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

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  1. 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.score: 15.0
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  2. 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 Retracted Article: Improving Case-Based Ethics Training: How Modeling Behaviors and Forecasting Influence Effectiveness.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.score: 15.0
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  3. 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.score: 15.0
     
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  4. Nigel Harvey (2007). Use of Heuristics: Insights From Forecasting Research. Thinking and Reasoning 13 (1):5 – 24.score: 12.0
    Tversky and Kahneman (1974) originally discussed three main heuristics: availability, representativeness, and anchoring-and-adjustment. Research on judgemental forecasting suggests that the type of information on which forecasts are based is the primary factor determining the type of heuristic that people use to make their predictions. Specifically, availability is used when forecasts are based on information held in memory; representativeness is important when the value of one variable is forecast from explicit information about the value of another variable; and anchoring-and-adjustment is (...)
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  5. Cheryl K. Stenmark, Alison L. Antes, Xiaoqian Wang, Jared J. Caughron, Chase E. Thiel & Michael D. Mumford (2010). Strategies in Forecasting Outcomes in Ethical Decision-Making: Identifying and Analyzing the Causes of the Problem. Ethics and Behavior 20 (2):110 – 127.score: 12.0
    This study examined the role of key causal analysis strategies in forecasting and ethical decision-making. Undergraduate participants took on the role of the key actor in several ethical problems and were asked to identify and analyze the causes, forecast potential outcomes, and make a decision about each problem. Time pressure and analytic mindset were manipulated while participants worked through these problems. The results indicated that forecast quality was associated with decision ethicality, and the identification of the critical causes of (...)
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  6. Michael D. Mumford, Chase E. Thiel, Jared J. Caughron, Xiaoqian Wang, Alison L. Antes & Cheryl K. Stenmark (2010). Strategies in Forecasting Outcomes in Ethical Decision-Making: Identifying and Analyzing the Causes of the Problem. Ethics and Behavior 20 (2):110-127.score: 12.0
    This study examined the role of key causal analysis strategies in forecasting and ethical decision-making. Undergraduate participants took on the role of the key actor in several ethical problems and were asked to identify and analyze the causes, forecast potential outcomes, and make a decision about each problem. Time pressure and analytic mindset were manipulated while participants worked through these problems. The results indicated that forecast quality was associated with decision ethicality, and the identification of the critical causes of (...)
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  7. David A. Bessler & Zijun Wang (2012). D-Separation, Forecasting, and Economic Science: A Conjecture. [REVIEW] Theory and Decision 73 (2):295-314.score: 12.0
    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 modeling.
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  8. Robert S. Goldfarb, H. O. Stekler & Joel David (2005). Methodological Issues in Forecasting: Insights From the Egregious Business Forecast Errors of Late 1930. Journal of Economic Methodology 12 (4):517-542.score: 12.0
    This paper examines some economic forecasts made in late 1930 that were intended to predict economic activity in the United States in order to shed light on several methodological issues. We document that these forecasts were extremely optimistic, predicting that the recession in the US would soon end, and that 1931 would show a recovery. These forecasts displayed egregious errors, because 1931 witnessed the largest negative growth rate for the US economy in any year in the twentieth century. A specific (...)
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  9. Lauren N. Harkrider, Chase E. Thiel, Zhanna Bagdasarov, Michael D. Mumford, James F. Johnson, Shane Connelly & Lynn D. Devenport (2012). Improving Case-Based Ethics Training with Codes of Conduct and Forecasting Content. Ethics and Behavior 22 (4):258 - 280.score: 12.0
    Although case-based training is popular for ethics education, little is known about how specific case content influences training effectiveness. Therefore, the effects of (a) codes of ethical conduct and (b) forecasting content were investigated. Results revealed richer cases, including both codes and forecasting content, led to increased knowledge acquisition, greater sensemaking strategy use, and better decision ethicality. With richer cases, a specific pattern emerged. Specifically, content describing codes alone was more effective when combined with short-term forecasts, whereas content (...)
