Search results for 'Science Forecasting' (try it on Scholar)

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  1.  28
    David A. Bessler & Zijun Wang (2012). D-Separation, Forecasting, and Economic Science: A Conjecture. [REVIEW] Theory and Decision 73 (2):295-314.
    The paper considers the conjecture that forecasts from preferred economic models or theories d-separate forecasts from less preferred models or theories from the Actual realization of the variable for which a scientific explanation is sought. D-separation provides a succinct notion to represent forecast dominance of one set of forecasts over another; it provides, as well, a criterion for model preference as a fundamental device for progress in economic science. We demonstrate these ideas with examples from three areas of economic (...)
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  2. Walter A. McDougall (1989). Harnessing the Genie: Science and Technology Forecasting for the Air Force, 1944-1986Michael H. Gorn. Isis 80 (4):730-731.
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  3. Michio Kaku (1997). Visions: How Science Will Revolutionize the 21st Century. Anchor Books.
    In a spellbinding narrative that skillfully weaves together cutting-edge research among today's foremost scientists, theoretical physicist Michio Kaku--author of the bestselling book Hyperspace --presents a bold, exhilarating adventure into the science of tomorrow. In Visions, Dr. Kaku examines in vivid detail how the three scientific revolutions that profoundly reshaped the twentieth century--the quantum, biogenetic, and computer revolutions--will transform the way we live in the twenty-first century. The fundamental elements of matter and life--the particles of the atom and the nucleus (...)
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  4.  20
    Peter Coles (2006). From Cosmos to Chaos: The Science of Unpredictability. Oxford University Press.
    Cosmology has undergone a revolution in recent years. The exciting interplay between astronomy and fundamental physics has led to dramatic revelations, including the existence of the dark matter and the dark energy that appear to dominate our cosmos. But these discoveries only reveal themselves through small effects in noisy experimental data. Dealing with such observations requires the careful application of probability and statistics. But it is not only in the arcane world of fundamental physics that probability theory plays such an (...)
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  5. Werner Arber, N. Cabibbo & Marcelo Sánchez Sorondo (eds.) (2008). The Proceedings of the Plenary Session on Predictability in Science: Accuracy and Limitations: 3-6 November 2006. Pontifical Academy of Sciences.
     
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  6. George Steiner & Emílio Rui Vilar (eds.) (2008). Is Science Nearing its Limits? Fundação Calouste Gulbenkian.
     
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  7. Augusto Forti (ed.) (1984). Scientific Forecasting and Human Needs: Trends, Methods, and Message: Proceedings of a Symposium Held in Tbilisi, Ussr, 6-11 December 1981. [REVIEW] Pergamon.
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  8. B. J. Mason, Peter Mathias & J. H. Westcott (eds.) (1986). Predictability in Science and Society: A Joint Symposium of the Royal Society and the British Academy Held on 20 and 21 March 1986. [REVIEW] Distributed by Scholium International.
     
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  9. Ota Sulc (1977). Methodology of Forecasting Complex Development Processes of the Scientific and Technological Revolution. Centre for the Study of Science, Technology, and Develop[Ment], Council of Scientific and Industrial Research.
     
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  10.  47
    D. Napoletani, M. Panza & D. Struppa (2011). Agnostic Science. Towards a Philosophy of Data Analysis. Foundations of Science 16 (1):1-20.
    In this paper we will offer a few examples to illustrate the orientation of contemporary research in data analysis and we will investigate the corresponding role of mathematics. We argue that the modus operandi of data analysis is implicitly based on the belief that if we have collected enough and sufficiently diverse data, we will be able to answer most relevant questions concerning the phenomenon itself. This is a methodological paradigm strongly related, but not limited to, biology, and we label (...)
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  11.  16
    D. C. Struppa (2011). Agnostic Science. Towards a Philosophy of Data Analysis. Foundations of Science 16 (1):1-20.
    In this paper we will offer a few examples to illustrate the orientation of contemporary research in data analysis and we will investigate the corresponding role of mathematics. We argue that the modus operandi of data analysis is implicitly based on the belief that if we have collected enough and sufficiently diverse data, we will be able to answer most relevant questions concerning the phenomenon itself. This is a methodological paradigm strongly related, but not limited to, biology, and we label (...)
