, Volume 78, Issue 6, pp 1347–1365 | Cite as

Is There a Statistical Solution to the Generality Problem?

  • Julien Dutant
  • Erik J. Olsson
Original Article


This article is concerned with a statistical proposal due to James R. Beebe for how to solve the generality problem for process reliabilism. The proposal is highlighted by Alvin I. Goldman as an interesting candidate solution. However, Goldman raises the worry that the proposal may not always yield a determinate result. We address this worry by proving a dilemma: either the statistical approach does not yield a determinate result or it leads to trivialization, i.e. reliability collapses into truth (and anti-reliability into falsehood). Various strategies for avoiding this predicament are considered, including revising the statistical rule or restricting its application to natural kinds. All amendments are seen to have serious problems of their own. We conclude that reliabilists need to look elsewhere for a convincing solution to the generality problem.


True Belief Natural Kind Process Type Cognitive Architecture Relevant Type 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. Adler, J. (2005). Reliabilist justification (or knowledge) as a good truth-ratio. Pacific Philosophical Quarterly, 86, 445–458.CrossRefGoogle Scholar
  2. Adler, J., & Levin, M. (2002). Is the generality problem too general? Philosophy and Phenomenological Research, 65(1), 87–97.CrossRefGoogle Scholar
  3. Alston, W. (1995). How to think about reliability. Philosophical Topics, 23(1), 1–29.Google Scholar
  4. Baumann, P. (2011). A puzzle about responsibility: A problem and its contextualist solution. Erkenntnis, 74(2), 207–224.CrossRefGoogle Scholar
  5. Beebe, J. R. (2004). The generality problem, statistical relevance and the tri-level hypothesis. Nous, 38(1), 177–195.CrossRefGoogle Scholar
  6. Bishop, M. A. (2010). Why the generality problem is everybody’s problem. Philosophical Studies, 151, 285–298.CrossRefGoogle Scholar
  7. Brandom, R. B. (1998). Insights and blindspots of reliabilism. The Monist, 81(3), 371–392.CrossRefGoogle Scholar
  8. Christensen, D. (2007). Three questions about Leplin’s reliabilism. Philosophical Studies, 134(1), 43–50.CrossRefGoogle Scholar
  9. Comesaña, J. (2006). A well-founded solution to the generality problem. Philosophical Studies, 129, 27–47.CrossRefGoogle Scholar
  10. Conee, E., & Feldman, R. (1998). The generality problem for reliabilism. Philosophical Studies, 89, 1–29.CrossRefGoogle Scholar
  11. Dupré, J. (1993). The disorder of things: Metaphysical foundations of the disunity of science. USA: Harvard University Press.Google Scholar
  12. Feldman, R. (1985). Reliability and justification. The Monist, 68, 159–174.CrossRefGoogle Scholar
  13. Feldman, R., & Conee, E. (2002). Typing problems. Philosophy and Phenomenological Research, 65(1), 98–105.CrossRefGoogle Scholar
  14. Goldman, A. I. (1979). What is justified belief? In G. Pappas (Ed.), Justification and knowledge. Dordrecht: D. Reidel.Google Scholar
  15. Goldman, A. I. (1986). Epistemology and cognition. Cambridge MA: Harvard University Press.Google Scholar
  16. Goldman, A. I. (2008). Reliabilism. In E. N. Zalta (Ed.), The Stanford encyclopedia of philosophy (Summer 2008 Edition) URL = <>.
  17. Heller, M. (1995). The simple solution to the problem of generality. Noûs, 29(4), 501–515.CrossRefGoogle Scholar
  18. Hetherington, S. C. (1996). Knowledge puzzles: An introduction to epistemology. Boulder: Westview.Google Scholar
  19. Kappel, K. (2006). A diagnosis and resolution to the generality problem. Philosophical Studies, 127, 525–560.CrossRefGoogle Scholar
  20. Lemos, N. (2007). An introduction to the theory of knowledge. New York: Cambridge University Press.CrossRefGoogle Scholar
  21. Leplin, J. (2007). In defense of reliabilism. Philosophical Studies, 134(1), 31–42.CrossRefGoogle Scholar
  22. Lycan, W. G. (1988). Judgment and justification. New York: Cambridge University Press.Google Scholar
  23. Marr, D. (1982). Vision. San Francisco: W. H. Freeman.Google Scholar
  24. Plantinga, A. (1993). Warrant: The current debate. Oxford: Oxford University Press.CrossRefGoogle Scholar
  25. Pollock, J. L. (1986). Contemporary theories of knowledge. Totowa: Rowman and Littlefield.Google Scholar
  26. Pollock, J. L., & Cruz, J. (1999). Contemporary theories of knowledge (2nd ed.). Lanham: Rowman and Littlefield.Google Scholar
  27. Ramsey, F. P. (1931). In R. B. Braithwaite (Ed.), The foundations of mathematics and other logical essays. London: Routledge and Kegan Paul.Google Scholar
  28. Salmon, W. C. (1971). Statistical Explanation. In W. C. Salmon, R. Jeffrey, & J. Greeno (Eds.), Statistical explanation and statistical relevance. Pittsburgh: University of Pittsburgh Press.Google Scholar
  29. Wunderlich, M. (2003). Vector reliability: A new approach to epistemic justification. Synthese, 136, 237–262.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2012

Authors and Affiliations

  1. 1.Department of PhilosophyUniversity of GenevaGenevaSwitzerland
  2. 2.Department of PhilosophyLund UniversityLundSweden

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