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Why are philosophers more often right than others ? David Hume and general rules
[David Hume et les règles générales : Pourquoi les philosophes ont-ils plus raison que les autres ?]

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  • André Lapidus

    (PHARE - Philosophie, Histoire et Analyse des Représentations Économiques - UP1 - Université Paris 1 Panthéon-Sorbonne)

Abstract

This paper supports the contention that the general rules introduced by Hume in the Treatise on Human Nature (THN 1.3.15) are a selection mechanism for inductive inferences, which rejects two sources of inefficiency: (i) from emotional origin, which would reduce the uneasiness coming from a possible failure in the uniformity of nature; (ii) from cognitive origin, which would tolerate the possible overflow of the imagination on judgment. A growing consensus in recent decades, which distinguishes between two kinds of rules – extensive and corrective – is at the basis of this device. Whereas the extensive rules allow us to go beyond a singular experience and derive a wider range of inferences, the corrective rules, whose command opposes the philosopher to the vulgar, control and rectify the effects of extensive rules alone, so as to eliminate emotional and cognitive inefficiencies, and to make inferences that, borrowing the expression to Peirce, we will designate as abductive.

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  • André Lapidus, 2020. "Why are philosophers more often right than others ? David Hume and general rules [David Hume et les règles générales : Pourquoi les philosophes ont-ils plus raison que les autres ?]," Post-Print hal-01714256, HAL.
  • Handle: RePEc:hal:journl:hal-01714256
    DOI: 10.7202/1070256ar
    Note: View the original document on HAL open archive server: https://paris1.hal.science/hal-01714256v2
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    References listed on IDEAS

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    1. Arthur F. Burns & Wesley C. Mitchell, 1946. "Measuring Business Cycles," NBER Books, National Bureau of Economic Research, Inc, number burn46-1.
    2. Bateman, Bradley W., 1987. "Keynes's Changing Conception of Probability," Economics and Philosophy, Cambridge University Press, vol. 3(1), pages 97-119, April.
    3. Malinvaud, E., 1988. "Econometric Methodology at the Cowles Commission: Rise and Maturity," Econometric Theory, Cambridge University Press, vol. 4(2), pages 187-209, August.
    4. David Andrews, 1999. "Continuity and change in Keynes's thought: the importance of Hume," The European Journal of the History of Economic Thought, Taylor & Francis Journals, vol. 6(1), pages 1-21.
    5. Granger, C W J, 1969. "Investigating Causal Relations by Econometric Models and Cross-Spectral Methods," Econometrica, Econometric Society, vol. 37(3), pages 424-438, July.
    6. Jon Elster, 1998. "Emotions and Economic Theory," Journal of Economic Literature, American Economic Association, vol. 36(1), pages 47-74, March.
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