Abstract
Agent-based accounts of scientific representation all agree that the representational relationship is constituted by the actions of scientists. Despite this agreement, there are several differences in how agent-based accounts describe scientific representation. In this essay, I argue that these differences do not undercut the compatibility between the accounts. I make my argument by examining the nature of human agency and demonstrating that scientific, representational actions are multiply describable. I then argue that the differences between the accounts are valuable because they help to bring different parts of the representational practices of science into greater focus.
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Notes
Defenses of isomorphism or partial isomorphism are given by Van Fraassen (1980), French and Ladyman (1999), French (2003), Bartels (2006), Bueno and French (2011), among others; defenses of similarity are given by Giere (1988) and Weisberg (2013). For a response to the objections of Suárez (2003) and Frigg (2006), see Chakravartty (2010), Bueno and French (2011) and Toon (2012).
N. B. Suárez uses the term “source” where I use the term “vehicle”.
Of course, this is not to suggest that mental states play no role whatsoever, but rather that representation will not be reduced entirely to such a state. See Boesch (2017b).
Anscombe acknowledges that “there are a large number of X’s, in the imagined case, for which we can readily suppose that the answer to the question ‘Why are you X-ing?’ falls within the range” (Anscombe 2000, 38).
It is possible that the description of D is subject to the same features of multiple describability as I discuss it here, but I have decided to keep it the same in this case because Anscombe argues that there is a certain primacy or importance to the final description in a series, and so it may not be quite as interchangeable as others (Anscombe 2000, 46).
My rendering of the ‘Why?’ questions for Hughes’s account makes it such that the denotational action does not function directly in the means-end structuring, hence I begin with an answer about demonstration. Instead, the use of the model as a stand-in is implied by the other features. That is to say, by demonstrating features that hold of the model and showing how they can be interpreted to hold of the target, the agent is thereby using the model as a stand-in.
This paper has been substantively revised thanks to several helpful comments from Tarja Knuuttila, Mauricio Suárez, Michael Dickson, Jennifer Frey, and from two anonymous reviewers.
References
Ankeny, R., Chang, H., Boumans, M., & Boon, M. (2011). Introduction: Philosophy of science in practice. European Journal for Philosophy of Science, 1(3), 303. https://doi.org/10.1007/s13194-011-0036-4.
Anscombe, G. E. M. (2000). Intention (2nd ed.). Cambridge, MA: Harvard University Press.
Bailer-Jones, D. (2003). When scientific models represent. International Studies in the Philosophy of Science, 17(1), 59–74.
Bartels, A. (2006). Defending the structural concept of representation. Theoria, 21(1), 7–19.
Boesch, B. (2017a). The means-end account of scientific, representational actions. Synthese. https://doi.org/10.1007/s11229-017-1537-2.
Boesch, B. (2017b). There is a special problem of scientific representation. Philosophy of Science, 84(5), 970–981. https://doi.org/10.1086/693989.
Bueno, O., & French, S. (2011). How theories represent. The British Journal for the Philosophy of Science, 62(4), 857–894.
Callender, C., & Cohen, J. (2006). There is no special problem about scientific representation. Theoria, 21(1), 67–85.
Chakravartty, A. (2010). Informational versus functional theories of scientific representation. Synthese, 172(2), 197–213.
Contessa, G. (2007). Scientific representation, interpretation, and surrogative reasoning. Philosophy of Science, 74(1), 48–68.
Contessa, G. (2011). Scientific models and representation. In S. French & J. Saatsi (Eds.), The continuum companion to philosophy of science (pp. 120–137). New York: Bloomsbury.
Fang, W. (2018). An inferential account of model explanation. Philosophia. https://doi.org/10.1007/s11406-018-9958-9.
Foster, J. E. (1971). History and description of the Mississippi Basin Model. Vicksburg: U.S. Army Corp of Engineers Waterways Experiment Station.
French, S. (2003). A model-theoretic account of representation (or, I don’t know much about art…but I know it involves isomorphism). Philosophy of Science, 70(5), 1472–1483. https://doi.org/10.1086/377423.
French, S., & Ladyman, J. (1999). Reinflating the semantic approach. International Studies in the Philosophy of Science, 13(2), 103–121.
