- 수업명: <과학철학과제연구: 증거>
- 서울대 과학사 및 과학철학 협동과정 대학원
- 2020년 1학기
- 담당교수: 천현득
■ 수업 개요 및 목표
• 이번 학기 “과학철학과제연구” 수업은 과학적 증거의 철학을 주제로 한다.
• 과학은 세계에 관한 주장을 제시하고 이를 경험적 증거를 통해 뒷받침한다. 이 수업에서는 이론이나 가설이 증거와 맺는 관계에 관한 과학철학의 문헌들을 비판적으로 검토한다. 증거라는 개념은 어떻게 사용되는지, 무엇이 증거가 될 수 있는지, 증거가 결정하는 이론 선택에서 미결정적일 수 있는지, 증거는 확률을 통해 가장 잘 포착될 수 있는지, 오래된 증거가 이론을 입증하는 증거가 될 수 있는지, 새로운 현상을 성공적으로 예측한 경우에 이미 확립된 증거보다 이론을 더 강하게 지지하는지, 증거기반 의학에서 증거란 무엇인지 등을 다룬다.
• 이를 위해 확률에 관한 기본적인 개념과 연산법을 학습할 것이지만, 확률과 통계에 대한 선행 지식을 전제로 하지는 않을 것이다.
■ 교재
• [H] Hacking, I. (2001), An Introduction to Probability and Inductive Logic. Cambridge UP.
• [S] Strevens, M., Notes on Bayesian Confirmation Theory. (2017 version)
[ www.nyu.edu/classes/strevens/BCT/BCT.pdf ]
• [CCP] Curd, M., A. Cover, and C. Pincock (eds.) (2013), Philosophy of Science: The Central Issues (2nd Edition), Norton.
■ 참고문헌
• 주 교재는 없고, 필요한 문헌들은 게시판 등을 통해 배부한다. 아래는 참고문헌들이다.
• Achinstein, P. (2001), The Book of Evidence, Oxford: Oxford University Press.
• Earman, J. (1992), Bayes or Bust? A Critical Examination of Bayesian Confirmation Theory, Cambridge, MA: MIT Press.
• Earman, J. and W. Salmon (1992), “Chapter 2. Confirmation of Scientific Hypotheses”, in M. Salmon et al. (eds.), Introduction to the Philosophy of Science, NJ: Prentice Hall.
• Howson, C. & Urbach, P. (1989), Scientific Reasoning: The Bayesian Approach, LaSalle, Ill.: Open Court.
• Skyrms, B. (2000), Choice and Chance: An Introduction to Inductive Logic. 4th ed. Belmont, CA: Wadsworth Thomson Learning.
• Sprenger, J. and Hartmann, S., Bayesian Philosophy of Science, Oxford University Press.
■ 성적 평가: 참여도, 발제 및 토론, 기말논문
• 1) 모든 수강생은 매 수업에 성실하게 참여할 것이 요구된다. 주어진 문헌을 미리 읽어오고 수업 중 토론에 참여한다.
• 2) 발제자는 핵심 내용을 (논증적으로 재구성하는 방식으로) 요약하고, 함께 토론할만한 주제를 소개한다. 발제문은 수업시간 24시간 전까지 제출한다.(게시판 이용) 발제 횟수는 수강생의 수에 따라 달라질 수 있다.
• 3) 기말논문은 6월 25일(목요일)까지 제출하고, 기한 내 제출된 논문은 간략한 논평과 함께 반환한다. 기한을 넘겨 제출하는 경우 늦은 만큼 감점될 수 있고 논평을 받지 못할 수 있다.
■ Schedule and Readings (아래 일정은 잠정적이며, 각 주의 읽기 자료도 변경될 수 있다.)
Week 1 (03/19) - Introduction
• Achinstein, P. (2001) The Book of Evidence, Oxford: Oxford University Press, pp. 13-44.
• Kelly, T. “Evidence”, The Stanford Encyclopedia of Philosophy, Edward N. Zalta (ed.), URL = < https://plato.stanford.edu/archives/win2016/entries/evidence/ >.
• [opt] Reiss, Julian (2011) “Empirical Evidence: Its Nature and Sources”, Handbook of Philosophy of Social Science (ed. by Ian Jarvie and Jesús Zamora Bonilla), SAGE, 551-76.
Week 2 (03/26) - Hypothetico-deductivism and the paradox of confirmation
• Earman, J. and W. Salmon (1992), “Confirmation of Scientific Hypotheses”, Sect. 2.1~2.4 (pp.43-55).