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  12.  22
    M. A. Gareev (1998). If War Comes Tomorrow?: The Contours of Future Armed Conflict. Frank Cass.
    Military affairs have been affected by major changes in the 19902. The bipolar world of two superpowers has gone. The Cold War and the global military confrontation that accompanied it have ended. A new military and political order has emerged, but the world has not become more stable, indeed, wars and armed conflict have become much more common. Forecasting the contours of future armed conflict is the primary object of this work. Focusing on the impact of new technologies, General (...)
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  13.  6
    J. B. Nation (ed.) (2003). Formal Descriptions of Developing Systems. Kluwer Academic Publishers.
    A cutting-edge survey of formal methods directed specifically at dealing with the deep mathematical problems engendered by the study of developing systems, in particular dealing with developing phase spaces, changing components, structures and functionalities, and the problem of emergence. Several papers deal with the modelling of particular experimental situations in population biology, economics and plant and muscle developments in addition to purely theoretical approaches. Novel approaches include differential inclusions and viability theory, growth tensors, archetypal dynamics, ensembles with variable structures, and (...)
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  14. Nelson Goodman (1983). Fact, Fiction, and Forecast. Harvard University Press.
    In his new foreword to this edition, Hilary Putnam forcefully rejects these nativist claims.
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  15.  73
    Eric C. Barnes (2008). The Paradox of Predictivism. Cambridge University Press.
    This account of predictivism has considerable consequences for the realist/anti-realist debate.
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  16. Michio Kaku (2012). 2100 Ke Ji da Wei Lai: Cong Xian Zai Dao 2100 Nian, Ke Ji Jiang Ru He Gai Bian Wo Men de Sheng Huo. Shi Bao Wen Hua Chu Ban Qi Ye Gu Fen You Xian Gong Si.
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  17.  6
    Michael Specter (2009). Denialism: How Irrational Thinking Hinders Scientific Progress, Harms the Planet, and Threatens Our Lives. Penguin Press.
    Vioxx and the fear of science -- Vaccines and the great denial -- The organic fetish -- The era of echinacea -- Race and the language of life -- Surfing the exponential.
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  18.  11
    Jamie Morgan (2012). Forecasting, Prediction and Precision: A Commentary. Economic Thought 1 (2).
    Forecasting involves an underlying conceptualization of probability. It is this that gives sense to the notion of precision in number that makes us think of economic forecasting as more than simply complicated guesswork. We think of it as well-founded statement, a science and not an art of numbers. However, this understanding is at odds with the nature of social reality and the attributes of the forecaster. We should think differently about how we both anticipate and make the (...)
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  19.  14
    Lauren N. Harkrider, Alexandra E. MacDougall, Zhanna Bagdasarov, James F. Johnson, Michael D. Mumford, Shane Connelly & Lynn D. Devenport (2014). Retracted Article: Improving Case-Based Ethics Training: How Modeling Behaviors and Forecasting Influence Effectiveness. Science and Engineering Ethics 20 (1):299-299.
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  20. Tʻae-chʻang Kim & James Allen Dator (eds.) (1999). Co-Creating a Public Philosophy for Future Generations. Praeger.
  21. Zengquan Zhu (2005). Guan Zhan Bi Ji: Yi Ge Zhongguo Jiang Jun Yan Zhong de Wei Lai Zhan Zheng. Chang Jiang Wen Yi Chu Ban She.
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  22.  45
    Brent Ranalli (2012). Climate Science, Character, and the "Hard-Won" Consensus. Kennedy Institute of Ethics Journal 22 (2):183-210.
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  23.  10
    Robert Evans (2007). Social Networks and Private Spaces in Economic Forecasting. Studies in History and Philosophy of Science Part A 38 (4):686-697.