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  10. Cheryl Stenmark (2013). Forecasting and Ethical Decision Making: What Matters? Ethics and Behavior 23 (6):445-462.score: 12.0
    This study examined how the number and types of consequences considered are related to forecasting and ethical decision making. Undergraduate participants took on the role of the key actor in several ethical problems and were asked to forecast potential outcomes and make a decision about each problem. Performance pressure was manipulated by ostensibly making rewards contingent on good problem-solving performance. The results indicated that forecast quality was associated with decision ethicality, and the identification of the critical consequences of the (...)
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  11. Peter Ayton, Alice Pott & Najat Elwakili (2007). Affective Forecasting: Why Can't People Predict Their Emotions? Thinking and Reasoning 13 (1):62 – 80.score: 10.0
    Two studies explore the frequently reported finding that affective forecasts are too extreme. In the first study, driving test candidates forecast the emotional consequences of failing. Test failers overestimated the duration of their disappointment. Greater previous experience of this emotional event did not lead to any greater accuracy of the forecasts, suggesting that learning about one's own emotions is difficult. Failers' self-assessed chances of passing were lower a week after the test than immediately prior to the test; this difference correlated (...)
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  12. Teddy Seidenfeld, Mark Schervish & Jay Kadane, Forecasting with Imprecise/Indeterminate Probabilities [IP] – Some Preliminary Findings.score: 10.0
    Part 1 Background on de Finetti’s twin criteria of coherence: Coherence1: 2-sided previsions free from dominance through a Book. Coherence2: Forecasts free from dominance under Brier (squared error) score. Part 2 IP theory based on a scoring rule.
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  13. David Nerini, Jean Pierre Durbec, Claude Mante, Fabrice Garcia & Badih Ghattas (2000). Forecasting Physicochemical Variables by a Classification Tree Method. Application to the Berre Lagoon (South France). Acta Biotheoretica 48 (3-4).score: 10.0
    The dynamics of the "Etang de Berre", a brackish lagoon situated close to the French Mediterranean sea coast, is strongly disturbed by freshwater inputs coming from an hydroelectric power station. The system dynamics has been described as a sequence of daily typical states from a set of physicochemical variables such as temperature, salinity and dissolved oxygen rates collected over three years by an automatic sampling station. Each daily pattern summarizes the evolution, hour by hour of the physicochemical variables. This article (...)
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  14. Philip E. Tetlock, Michael C. Horowitz & Richard Herrmann (2012). Should “Systems Thinkers” Accept the Limits on Political Forecasting or Push the Limits? Critical Review 24 (3):375-391.score: 10.0
    Historical analysis and policy making often require counterfactual thought experiments that isolate hypothesized causes from a vast array of historical possibilities. However, a core precept of Jervis's ?systems thinking? is that causes are so interconnected that the historian can only with great difficulty imagine causation by subtracting all variables but one. Prediction, according to Jervis, is even more problematic: The more sensitive an event is to initial conditions (e.g., butterfly effects), the harder it is to derive accurate forecasts. Nevertheless, if (...)
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  15. Nelson Goodman (1983). Fact, Fiction, and Forecast. Harvard University Press.score: 9.0
    In his new foreword to this edition, Hilary Putnam forcefully rejects these nativist claims.
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  16. Philip Brey (2012). Anticipatory Ethics for Emerging Technologies. Nanoethics 6 (1):1-13.score: 9.0
    Abstract In this essay, a new approach for the ethical study of emerging technology ethics will be presented, called anticipatory technology ethics (ATE). The ethics of emerging technology is the study of ethical issues at the R&D and introduction stage of technology development through anticipation of possible future devices, applications, and social consequences. I will argue that a major problem for its development is the problem of uncertainty, which can only be overcome through methodologically sound forecasting and futures studies. (...)
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  17. M. A. Gareev (1998). If War Comes Tomorrow?: The Contours of Future Armed Conflict. Frank Cass.score: 9.0
    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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  18. Roman Frigg, Seamus Bradley, Reason L. Machete & Leonard A. Smith, Probabilistic Forecasting: Why Model Imperfection is a Poison Pill.score: 9.0
    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 philosophers interpret and motivate (...)