• Hempel, C.G. (1965), “Studies in the logic of confirmation”, Aspects of Scientific Explanation, New York: The Free Press, pp. 3-51. (sect.1-5 & 7-8)
• Earman, J. (1992), Bayes or Bust, Cambridge: MIT Press, pp. 63-73 (§§3.1-3.3)
• [opt] Hempel, C.G. (1962) “Criteria of Confirmation and Acceptability”, reprinted in [CCP]
• [opt] Glymour, C. (1972), “Relevant evidence”, Journal of Philosophy 72, 403-426.
Week 3 (04/02) - Data and Phenomena
• Bogen, J. and J. Woodward (1988), “Saving the phenomena”, The Philosophical Review 97(3): 303-352.
• McAlister, James, W. (1997), “Phenomena and Patterns in Data Sets”, Erkenntnis 47(2): 217-228.
• [opt] Votsis, I. (2011), “Data Meet Theories: Up Close and Inferentially Personal.” Synthese 182: 89-100.
• [opt] Massimi, M. (2011), “From data to phenomena: a Kantian stance.” Synthese 182: 101-116.
• [opt] Woodward, J. (2011), “Data and phenomena: a restatement and defense.” Synthese 182: 165-179.
Week 4 (04/09) - Probability calculus
• Earman, J. and W. Salmon (1992), “Confirmation of Scientific Hypotheses”, Sect. 2.7~2.8.
• Strevens, Chapter 1-3. [S]
• Hacking, Chapter 2-7. (pp. 11-78) [H]
Week 5 (04/16) - Bayesianism: How it works
• Earman, J. and W. Salmon (1992), “Confirmation of Scientific Hypotheses”, Sect. 2.9-2.10 (pp. 89-99)
• Hacking, Chapter 13-15. [H]
• Strevens, Chapter 4-6, and 8. (for induction: Ch. 7) [S]
• [opt] Hacking, Chapter 11-12.
• [opt] Hájek, Alan, “Interpretations of Probability”, The Stanford Encyclopedia of Philosophy (Fall 2019 Edition), Edward N. Zalta (ed.)
Week 6 (04/23) - Problem of Underdetermination
• Gillies, D. “The Duhem Thesis and the Quine Thesis”, reprinted in [CCP, 271-287]
• Laudan, L. (1990), “Demystifying Underdetermination.” in C. W. Savage (ed.), Scientific Theories, University of Minnesota Press. reprinted in [CCP, 288-320]
• Norton, J. (2008), “Must Evidence Underdetermine Theory?”, in M. Carrier, D. Howard, and J. Kourany (eds.), The Challenge of the Social and the Pressure of Practice: Science and Values Revisited, Pittsburgh: University of Pittsburgh Press, pp. 17–44.
Week 7 (04/30) Bayes and Underdetermination
• Strevens, Chapter 10. [S]
• Dorling Jon (1979) “Bayesian personalism, the methodology of scientific research programmes, and Duhem’s problem”, Studies in the History and Philosophy of Science 10: 177-187.
• Earman, J. (1992), Bayes or Bust, Cambridge: MIT Press, pp. 83-85 (§3.7).
• Howson, C. and P. Urbach, Scientific Reasoning, 103-114 (§4.e “The Duhem Problem”); reprinted in [CCP]
Week 8 (05/07) - The Problem of Old Evidence
• Strevens, Chapter 11. [S]
• Glymour, C. (1980), “Why I am not a Bayesian”, Theory and Evidence, Ch. 3 (esp., 85-93)
• Howson, C. (1991) “The “Old Evidence” Problem.”, British Journal for the Philosophy of Science 42: 547-555.
• Barnes, E. C. (1999) “The Quantitative Problem of Old Evidence.” British Journal for the Philosophy of Science 50: 249-264.
• Eells, E. & B. Fitelson (2000) “Measuring Confirmation and Evidence.” Journal of Philosophy 97: 663-672.
• [opt] Earman, J. (1992) Bayes or Bust?, Cambridge: The MIT Press, Chapter 5.
Week 9 (05/14) - Tom Bayes and Tom Kuhn
• Salmon, W. (1990), “Rationality and objectivity in science, or Tom Kuhn meets Tom Bayes,” in C. W. Savage (ed.), Scientific Theories, University of Minnesota Press. reprinted in [CCP, 518-549]
• Earman, J. (1992) Bayes or Bust?, Cambridge: MIT Press. Chapter. 8
• Farmakis, L. (2008). “Did Tom Kuhn actually Meet Tom Bayes?”, Erkenntnis 68(1), 41-53.
