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The Technological Obsolescence Of Scientific Fraud

Author

Listed:
  • Susan Feigenbaum
  • David M. Levy

Abstract

In a world where researchers prefer their experiments to have a particular outcome, scientific fraud and research bias are alternative methods to implement such preferences. A critical constraint distinguishes these two methods: biased research is `narrowly replicable' while fraud is non-replicable. Recent proposals to severely punish fraud have typically excluded biased research from their purview. An unintended consequence of such asymmetric sanctions is the substitution of creative uses of technology to bias research outcomes in favor of one's preferences. Importantly, such bias may be substantially more difficult to detect than outright fraud, given current scientific conventions. This article demonstrates, using the simplest of statistical examples, how biased outcomes can derive from seemingly unbiased procedures.

Suggested Citation

  • Susan Feigenbaum & David M. Levy, 1996. "The Technological Obsolescence Of Scientific Fraud," Rationality and Society, , vol. 8(3), pages 261-276, August.
  • Handle: RePEc:sae:ratsoc:v:8:y:1996:i:3:p:261-276
    DOI: 10.1177/104346396008003002
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    References listed on IDEAS

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    1. Denton, Frank T, 1985. "Data Mining as an Industry," The Review of Economics and Statistics, MIT Press, vol. 67(1), pages 124-127, February.
    2. Leamer, Edward E, 1983. "Let's Take the Con Out of Econometrics," American Economic Review, American Economic Association, vol. 73(1), pages 31-43, March.
    3. Levy, David M. & Feigenbaum, Susan, 1990. "Testing the replication hypothesis : When the data set is subject to gross error," Economics Letters, Elsevier, vol. 34(1), pages 49-53, September.
    4. David M. Levy, 1988. "The Market for Fame and Fortune," History of Political Economy, Duke University Press, vol. 20(4), pages 615-625, Winter.
    5. Stigler, George J & Becker, Gary S, 1977. "De Gustibus Non Est Disputandum," American Economic Review, American Economic Association, vol. 67(2), pages 76-90, March.
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    Cited by:

    1. Roger Koppl, 2005. "How to Improve Forensic Science," European Journal of Law and Economics, Springer, vol. 20(3), pages 255-286, November.
    2. Dalibor Roháč, 2012. "On economists and garbagemen: Reflections on Šťastný (2010)," The Review of Austrian Economics, Springer;Society for the Development of Austrian Economics, vol. 25(2), pages 173-183, June.
    3. David Levy & Sandra Peart, 2012. "Tullock on motivated inquiry: expert-induced uncertainty disguised as risk," Public Choice, Springer, vol. 152(1), pages 163-180, July.
    4. Auspurg Katrin & Hinz Thomas, 2011. "What Fuels Publication Bias?: Theoretical and Empirical Analyses of Risk Factors Using the Caliper Test," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 231(5-6), pages 636-660, October.
    5. Juan Pablo Couyoumdjian, 2008. "An Expert at Work: Revisiting Jeremy Bentham's Proposals on Codification," Kyklos, Wiley Blackwell, vol. 61(4), pages 503-519, November.
    6. Tyler Cowen, 2005. "Self-deception as the root of political failure," Public Choice, Springer, vol. 124(3), pages 437-451, September.
    7. Levy, David M. & Peart, Sandra J., 2004. "Statistical prejudice: from eugenics to immigrants," European Journal of Political Economy, Elsevier, vol. 20(1), pages 5-22, March.
    8. Chris Doucouliagos & T.D. Stanley, 2013. "Are All Economic Facts Greatly Exaggerated? Theory Competition And Selectivity," Journal of Economic Surveys, Wiley Blackwell, vol. 27(2), pages 316-339, April.

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