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  19. Martin Wachs (1990). Ethics and Advocacy in Forecasting for Public Policy. Business and Professional Ethics Journal 9 (1/2):141-157.score: 9.0
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  20. Robert Evans (2007). Social Networks and Private Spaces in Economic Forecasting. Studies in History and Philosophy of Science Part A 38 (4):686-697.score: 9.0
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  21. Kristina A. Diekmann (2008). “She Did What? There is No Way I Would Do That!” The Potential Interpersonal Harm Caused by Mispredicting One's Behavior. Journal of Business Ethics 80 (1):5 - 11.score: 9.0
    When forecasting their own behavior, people are often inaccurate and tend to predict that they will engage in more socially desirable behavior than they actually do. The problem with inaccurate behavioral forecasts is that they can lead to negative consequences both for the self and for others. One particularly negative consequence may be that such errors can produce overly harsh evaluations and condemnation of others who do not act in a way that most people predict they themselves would act. (...)
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  22. D. S. Horner (2005). Anticipating Ethical Challenges: Is There a Coming Era of Nanotechnology? [REVIEW] Ethics and Information Technology 7 (3):127-138.score: 9.0
    In this paper I question the claims made for a ‘coming era of nanotechnology’ and the ethical challenges, it is argued, that are entailed by this particular technological revolution. I argue that such futurist claims are sustained by an untenable modernist narrative which separates the technical and the social. This is exemplified by the work of K. Eric Drexler and his claim that whilst the course of scientific knowledge may remain unpredictable we nevertheless can predict with accuracy the trajectory of (...)
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  23. Rosamond Rhodes & James J. Strain (2007). Affective Forecasting and Its Implications for Medical Ethics. Cambridge Quarterly of Healthcare Ethics 17 (01):54-65.score: 9.0
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  24. Friedel Weinert (1999). Predicting the Future: An Introduction to the Theory of Forecasting by Nicholas Rescher. State University of New York Press, Albany, 1998, Pp. XI + 232. Philosophy 74 (1):122-139.score: 9.0
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  25. Nada Gligorov (2009). Reconsidering the Impact of Affective Forecasting. Cambridge Quarterly of Healthcare Ethics 18 (02):166-.score: 9.0
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  26. Rosamond Rhodes & James J. Strain (2009). Further Thoughts About Affective Forecasting Biases in Medicine: A Response to Nada Gligorov. Cambridge Quarterly of Healthcare Ethics 18 (02):174-.score: 9.0
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  27. Stanley R. Barrett (1999). Forecasting Theory: Problems and Exemplars in the Twenty-First Century. In E. L. Cerroni-Long (ed.), Anthropological Theory in North America. Bergin & Garvey. 255.score: 9.0
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  28. Daniel B. Botkin, Henrik Saxe, Miguel B. Araujo, Richard Betts, Richard Hw Bradshaw, Tomas Cedhagen, Peter Chesson, Terry P. Dawson, Julie R. Etterson & Daniel P. Faith (2007). Forecasting the Effects of Global Warming on Biodiversity. Bioscience 57 (3):227-236.score: 9.0
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  29. Shyi-Ming Chen (2002). Forecasting Enrollments Based on High-Order Fuzzy Time Series. In Robert Trappl (ed.), Cybernetics and Systems. Austrian Society for Cybernetics Studies. 33--1.score: 9.0
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  30. Newton C. A. da Costa & FranciscoAntonio Doria (1994). Gödel Incompleteness in Analysis, with an Application to the Forecasting Problem in the Social Sciences. Philosophia Naturalis 31 (1):1-24.score: 9.0
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  31. Francis X. Diebold & Glenn D. Rudebusch (2013). Yield Curve Modeling and Forecasting: The Dynamic Nelson-Siegel Approach. Princeton University Press.score: 9.0
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  32. Vladimir Faifr, Fedor Gal, Martin Potucek & Milos Zeman (1984). Forecasting Modelling by Means of the KPM Method. World Futures 20 (1):105-133.score: 9.0
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  33. F. Mobio (2000). Stock-Market Forecasting as Cosmography. Diogenes 48 (190):43-57.score: 9.0
