엄격한 시험과 증거-가설 생성의 메커니즘

Severe Tests and Mechanisms Generating an Evidence-Hypothesis

  • 투고 : 2020.05.16
  • 심사 : 2020.06.24
  • 발행 : 2020.06.30

초록

어느 가설에 대해 동일한 증거라 할지라도 그 증거가 어떤 방식으로 얻어진 것인가에 따라 분명 해당 가설에 대한 지지의 정도가 다른 것으로 보인다. 이러한 점에서 증거를 얻는 절차에 관한 메이요의 '엄격한 시험' 개념과 그에 대한 기법의 개발은 주목할 만하다. 그럼에도 불구하고 그에 대한 비판들이 여러 측면에서 제기되었는데, 여기서는 그 가운데 특별히 정동욱 (2018)과 Iseda (1999)에서 제기된 비판에 초점을 맞춰, 메이요를 대신해 그에 답해 보기로 한다. 이를 위해 본 논문에서는 특히 '증거-가설의 메커니즘'이라는 새로운 개념이 제안된다. 이 과정에서 또한 메이요 자신의 잘못에 대해서도 지적하게 될 것이다.

It seems certain that even if the same evidence is in itself given for any hypotheses, the way how it is obtained makes some differences in its support degree of them. In this respect, it is worth paying our attention to Mayo's conception of "severe test" and her technical development of it, which are just concerned with the procedures of getting evidence. Nonetheless, there have been criticisms against her theory from various respects. Among them, here this paper focuses on those especially raised by Jung (2018) and Iseda (1999). And it attempts to defend Mayo's theory on behalf of her against their critiques. For this purpose, the paper also proposes particularly a new concept of what is called the "mechanism generating an evidence-hypothesis". On the way, Mayo's own faults are revealed as well.

키워드

참고문헌

  1. 전영삼 (2018), "우도와 증거-가설 생성의 메커니즘", 과학철학 21권 2호, pp. 1-45.
  2. 정동욱 (2018), "반사실적 베이즈주의 증거 이론", 서울대학교 대학원 협동과정 과학사 및 과학철학 전공 이학박사학위논문.
  3. Fitelson, B. (2006), "Logical Foundations of Evidential Support", Philosophy of Science 73, pp. 500-512. https://doi.org/10.1086/518320
  4. Giere, R. N. (1983), "Testing Theoretical Hypotheses", in J. Earman (ed.), Testing Scientific Theories, Minnesota Studies in the Philosophy of Science, Vol. X, Minneapolis: Univ. of Minnesota Press, pp. 269-298.
  5. Iseda, T. (1999), "Use-Novelty, Severity, and a Systematic Neglect of Relevant Alternatives", Philosophy of Science 66 (Proceedings), pp. S403-413. https://doi.org/10.1086/392741
  6. Mayo, D. G. (1996), Error and the Growth of Experimental Knowledge, Chicago: The Univ. of Chicago Press.
  7. Mayo, D. G. (2005), "Evidence as Passing Severe Tests: Highly Probable versus Highly Probed Hypotheses", in P. Achinstein (ed.), Scientific Evidence: Philosophical Theories & Applications, Baltimore: The Johns Hopkins Univ. Press, pp. 95-127.
  8. Mayo, D. G. (2010), "An Ad Hoc Save of a Theory of Adhocness?: Exchanges with John Worrall", in D. G. Mayo & A. Spanos (eds.), Error and Inference: Recent's Exchanges on Experimental Reasoning, Reliability, and the Objectivity and Rationality of Science, Cambridge: Cambridge Univ. Press. pp. 155-169.
  9. Mayo, D. G. (2014), "Some surprising facts about (the problem of) surprising facts (from the Dusseldorf Conference, February 2011)", Studies in History and Philosophy of Science 45, pp. 79-86. https://doi.org/10.1016/j.shpsa.2013.10.005
  10. Mayo, D. G. (2018), Statistical Inference as Severe Testing: How to Get Beyond the Statistical Wars, Cambridge: Cambridge Univ. Press.
  11. Steel, D. (2007), "Bayesian Confirmation Theory and the Likelihood Principle", Synthese 156, pp. 53-77. https://doi.org/10.1007/s11229-005-3492-6
  12. Worrall, J. (2010), "Error, Tests, and Theory Confirmation", in D. G. Mayo & A. Spanos (eds.), Error and Inference: Recent's Exchanges on Experimental Reasoning, Reliability, and the Objectivity and Rationality of Science, Cambridge: Cambridge Univ. Press, pp. 125-154.