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Sleeping Beauty Goes to the Lab: The Psychology of Self-Locating Evidence

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Abstract

Analyses of the Sleeping Beauty Problem are polarised between those advocating the “1/2 view” (“halfers”) and those endorsing the “1/3 view” (“thirders”). The disagreement concerns the evidential relevance of self-locating information. Unlike halfers, thirders regard self-locating information as evidentially relevant in the Sleeping Beauty Problem. In the present study, we systematically manipulate the kind of information available in different formulations of the Sleeping Beauty Problem. Our findings indicate that patterns of judgment on different formulations of the Sleeping Beauty Problem do not fit either the “1/2 view” or the “1/3 view.” Human reasoners tend to acknowledge self-locating evidence as relevant, but discount its weight significantly. Accordingly, self-locating information may trigger more cautious judgments of confirmation than familiar kinds of statistical evidence. We also discuss how these results can advance the debate by providing a more nuanced and empirically grounded account or explication of the evidential impact of self-locating information.

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Notes

  1. Here we have to acknowledge very helpful remarks from two reviewers.

  2. Once properly specified, this hypothesis might find support from further investigation within our experimental paradigm. One could, in particular, consider how probability judgments differ in our Basic vs. Plus version (and/or some modification thereof) and make a quantitative comparison with the variation in the Plus vs. Marble version. Notice, however, that responses would have to lie on an interval scale for making this comparison. Given our elicitation procedure (with a 7-point scale), we deemed appropriate not to rely on this assumption in our analyses of data. (We thank the editor for raising this point.)

  3. In fact, our notion of explicationism allows for significant nuances. Carnap (1950, p. 3) characterizes the task of explication as that of “transforming a given more or less inexact concept into an exact one, or, rather, in replacing the first by the second.” According to Carnap (1950, p. 7), an adequate explicatum should be similar to the explicandum in respecting prior usage — though “close similarity is not required” and “considerable differences are permitted.” It should be more exact than the explicandum. It should be fruitful in the sense of being “useful for the formulation of [...] empirical laws [or] logical theorems.” And last, the explicatum should be simple. Given its emphasis on the requirement of fruitfulness, Carnapian explication can be aptly described as aiming at “concept engineering” (Kitcher 2008). Kemeny & Oppenheim (1952, p. 308), on the other hand, distinguished their project from Carnap’s in these terms: “The commonest procedure of explication is to apply a trial and error method till one arrives at an ingenious guess, and then try to find intuitive reasons to justify the proposed explicatum. This procedure is clearly very dangerous: The intuition of the most honest and well-trained philosopher is likely at times to become a tool for grinding an axe. […] We feel that we must first put down clearly all that our intuition tells us about the explicandum, and then find the precise definitions that satisfy our intuitive requirements.” Given a stronger emphasis on the requirement of similarity, the goal of Oppenheimian explication is more one of concept clarification instead of concept engineering.

  4. We thank an anonymous reviewer for prompting this clarification.

References

  • Arntzenius, F. 2002. Reflections on sleeping beauty. Analysis 62 (1): 53–62.

    Article  Google Scholar 

  • Bostrom, N. 2007. Sleeping beauty and self-location: A hybrid model. Synthese 157 (1): 59–78.

    Article  Google Scholar 

  • Bradley, D. 2012. Four problems about self-locating belief. Philosophical Review 121: 149–177.

    Article  Google Scholar 

  • Brössel, P. 2013. The problem of measure sensitivity redux. Philosophy of Science 80: 378–397.

    Article  Google Scholar 

  • Carnap, R. 1950. Logical foundations of probability. Chicago: University of Chicago Press.

    Google Scholar 

  • Cisewski, J., J.B. Kadane, M.J. Schervish, T. Seidenfeld, and R. Stern. 2016. Sleeping Beauty’s credences. Philosophy of Science 83: 324–347.

    Article  Google Scholar 

  • Clotfelter, C., and P.J. Cook. 1993. The ‘gambler's fallacy’ in lottery play. Management Science 39: 1521–1525.

    Article  Google Scholar 

  • Colombo, M. 2017. Experimental philosophy of explanation rising: The case for a plurality of concepts of explanation. Cognitive Science 41 (2): 503–517.

    Article  Google Scholar 

  • Cozic, M. 2011. Imaging and sleeping beauty: A case for double-halfers. International Journal of Approximate Reasoning. 52: 137–143.

    Article  Google Scholar 

  • Crupi, V., and K. Tentori. 2014. Measuring information and confirmation. Studies in the History and Philosophy of Science 47: 81–90.

    Article  Google Scholar 

  • Crupi, V., N. Chater, and K. Tentori. 2013. New axioms for probability and likelihood ratio measures. British Journal for the Philosophy of Science 64: 189–204.

    Article  Google Scholar 

  • Dorr, C. 2002. Sleeping beauty: In defense of Elga. Analysis 62: 292–296.

    Article  Google Scholar 

  • Draper, K. 2013. The evidential relevance of self-locating information. Philosophical Studies 166 (1): 185–202.

    Article  Google Scholar 

  • Edwards, W. 1968. Conservatism in human information processing. In Formal representation of human judgment, ed. B. Kleinmuntz, 17–52. New York: Wiley.

    Google Scholar 

  • Elga, A. 2000. Self-locating belief and the sleeping beauty problem. Analysis 60 (2): 143–147.

    Article  Google Scholar 

  • Festa, R., and G. Cevolani. 2017. Unfolding the grammar of Bayesian confirmation: Likelihood and anti-likelihood principles. Philosophy of Science 84: 56–81.