    The outputs of economic forecasting—predictions for national economic indicators such as GDP, unemployment rates and inflation—are all highly visible. The production of these forecasts is a much more private affair, however, typically being thought of as the work of individual forecasters or forecast teams using their economic model to produce a forecast that is then made public. This conception over-emphasises the individual and the technical whilst silencing the broader social context through which economic forecasters develop the expertise that is (...)
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  24. Carlo Maria Flumiani (1978). The Economic Philosophy of History & the Science of Maximal Prediction. American Classical College Press.
     
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  25. Neil F. Johnson (2009). Simply Complexity: A Clear Guide to Complexity Theory. Oneworld.
    What exactly is complexity science? Two's company, three is complexity ; Disorder rules, OK? ; Chaos and all that jazz ; Mob mentality ; Getting connected -- What can complexity science do for me? Forecasting financial markets ; Tackling traffic networks and climbing the corporate ladder ; Looking for Mr./Mrs. Right ; Coping with conflict : next-generation wars and global terrorism -- Catching a cold, avoiding super-flu and curing cancer ; The mother of all complexities : our (...)
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  26.  15
    Roman Frigg, Seamus Bradley, Reason L. Machete & Leonard A. Smith, Probabilistic Forecasting: Why Model Imperfection is a Poison Pill.
    This volume is a serious attempt to open up the subject of European philosophy of science to real thought, and provide the structural basis for the interdisciplinary development of its specialist fields, but also to provoke reflection on the idea of ‘European philosophy of science’. This efforts should foster a contemporaneous reflection on what might be meant by philosophy of science in Europe and European philosophy of science, and how in fact awareness of it could assist (...)
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  27.  13
    Carolyn R. Miller (1994). Opportunity, Opportunism, and Progress:Kairos in the Rhetoric of Technology. [REVIEW] Argumentation 8 (1):81-96.
    As the principle of timing or opportunity,kairos serves both as a powerful theme within technological discourse and as an analytical concept that explains some of the suasory force by which such discourse maintains itself and its position in our culture. This essay makes a case for a rhetoric of technology that is distinct from the rhetoric of science and illustrates the value of the classical vocabulary for understanding contemporary rhetoric. This case is made by examining images and models of (...)
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  28.  3
    William Thomas & Lambert Williams (2009). The Epistemologies of Non-Forecasting Simulations, Part I: Industrial Dynamics and Management Pedagogy at MIT. Science in Context 22 (2):245.
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  29.  1
    Leon Wansleben (2014). Consistent Forecasting Vs. Anchoring of Market Stories: Two Cultures of Modeling and Model Use in a Bank. Science in Context 27 (4):605-630.
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  30.  3
    Lambert Williams & William Thomas (2009). The Epistemologies of Non-Forecasting Simulations, Part II: Climate, Chaos, Computing Style, and the Contextual Plasticity of Error. Science in Context 22 (2):271.
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  31.  2
    Devon Stillwell (2013). Genetic Counseling in Historical Perspective: Understanding Our Hereditary Past and Forecasting Our Genomic Future. Studies in History and Philosophy of Science Part A 44 (4):618-622.
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  32. Wei Huang, Lean Yu, Shouyang Wang, Yukun Bao & Lin Wang (2006). Computational Finance and Business Intelligence-Comparisons of the Different Frequencies of Input Data for Neural Networks in Foreign Exchange Rates Forecasting. In O. Stock & M. Schaerf (eds.), Lecture Notes in Computer Science. Springer-Verlag 517-524.
     
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  33. Jones Jeans (2008). Today and Tomorrow Volume 9 Science and Medicine: Eos or the Wider Aspects of Cosmogony Hermes, or the Future of Chemistry Sybilla, or the Revival of Prophecy Archimedes or the Future of Physics. Routledge.
    Eos or the Wider Aspects of Cosmogony J H Jeans Originally published in 1928 "A fascinating summary of his tremendous conclusions…" Times Literary Supplement "No book in the series surpasses Eos in brilliance and profundity…" Is this universe permanent or transitory? If transitory, is it near its end or just beginning? Is life common or rare? Where does life stand in relation t the stupendous mass of inert matter? These and other issues are lucidly dealt with in this book. 80pp, (...)