Frigg, R. (2006). Scientific representation and the semantic view of theories. Theoria, 21(1), 49–65.
Frigg, R., & Nguyen, J. (2016). The fiction view of models reloaded. The Monist, 99(3), 225–242.
Frigg, R., & Nguyen, J. (2017). Scientific representation is representation-as. In H.-K. Chao, & J. Reiss (Eds.), Philosophy of science in practice (pp. 149–179). Berlin: Springer. https://doi.org/10.1007/978-3-319-45532-7_9.
Frisch, M. (2015). Users, structures, and representation. British Journal for the Philosophy of Science, 66(2), 285–306. https://doi.org/10.1093/bjps/axt032.
Giere, R. N. (1988). Explaining science: A cognitive approach. Chicago: University of Chicago Press.
Giere, R. N. (2004). How models are used to represent reality. Philosophy of Science, 71(5), 742–752.
Giere, R. N. (2010). An agent-based conception of models and scientific representation. Synthese, 172(2), 269–281.
Hughes, R. I. G. (1997). Models and representation. Philosophy of Science, 64(Supplement), S325–S336.
Humphreys, P. (2004). Extending ourselves: Computational science, empiricism, and scientific method. Oxford: Oxford University Press.
Knuuttila, T. (2005). Models, representation, and mediation. Philosophy of Science, 72(5), 1260–1271. https://doi.org/10.1086/508124.
Knuuttila, T. (2011). Modelling and representing: An artefactual approach to model-based representation. Studies in History and Philosophy of Science Part A, 42(2), 262–271. https://doi.org/10.1016/j.shpsa.2010.11.034.
Knuuttila, T., & García Deister, V. (2018). Modelling gene regulation: (De)compositional and template-based strategies. Studies in History and Philosophy of Science Part A. https://doi.org/10.1016/j.shpsa.2017.11.002.
Knuuttila, T., & Loettgers, A. (2012). The productive tension: Mechanisms vs. templates in modeling the phenomena. In P. Humphreys, & C. Imbert (Eds.), Representations, models, and simulations (pp. 3–24). London: Routledge.
Mäki, U. (2009). Missing the world. Models as isolations and credible surrogate systems. Erkenntnis (1975-), 70(1), 29–43.
Mississippi Basin Model Board. (1945). Report of first meeting of Mississippi Basin Model Board. Mississippi Basin Model report 2-1. Mississippi Basin Model Board.
Suárez, M. (2003). Scientific representation: Against similarity and isomorphism. International Studies in the Philosophy of Science, 17(3), 225–244. https://doi.org/10.1080/0269859032000169442.
Suárez, M. (2004). An inferential conception of scientific representation. Philosophy of Science, 71(5), 767–779. https://doi.org/10.1086/421415.
Suárez, M. (2010). Scientific representation. Philosophy Compass, 5(1), 91–101.
Suárez, M. (2015). Deflationary representation, inference, and practice. Studies in History and Philosophy of Science Part A, 49, 36–47. https://doi.org/10.1016/j.shpsa.2014.11.001.
Teller, P. (2001). Twilight of the perfect model model. Erkenntnis (1975-), 55(3), 393–415.
Toon, A. (2012). Similarity and scientific representation. International Studies in the Philosophy of Science, 26(3), 241–257.
Van Fraassen, B. C. (1980). The scientific image. New York: Oxford University Press.
Van Fraassen, B. C. (2008). Scientific representation: Paradoxes of perspective. Oxford: Oxford University Press.
Weisberg, M. (2013). Simulation and similarity: Using models to understand the world. New York: Oxford University Press.
Acknowledgements
I am grateful to Tarja Knuuttila, Michael Dickson, Mauricio Suárez, Jennifer Frey, and two anonymous reviewers for helpful comments. I am grateful for helpful comments from audiences at the Three Rivers Philosophy Conference in 2015 and the South Carolina Society for Philosophy Conference in 2015, where earlier versions of this paper were presented.
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Boesch, B. Resolving and Understanding Differences Between Agent-Based Accounts of Scientific Representation. J Gen Philos Sci 50, 195–213 (2019). https://doi.org/10.1007/s10838-019-09442-0
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DOI: https://doi.org/10.1007/s10838-019-09442-0