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  1. Naomi Oreskes (2013). Why I Am a Presentist. Science in Context 26 (4):595-609.
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  2. Naomi Oreskes (2012). Models All the Way Down. Metascience 21 (1):99-104.
    Models all the way down Content Type Journal Article Pages 1-6 DOI 10.1007/s11016-011-9558-9 Authors Naomi Oreskes, Department of History, University of California, San Diego La Jolla, CA 92093-0104, USA Journal Metascience Online ISSN 1467-9981 Print ISSN 0815-0796.
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  3. Steven Yearley, David Mercer, Andy Pitman, Naomi Oreskes & Erik Conway (2012). Perspectives on Global Warming. Metascience 21 (3):531-559.
    Perspectives on global warming Content Type Journal Article Category Book Symposium Pages 1-29 DOI 10.1007/s11016-011-9639-9 Authors Steven Yearley, ESRC Genomics Policy and Research Forum, University of Edinburgh, Holyrood Road, Edinburgh, EH8 8AQ UK David Mercer, Science and Technology Studies Program, University of Wollongong, Wollongong, NSW 2522, Australia Andy Pitman, Climate Change Research Centre, The University of New South Wales, Sydney, NSW 2052, Australia Naomi Oreskes, Department of History, University of California, San Diego, La Jolla, CA 92093-0104, USA Erik Conway, Caltech, (...)
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  4. Peter Galison, Victor S. Navasky, Naomi Oreskes, Anthony Romero & Aryeh Neier (2010). What We Have Learned About Limiting Knowledge in a Democracy. Social Research: An International Quarterly 77 (3):1013-1051.
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  5. Naomi Oreskes & Erik M. Conway (2010). Merchants of Doubt: How a Handful of Scientists Obscured the Truth on Issues From Tobacco Smoke to Global Warming. Bloomsbury Press.
    Industry doubt-mongering worked in part because most of us don' t really understand what it means to say something is a cause. We think it means that ifA causes B, then ifyou do A, you will get B. If smoking causes cancer, then if you smoke, ...
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  6. Naomi Oreskes, David A. Stainforth & Leonard A. Smith (2010). Adaptation to Global Warming: Do Climate Models Tell Us What We Need to Know? Philosophy of Science 77 (5):1012-1028.
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  7. Naomi Oreskes (2008). The Devil is in the (Historical) Details: Continental Drift as a Case of Normatively Appropriate Consensus? Perspectives on Science 16 (3):pp. 253-264.
    In Social Empiricism, Miriam Solomon proposes a via media between traditional philosophical realism and social construction of scientific knowledge, but ignores a large body of historical literature that has attempted to plough just that path. She also proposes a standard for normatively appropriate consensus that, arguably, no theory in the history of science has ever achieved, including her own ideal type—plate tectonics. And while valorizing dissent, she fails to consider how dissent has been used in recent decades as a political (...)
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  8. Naomi Oreskes & Erik M. Conway (2008). Challenging Knowledge: How Climate Science Became a Victim of the Cold War. In Robert N. Proctor & Londa Schiebinger (eds.), Agnotology: The Making and Unmaking of Ignorance. Stanford University Press Stanford, California. 55--89.
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  9. Naomi Oreskes (2007). The Scientific Consensus on Climate Change: How Do We Know We're Not Wrong? In Joseph F. DiMento & Pamela Doughman (eds.), Climate Change: What It Means for Us, Our Children, and Our Grandchildren. The Mit Press. 65.
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  10. Naomi Oreskes (2001). Author's Response. Metascience 10 (2):217-222.
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  11. Naomi Oreskes & James R. Fleming (2000). Why Geophysics? Studies in History and Philosophy of Science Part B: Studies in History and Philosophy of Modern Physics 31 (3):253-257.
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  12. Martin Rudwick, Naomi Oreskes, David Oldroyd, David Philip Miller, Alan Chalmers, John Forge, David Turnbull, Peter Slezak, David Bloor, Craig Callender, Keith Hutchison, Steven Savitt & Huw Price (1996). Review Symposia. Metascience 5 (1):7-85.
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  13. Naomi Oreskes, Kristin Shrader-Frechette & Kenneth Belitz (1994). Verification, Validation, and Confirmation of Numerical Models in the Earth Sciences. Science 263 (5147):641-646.
    Verification and validation of numerical models of natural systems is impossible. This is because natural systems are never closed and because model results are always nonunique. Models can be confirmed by the demonstration of agreement between observation and prediction, but confirmation is inherently partial. Complete confirmation is logically precluded by the fallacy of affirming the consequent and by incomplete access to natural phenomena. Models can only be evaluated in relative terms, and their predictive value is always open to question. The (...)
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