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  34. William Meyer (2003). Scanning the Skies: A History of Tornado Forecasting. [REVIEW] Isis: A Journal of the History of Science 94:779-780.
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  35. Alexander Mourelatos (2005). The Ancients''Meteorology': Forecasting and Cosmic Natural History. Rhizai. A Journal for Ancient Philosophy and Science 2:279-291.
    A Critical Notice of Liba Taub, Ancient Meteorology, Routledge, London and New York, 2003.
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  36.  61
    Bruno Latour (1987). Science in Action: How to Follow Scientists and Engineers Through Society. Harvard University Press.
    In this book Bruno Latour brings together these different approaches to provide a lively and challenging analysis of science, demonstrating how social context..
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  37. Maya J. Goldenberg (forthcoming). Public Misunderstanding of Science? Reframing the Problem of Vaccine Hesitancy. Perspectives on Science:552-581.
    Public resistance towards scientific claims regarding vaccine safety is widely thought to stem from public misunderstanding (or ignorance) of science. Repeated failures to alleviate this ignorance make the problem of vaccine hesitancy seem intractable. I challenge this presumption of knowledge deficit and reinterpret vaccine hesitancy to be a problem of public mistrust of scientific experts and institutions. This finding invites new corrective measures: self-scrutiny by our scientific and governmental bodies regarding their own credibility as well as investment in dialogical (...)
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  38.  1
    Kristine C. Harper (2006). Meteorology's Struggle for Professional Recognition in the USA (1900–1950). Annals of Science 63 (2):179-199.
    Summary Meteorology, a scientific discipline almost exclusively associated with weather forecasting in the first half of the twentieth century in the USA, was viewed with disdain by more mathematically based scientific communities. A descriptive science lacking in physical and mathematical rigor, meteorology was typically without an academic home in US colleges and universities. This stood in sharp contrast to the meteorological communities across the Atlantic which were supported by dedicated geophysical institutes. Four factors kept US meteorologists, unlike their (...)
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  39. Jerry A. Fodor (1981). Representations: Philosophical Essays on the Foundations of Cognitive Science. MIT Press.
  40. Anthony J. Marcel & E. Bisiach (eds.) (1988). Consciousness in Contemporary Science. Oxford University Press.
    The significance of consciousness in modern science is discussed by leading authorities from a variety of disciplines. Presenting a wide-ranging survey of current thinking on this important topic, the contributors address such issues as the status of different aspects of consciousness; the criteria for using the concept of consciousness and identifying instances of it; the basis of consciousness in functional brain organization; the relationship between different levels of theoretical discourse; and the functions of consciousness.
     
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  41. Luca Tambolo (2015). A Tale of Three Theories: Feyerabend and Popper on Progress and the Aim of Science. Studies in History and Philosophy of Science Part A 51:33-41.
    In this paper, three theories of progress and the aim of science are discussed: the theory of progress as increasing explanatory power, advocated by Popper in The logic of scientific discovery ; the theory of progress as approximation to the truth, introduced by Popper in Conjectures and refutations ; the theory of progress as a steady increase of competing alternatives, which Feyerabend put forward in the essay “Reply to criticism. Comments on Smart, Sellars and Putnam” and defended as late (...)
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  42. Torsten Wilholt (2013). Epistemic Trust in Science. British Journal for the Philosophy of Science 64 (2):233-253.
    Epistemic trust is crucial for science. This article aims to identify the kinds of assumptions that are involved in epistemic trust as it is required for the successful operation of science as a collective epistemic enterprise. The relevant kind of reliance should involve working from the assumption that the epistemic endeavors of others are appropriately geared towards the truth, but the exact content of this assumption is more difficult to analyze than it might appear. The root of the (...)
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  43.  25
    Larry Laudan (1984). Science and Values: The Aims of Science and Their Role in Scientific Debate. University of California Press.
    Laudan constructs a fresh approach to a longtime problem for the philosopher of science: how to explain the simultaneous and widespread presence of both agreement and disagreement in science. Laudan critiques the logical empiricists and the post-positivists as he stresses the need for centrality and values and the interdependence of values, methods, and facts as prerequisites to solving the problems of consensus and dissent in science.
