pp 1–18 | Cite as

Structural and indicator representations: a difference in degree, not kind

  • Gregory Nirshberg
  • Lawrence ShapiroEmail author


Some philosophers have offered structural representations as an alternative to indicator-based representations. Motivating these philosophers is the belief that an indication-based analysis of representation exhibits two fatal inadequacies from which structural representations are spared: such an analysis cannot account for the causal role of representational content and cannot explain how representational content can be made determinate. In fact, we argue, indicator and structural representations are on a par with respect to these two problems. This should not be surprising, we contend, given that the distinction between indicator and structural representations is better conceived as one involving degree rather than kind.


Structural representation Indication Disjunction problem Content determinacy 



Thanks to two very thorough referees for comments that greatly improved this paper. Thanks also go to Gerard O’Brien for useful discussion, and to Rob Rupert for comments on an earlier draft.


  1. Bechtel, W. (1998). Representations and cognitive explanations: Assessing the dynamicist challenge in cognitive science. Cognitive Science,22(3), 295–317.CrossRefGoogle Scholar
  2. Cummins, R. (1996). Representations, targets, and attitudes. Cambridge: MIT Press.Google Scholar
  3. Dennett, D. (1982). Styles of mental representation. Proceedings of the Aristotelian Society,83(213–226), 213–226.Google Scholar
  4. Dretske, F. (1988). Explaining Behavior. Cambridge: MIT Press.Google Scholar
  5. Dretske, F. (1994). The explanatory role of information. Philosophical Transactions: Physical Sciences and Engineering,349, 59–70.CrossRefGoogle Scholar
  6. Fodor, J. (1984). Semantics, wisconsin style. Synthese,59(3), 231–250.CrossRefGoogle Scholar
  7. Fodor, J. (1987). Psychosemantics. Cambridge: MIT Press.CrossRefGoogle Scholar
  8. Fodor, J. (1990). A theory of content and other essays. Cambridge, MA: MIT Press.Google Scholar
  9. Gładziejewski, P., & Miłkowski, M. (2017). Structural representations: Causally relevant and different from detectors. Biology and Philosophy,32(3), 337–355.CrossRefGoogle Scholar
  10. Hardwick, C. (Ed.). (1977). Semiotic and significs: The correspondence between Charles S. Peirce and Victoria Lady Welby. Bloomington: Indiana University Press.Google Scholar
  11. Isaac, A. M. C. (2013). Objective similarity and mental representation. Australasian Journal of Philosophy,91(4), 683–704.CrossRefGoogle Scholar
  12. Kosslyn, S. (1983). Ghosts in the mind’s machine. New York, NY: W.W. Norton.Google Scholar
  13. Morgan, A. (2014). Representations gone mental. Synthese,191(2), 213–244.CrossRefGoogle Scholar
  14. O’Brien, G. (2016). How does mind matter? Solving the content causation problem. In T. Metzinger (Ed.), Open MIND philosophy and the mind sciences in the 21st century (Vol. 2, pp. 1137–1150). Cambridge: MIT Press.Google Scholar
  15. Opie, J., & O’Brien, G. (2004). Notes toward a structuralist theory of mental representation. In H. Clapin, P. Staines, & P. Slezak (Eds.), Representation in mind: New approaches to mental representation. Amsterdam: Elsevier.Google Scholar
  16. Ramsey, W. (2007). Representation reconsidered. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
  17. Ramsey, W. (2016). Untangling two questions about mental representation. New Ideas in Psychology,40(A), 3–12.CrossRefGoogle Scholar
  18. Rupert, R. (2018). Representation and mental representation. Philosophical Explorations,21(2), 204–225.CrossRefGoogle Scholar
  19. Shea, N. (2014). Exploitable isomorphism and structural representation. Proceedings of the Aristotelian Society,114(2), 123–144.CrossRefGoogle Scholar
  20. Shea, N. (2018). Representation in cognitive science. Oxford: Oxford University Press.CrossRefGoogle Scholar
  21. Von Eckardt, B. (1993). What is cognitive science?. Cambridge: MIT Press.Google Scholar
  22. Woodward, J. (2003). Making things happen: A theory of causal explanation. Oxford: Oxford University Press.Google Scholar

Copyright information

© Springer Nature B.V. 2020

Authors and Affiliations

  1. 1.Department of PhilosophyUniversity of Wisconsin – MadisonMadisonUSA

Personalised recommendations