    Article  Google Scholar 

  • Fischoff, B., and R. Beyth-Marom. 1983. Hypothesis evaluation from a Bayesian perspective. Psychological Review 90 (3): 239–260.

    Article  Google Scholar 

  • Fitelson, B. 1999. The plurality of Bayesian measures of confirmation and the problem of measure sensitivity. Philosophy of Science 66: S362–S378.

    Article  Google Scholar 

  • Granberg D. (1996). The Monty hall problem: To switch or not to switch. In M. vos Savant, The Power of Logical Thinking (pp. 169–196). St. Martin’s Press, New York.

  • Hawley, P. 2013. Inertia, optimisim, and beauty. Noûs 47 (1): 85–103.

    Article  Google Scholar 

  • Hoffrage, U., S. Lindsey, R. Hertwig, and G. Gigerenzer. 2000. Communicating statistical information. Science 290 (5500): 2261–2262.

    Article  Google Scholar 

  • Horgan, T. 2004. Sleeping beauty awakened: New odds at the dawn of the new day. Analysis 64: 10–21.

    Article  Google Scholar 

  • Kemeny, J.G., and P. Oppenheim. 1952. Degree of factual support. Philosophy of Science 19: 307–324.

    Article  Google Scholar 

  • Kitcher, P. 2008. Carnap and the caterpillar. Philosophical Topics 36: 111–127.

    Article  Google Scholar 

  • Krauss, S., and X.T. Wang. 2003. The psychology of the Monty hall problem: Discovering psychological mechanisms for solving a tenacious brain teaser. Journal of Experimental Psychology: General 132 (1): 3–22.

    Article  Google Scholar 

  • Lewis, D. 2001. Sleeping beauty: Reply to Elga. Analysis 61 (3): 171–176.

    Article  Google Scholar 

  • Meacham, C. 2008. Sleeping beauty and the dynamics of de se belief. Philosophical Studies 138 (2): 245–269.

    Article  Google Scholar 

  • Phillips, L.D., and W. Edwards. 1966. Conservatism in a simple probability inference task. Journal of Experimental Psychology 72: 346–354.

    Article  Google Scholar 

  • Piccione, M., and A. Rubinstein. 1997. On the interpretation of decision problems with imperfect recall. Games and Economic Behavior 20 (1): 3–24.

    Article  Google Scholar 

  • Pighin S., K. Tentori, and V. Girotto. 2017. Another chance for good reasoning. Psychonomic Bulletin & Review 24: 1995–2002.

  • Ross, J. 2010. Sleeping beauty, countable additivity, and rational dilemmas. Philosophical Review 119 (4): 411–447.

    Article  Google Scholar 

  • Schupbach, J.N. 2017. Experimental explication. Philosophy and Phenomenological Research 94: 672–710.

    Article  Google Scholar 

  • Shepherd, J., and J. Justus. 2015. X-phi and Carnapian explication. Erkenntnis 80: 381–402.

    Article  Google Scholar 

  • Slovic, P., and S. Lichtenstein. 1971. Comparison of Bayesian and regression approaches to the study of information processing in judgement. Organizational Behavior & Human Processes 6: 649–744.

    Article  Google Scholar 

  • Tentori, K., V. Crupi, and D. Osherson. 2007. Determinants of confirmation. Psychonomic Bulletin & Review 14: 877–883.

    Article  Google Scholar 

  • Tentori, K., V. Crupi, and D. Osherson. 2010. Second-order probability affects hypothesis confirmation. Psychonomic Bulletin & Review 17: 129–134.

    Article  Google Scholar 

  • Terrell, D. 1994. A test of the gambler’s fallacy: Evidence from pari-mutuel games. Journal of Risk and Uncertainty 8: 309–317.

    Article  Google Scholar 

  • Terrell, D. 1998. Biases in assessments of probabilities: New evidence from greyhound races. Journal of Risk and Uncertainty 17: 151–166.

    Article  Google Scholar 

  • Titelbaum, M.G. 2008. The relevance of self-locating beliefs. Philsophical Review 117: 555–605.

    Article  Google Scholar 

  • Titelbaum, M.G. 2013. Ten reasons to care about the sleeping beauty problem. Philosophy Compass 8 (11): 1003–1017.

    Article  Google Scholar 

  • Weintraub, R. 2004. Sleeping beauty: A simple solution. Analysis 64 (1): 8–10.

    Article  Google Scholar 

  • White, R. 2006. The generalized sleeping beauty problem: A challenge for thirders. Analysis 66 (290): 114–119.

    Article  Google Scholar 

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Acknowledgments

Work on this project was supported by the Deutsche Forschungsgemeinshaft (DFG) as part of the priority program New Frameworks of Rationality (SPP 1516).

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Authors and Affiliations

  1. Tilburg Center for Logic, Ethics, and Philosophy of Science, Tilburg University, Tilburg, Netherlands

    Matteo Colombo & Jun Lai

  2. Center for Logic, Language, and Cognition, University of Turin, Turin, Italy

    Vincenzo Crupi

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  1. Matteo Colombo
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  2. Jun Lai
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  3. Vincenzo Crupi
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Correspondence to Vincenzo Crupi.

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Colombo, M., Lai, J. & Crupi, V. Sleeping Beauty Goes to the Lab: The Psychology of Self-Locating Evidence. Rev.Phil.Psych. 10, 173–185 (2019). https://doi.org/10.1007/s13164-018-0381-8

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