Advertisement

Philosophical Studies

, Volume 172, Issue 12, pp 3273–3292 | Cite as

What is a philosophical effect? Models of data in experimental philosophy

  • Bryce HuebnerEmail author
Article

Abstract

Papers in experimental philosophy rarely offer an account of what it would take to reveal a philosophically significant effect. In part, this is because experimental philosophers tend to pay insufficient attention to the hierarchy of models that would be required to justify interpretations of their data; as a result, some of their most exciting claims fail as explanations. But this does not impugn experimental philosophy. My aim is to show that experimental philosophy could be made more successful by developing, articulating, and advancing plausible models of the data that are collected and the analyses that are employed.

Keywords

Experimental philosophy Models of data Likert scales 

Notes

Acknowledgments

Eric Winsberg and Rebecca Kukla helped me see that the relationship between models of data and scientific explanation was relevant to experimental philosophy. I received helpful feedback on an early version of this paper from Rik Hine and an audience at the Southern Society for Philosophy and Psychology (Austin, 2013). Ruth Kramer, James Mattingly, and J. Brendan Ritchie read drafts of this paper, and offered comments that made the arguments stronger than they otherwise would have been. Finally, I would like to thank all of the anonymous reviewers of this paper; I appreciated the time they took to offer comments, even where I disagreed with them.

References

  1. Amit, E., & Greene, J. (2012). You see, the ends don’t justify the means. Psychological Science, 23(8), 861–868.CrossRefGoogle Scholar
  2. Bogen, J., & Woodward, J. (1998). Saving the phenomena. The Philosophical Review, 97(3), 303–352.CrossRefGoogle Scholar
  3. Buckwalter, W. & M. Phelan (2013). Function and feeling machines. Philosophical Studies, 166(2), 349–361. Online supplementary material http://goo.gl/D27JTg. Accessed 1 March 2015.
  4. Chambers, C. (2012). The dirty dozen: A wish list for psychology and cognitive neuroscience. http://goo.gl/XluVRQ, Accessed 31 January 2014.
  5. Chambers, C. et al (2013). Trust in science would be improved by study pre-registration. The Guardian. http://goo.gl/L1Hzck. Accessed 31 January 2014.
  6. Crockett, M. (2014). Behind the scenes of a ‘shocking’ new study on human altruism. The Guardian. http://gu.com/p/43gpm/stw Accessed 2 December 2014.
  7. Crockett, M., Kurth-Nelsona, Z., Siegela, J., Dayan, P., & Dolan, R. (2014). Harm to others outweighs harm to self in moral decision making. PNAS, 111(48), 17320–17325.CrossRefGoogle Scholar
  8. Cummins, R., Roth, M., & Harmon, I. (2014). Why it doesn’t matter to metaphysics what Mary learns. Philosophical Studies, 167(3), 541–555.CrossRefGoogle Scholar
  9. Haugeland, J. (1991). Representational genera. In W. Ramsey, S. Stich, & D. Rumelhart (Eds.), Philosophy and connectionist theory (pp. 61–89). Hillsdale: Lawrence Erlbaum Associates.Google Scholar
  10. Nuzzo, R. (2014). Scientific method: Statistical errors. Nature, 506, 150–152.CrossRefGoogle Scholar
  11. Rosenthal, D. (2011). Mental quality, valence, and intuition: Comments on Edouard Machery. https://wfs.gc.cuny.edu/DRosenthal/www/DR-MERG.pdf.
  12. Schulz, E., Cokely, E. T., & Feltz, A. (2011). Persistent bias in expert judgments about free will and moral responsibility. Consciousness and Cognition, 20(4), 1722–1731.CrossRefGoogle Scholar
  13. Shanahan, K. (2002). A systematic error in mass flow calorimetery demonstrated. Thermochimica Acta, 382(2), 95–100.CrossRefGoogle Scholar
  14. Suppes, P. (1962). Models of data. In E. Nagel, P. Suppes, & A. Tarski (Eds.), Logic, methodology and philosophy of science (pp. 252–261). Stanford: Stanford University Press.Google Scholar
  15. Wimsatt, W. (1974). Complexity and organization. In K. Schaffner, & R. Cohen (Eds.), Boston studies in the philosophy of science (Vol. 20, pp. 67–86). Dordrecht: Reidel.Google Scholar
  16. Wimsatt, W. (2007). Re-engineering philosophy for limited beings: Piecewise approximations to reality. Cambridge: Harvard University Press.Google Scholar
  17. Winsberg, E., Huebner, B., & Kukla, R. (in press). Accountability, values, and social modeling in radically collaborative research. Studies in the history and philosophy of science, 46, 16–23.Google Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2015

Authors and Affiliations

  1. 1.Department of PhilosophyGeorgetown UniversityWashingtonUSA

Personalised recommendations