is science an instrument only distantly related to what's real? Can the language of science be used to adequately describe the truth? In this book, Jody Azziouni investigates the technology of science - the actual forging and exploiting of causal links, between ourselves and what we endeavor to know and understand.
"[Goldman's] theory of knowing is novel, powerful and yet fairly simple. His attack on skepticism is as persuasive and as well worked-out as any I know."--William Gregory Lycan, University of North Carolina at Chapel Hill "In both conception and execution this is a fine book. . . . Goldman's treatment is fresh and invigorating."--Frederick Schmitt, University of Illinois at Urbana-Champaign "[Goldman's] theory of knowing is novel, powerful and yet fairly simple. His attack on skepticism is as persuasive and as well worked-out as any I know."--William Gregory Lycan, University of North Carolina at Chapel Hill
One of the pathways by which the scientific community confirms the validity of a new scientific discovery is by repeating the research that produced it. When a scientific effort fails to independently confirm the computations or results of a previous study, some fear that it may be a symptom of a lack of rigor in science, while others argue that such an observed inconsistency can be an important precursor to new discovery. Concerns about reproducibility and replicability have been expressed in both scientific and popular media. As these concerns came to light, Congress requested that the National Academies of Sciences, Engineering, and Medicine conduct a study to assess the extent of issues related to reproducibility and replicability and to offer recommendations for improving rigor and transparency in scientific research. Reproducibility and Replicability in Science defines reproducibility and replicability and examines the factors that may lead to non-reproducibility and non-replicability in research. Unlike the typical expectation of reproducibility between two computations, expectations about replicability are more nuanced, and in some cases a lack of replicability can aid the process of scientific discovery. This report provides recommendations to researchers, academic institutions, journals, and funders on steps they can take to improve reproducibility and replicability in science.
Students can easily misstep when they first begin to do research. Leanne C. Powner’s new title Empirical Research and Writing: A Student′s Practical Guide provides valuable advice and guidance on conducting and writing about empirical research. Chapter by chapter, students are guided through the key steps in the research process. Written in a lively and engaging manner and with a dose of humor, this practical text shows students exactly how to choose a research topic, conduct a literature review, make research design decisions, collect and analyze data, and then write up and present the results. The book′s approachable style and just-in-time information delivery make it a text students will want to read, and its wide-ranging and surprisingly sophisticated coverage will make it an important resource for their later coursework.
How must our knowledge be systematically organized in order to justify our beliefs? There are two options—the solid securing of the ancient foundationalist pyramid or the risky adventure of the new coherentist raft. For the foundationalist like Descartes each piece of knowledge can be stacked to build a pyramid. Not so, argues Laurence BonJour. What looks like a pyramid is in fact a dead end, a blind alley. Better by far to choose the raft. Here BonJour sets out the most extensive antifoundationalist argument yet developed. The first part of the book offers a systematic exposition of foundationalist views and formulates a general argument to show that no variety of foundationalism provides an acceptable account of empirical justification. In the second part he explores a coherence theory of empirical knowledge and argues that a defensible theory must incorporate an adequate conception of observation. The book concludes with an account of the correspondence theory of empirical truth and an argument that systems of empirical belief which satisfy the coherentist standard of justification are also likely to be true.
“The Knowledge Machine is the most stunningly illuminating book of the last several decades regarding the all-important scientific enterprise.” —Rebecca Newberger Goldstein, author of Plato at the Googleplex A paradigm-shifting work, The Knowledge Machine revolutionizes our understanding of the origins and structure of science. • Why is science so powerful? • Why did it take so long—two thousand years after the invention of philosophy and mathematics—for the human race to start using science to learn the secrets of the universe? In a groundbreaking work that blends science, philosophy, and history, leading philosopher of science Michael Strevens answers these challenging questions, showing how science came about only once thinkers stumbled upon the astonishing idea that scientific breakthroughs could be accomplished by breaking the rules of logical argument. Like such classic works as Karl Popper’s The Logic of Scientific Discovery and Thomas Kuhn’s The Structure of Scientific Revolutions, The Knowledge Machine grapples with the meaning and origins of science, using a plethora of vivid historical examples to demonstrate that scientists willfully ignore religion, theoretical beauty, and even philosophy to embrace a constricted code of argument whose very narrowness channels unprecedented energy into empirical observation and experimentation. Strevens calls this scientific code the iron rule of explanation, and reveals the way in which the rule, precisely because it is unreasonably close-minded, overcomes individual prejudices to lead humanity inexorably toward the secrets of nature. “With a mixture of philosophical and historical argument, and written in an engrossing style” (Alan Ryan), The Knowledge Machine provides captivating portraits of some of the greatest luminaries in science’s history, including Isaac Newton, the chief architect of modern science and its foundational theories of motion and gravitation; William Whewell, perhaps the greatest philosopher-scientist of the early nineteenth century; and Murray Gell-Mann, discoverer of the quark. Today, Strevens argues, in the face of threats from a changing climate and global pandemics, the idiosyncratic but highly effective scientific knowledge machine must be protected from politicians, commercial interests, and even scientists themselves who seek to open it up, to make it less narrow and more rational—and thus to undermine its devotedly empirical search for truth. Rich with illuminating and often delightfully quirky illustrations, The Knowledge Machine, written in a winningly accessible style that belies the import of its revisionist and groundbreaking concepts, radically reframes much of what we thought we knew about the origins of the modern world.
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