Week 10 (05/21) - Accommodation vs. Prediction
• Maher, P. (1988), “Prediction, Accommodation, and the Logic of Discovery”, PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association 1988, 1: 273–285.
• Brush, S. G. (1989) “Prediction and Theory Evaluation: The Case of Light Bending”, Science, 246(4934): 1124–1129.
• Howson, C. and A. Franklin (1991) “Maher, Mendeleev and Bayesianism”, Philosophy of Science, 58(4): 574–585.
• Mayo, D. (1991) “Novel Evidence and Severe Tests”, Philosophy of Science 58: 523-552.
o Or, Mayo, D. (1996). Error and the Growth of Experimental Knowledge, U Chicago Press, Chapter 9.
• Hudson, R. G. (2007) ‘What’s Really at Issue with Novel Predictions?’, Synthese 155(1): 1-20.
• Hitchcock, C., and Sober, E. (2004). “Prediction Versus Accommodation and the Risk of Overfitting”, The British Journal for the Philosophy of Science, 55(1), 1-34.
Week 11 (05/28) - Simulations and Modelling
• Evelyn Fox Keller (2003), “Models, simulation, and ‘computer experiments’”, in Hans Radder (ed.), The Philosophy of Scientific Experimentation, Pittsburgh, pp. 198-215.
• Mary S Morgan (2003), “Experiments without material intervention”, in Hans Radder (ed.), The Philosophy of Scientific Experimentation, Pittsburgh, pp. 216-235.
• Wendy S Parker (2009), “Does matter really matter? Computer simulations, experiments, and materiality”, Synthese 169: 483-496.
Week 12 (06/04) - Evidence in evidence-based medicine
• Worrall, J. (2002), “What Evidence in Evidence-Based Medicine?”, Philosophy of Science 69: 316-30.
• Worrall, J. (2007), ‘Evidence in Medicine and Evidence-Based Medicine’, Philosophy Compass, vol. 2(6): 981–1022.
• Sackett, D.L. et. al. (1996), “Evidence Based Medicine: What it is and What it isn’t”, British Medical Journal, vol. 312: 71-72.
o Atkins D, Best D, Briss PA, Eccles M, Falck-Ytter Y, Flottorp S, et al. (2004) “Grading quality of evidence and strength of recommendations.” BMJ 2004 Jun 19; 328(7454): 1490.
o Straus SE, Jones G. (2004). “What has evidence-based medicine done for us?”, BMJ 2004 Oct 30; 329(7473): 987-8.
o Guyatt G, Cook D, Haynes B. (2004), “Evidence based medicine has come a long way.” BMJ 2004 Oct 30; 329(7473): 990-1.
o Reilly BM. (2004), “The essence of EBM.” BMJ 2004 Oct 30; 329(7473): 991-2.
• Ashcroft, R. E. (2004) ‘Current Epistemological Problems in EBM’, Journal of Medical Ethics, 30(2), 131-135.
Week 13 (06/11) - RCT, the gold standard?
• Nancy Cartwright, “Are RCTs the gold standard?”, BioSocieties 2 (2007): 11-20.
o Upshur, R. E. G. (2005) ‘Looking for Rules in a World of Exceptions: reflections on evidence-based practices’, Perspectives in Biology and Medicine, 48(4), 477-489.
o Grossman, J. and F.J. Mackenzie (2005) ‘The Randomized Controlled Trial. Gold Standard or Merely Standard?’, Perspectives in Biology and Medicine, vol. 48(4): 516-534.
• Howich, Philosophy of EBM, Ch 11.
• Solomon, M. 2011. “Just a Paradigm: Evidence Based medicine in epistemological context”, European Journal for Philosophy of Science 1: 451-466.
Week 14 (06/18) - Proposal Presentation (or Replication Crisis)
• Ioannidis, J. (2005). “Why Most Published Research Findings Are False.” PLoS Medicine 2(8), e124.
( https://dx.doi.org/10.1371/journal.pmed.0020124 )
• Romero, F. (2016). “Can the behavioral sciences self-correct? A social epistemic study.” Studies in History and Philosophy of Science 60: 55-69.
• Leonelli, S. (2018), “Rethinking Reproducibility as a Criterion for Research Quality” (preprint)
• Feest, U. (2019). “Why Replication is Overrated.” Philosophy of Science 86: 895-905.
(2020.03.17.)
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