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  44. Massimo Pigliucci (2014). 5 Questions on Science & Religion. In Gregg D. Caruso (ed.), 5 Questions on Science & Religion. Automatic Press 163-170.
    Are science and religion compatible when it comes to understanding cosmology (the origin of the universe), biology (the origin of life and of the human species), ethics, and the human mind (minds, brains, souls, and free will)? Do science and religion occupy non-overlapping magisteria? Is Intelligent Design a scientific theory? How do the various faith traditions view the relationship between science and religion? What, if any, are the limits of scientific explanation? What are the most important open (...)
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  45.  46
    Emiliano Ippoliti, Thomas Nickles & Fabio Sterpetti (2016). Modeling and Inferring in Science. In Emiliano Ippoliti, Fabio Sterpetti & Thomas Nickles (eds.), Models and Inferences in Science. Springer 1-9.
    Science continually contributes new models and rethinks old ones. The way inferences are made is constantly being re-evaluated. The practice and achievements of science are both shaped by this process, so it is important to understand how models and inferences are made. But, despite the relevance of models and inference in scientific practice, these concepts still remain contro-versial in many respects. The attempt to understand the ways models and infer-ences are made basically opens two roads. The first one (...)
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  46. Jerry A. Fodor (1998). Concepts: Where Cognitive Science Went Wrong. Oxford University Press.
    The renowned philosopher Jerry Fodor, a leading figure in the study of the mind for more than twenty years, presents a strikingly original theory on the basic constituents of thought. He suggests that the heart of cognitive science is its theory of concepts, and that cognitive scientists have gone badly wrong in many areas because their assumptions about concepts have been mistaken. Fodor argues compellingly for an atomistic theory of concepts, deals out witty and pugnacious demolitions of rival theories, (...)
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  47. Massimo Pigliucci & Maarten Boudry (2011). Why Machine-Information Metaphors Are Bad for Science and Science Education. Science and Education 20 (453):471.
    Genes are often described by biologists using metaphors derived from computa- tional science: they are thought of as carriers of information, as being the equivalent of ‘‘blueprints’’ for the construction of organisms. Likewise, cells are often characterized as ‘‘factories’’ and organisms themselves become analogous to machines. Accordingly, when the human genome project was initially announced, the promise was that we would soon know how a human being is made, just as we know how to make airplanes and buildings. Impor- (...)
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  48. Ian Hacking (1983). Representing and Intervening: Introductory Topics in the Philosophy of Natural Science. Cambridge University Press.
    This is a lively and clearly written introduction to the philosophy of natural science, organized around the central theme of scientific realism. It has two parts. 'Representing' deals with the different philosophical accounts of scientific objectivity and the reality of scientific entities. The views of Kuhn, Feyerabend, Lakatos, Putnam, van Fraassen, and others, are all considered. 'Intervening' presents the first sustained treatment of experimental science for many years and uses it to give a new direction to debates about (...)
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  49. Nancy Cartwright (1999). The Dappled World: A Study of the Boundaries of Science. Cambridge University Press.
    It is often supposed that the spectacular successes of our modern mathematical sciences support a lofty vision of a world completely ordered by one single elegant theory. In this book Nancy Cartwright argues to the contrary. When we draw our image of the world from the way modern science works - as empiricism teaches us we should - we end up with a world where some features are precisely ordered, others are given to rough regularity and still others behave (...)
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  50.  26
    Ingo Brigandt (2016). Why the Difference Between Explanation and Argument Matters to Science Education. Science and Education 25:251-275.
    Contributing to the recent debate on whether or not explanations ought to be differentiated from arguments, this article argues that the distinction matters to science education. I articulate the distinction in terms of explanations and arguments having to meet different standards of adequacy. Standards of explanatory adequacy are important because they correspond to what counts as a good explanation in a science classroom, whereas a focus on evidence-based argumentation can obscure such standards of what makes an explanation explanatory. (...)
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