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  34. J. Barnard Gilmore (1991). On Forecasting Validity and Finessing Reliability. Behavioral and Brain Sciences 14 (1):148-149.score: 9.0
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  35. Hugh Duncan Grant (1937). Long-Range Weather Forecasting. Thought 12 (2):265-282.score: 9.0
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  36. Clive Wj Granger (2012). The Philosophy of Economic Forecasting. In Uskali Mäki, Dov M. Gabbay, Paul Thagard & John Woods (eds.), Philosophy of Economics. North Holland.score: 9.0
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  37. Peter Gärdenfors (1982). Dynamic Models as Tools for Forecasting and Planning: A Presentation and Some Methodological Aspects. Theory and Decision 14 (3):237-273.score: 9.0
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  38. N. Harvey & P. Ayton (1990). Actor-Observer Differences in Judgmental Probability Forecasting of Control Response Efficacy. Bulletin of the Psychonomic Society 28 (6):523-523.score: 9.0
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  39. Michael Hoerger, Stuart W. Quirk, Benjamin P. Chapman & Paul R. Duberstein (2012). Affective Forecasting and Self-Rated Symptoms of Depression, Anxiety, and Hypomania: Evidence for a Dysphoric Forecasting Bias. Cognition and Emotion 26 (6):1098-1106.score: 9.0
  40. 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.score: 9.0
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  41. M. R. Hyman (1988). The Timeliness Problem in the Application of Bass-Type New Product-Growth Models to Durable Sales Forecasting. Journal of Business Research 16 (1):31--47.score: 9.0
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  42. David Johnstone (2007). Economic Darwinism: Who has the Best Probabilities? [REVIEW] Theory and Decision 62 (1):47-96.score: 9.0
    Simulation evidence obtained within a Bayesian model of price-setting in a betting market, where anonymous gamblers queue to bet against a risk-neutral bookmaker, suggests that a gambler who wants to maximize future profits should trade on the advice of the analyst cum probability forecaster who records the best probability score, rather than the highest trading profits, during the preceding observation period. In general, probability scoring rules, specifically the log score and better known “Brier” (quadratic) score, are found to have higher (...)
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  43. Sine N. Just, Nico Mouton & Jonas Gabrielsen (2013). Looking Forward: On the Uses of Forecasting in Market Formation. International Journal of Management Concepts and Philosophy 7 (3/4):224.score: 9.0
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  44. Alfred Kähler (forthcoming). Forecasting the Business Cycle. Social Research.score: 9.0
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  45. Robert Kubey (2000). TV and the Internet: Pitfalls in Forecasting the Future. Knowledge, Technology and Policy 13 (2):63-85.score: 9.0
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  46. F. Kutta, A. Hodek, J. Dvorak, V. Rab, Z. Drab, L. Machon, J. Jirasek & M. Nebesky (1978). Ideological Discussion on Topic Planning-and-Forecasting-Social-Processes. Filosoficky Casopis 26 (2):329-347.score: 9.0
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  47. George Loewenstein (2007). Affect Regulation and Affective Forecasting. In James J. Gross (ed.), Handbook of Emotion Regulation. Guilford Press. 180--203.score: 9.0
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  48. Alexandra E. MacDougall, Lauren N. Harkrider, Zhanna Bagdasarov, James F. Johnson, Chase E. Thiel, Juandre Peacock, Michael D. Mumford, Lynn D. Devenport & Shane Connelly (2014). Examining the Effects of Incremental Case Presentation and Forecasting Outcomes on Case-Based Ethics Instruction. Ethics and Behavior 24 (2):126-150.score: 9.0
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  49. Carolyn R. Miller (1994). Opportunity, Opportunism, and Progress:Kairos in the Rhetoric of Technology. [REVIEW] Argumentation 8 (1):81-96.score: 9.0
    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 technological (...)
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  50. Franco Modigliani (forthcoming). Fluctuations in the Saving Ratio: A Problem in Economic Forecasting. Social Research.score: 9.0
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