Skip to main content Accessibility help
×
  • Cited by 28
    • Show more authors
    • Open Access
      You have digital access to this book
    • Select format
    • Publisher:
      Cambridge University Press
      Publication date:
      10 August 2022
      01 September 2022
      ISBN:
      9781009003575
      9781009009157
      Creative Commons:
      Creative Common License - CC Creative Common License - BY Creative Common License - NC Creative Common License - ND
      This content is Open Access and distributed under the terms of the Creative Commons Attribution licence CC-BY-NC-ND 4.0.
      https://creativecommons.org/creativelicenses
      Dimensions:
      Weight & Pages:
      Dimensions:
      (229 x 152 mm)
      Weight & Pages:
      0.16kg, 90 Pages
    • Series:
      Elements in the Philosophy of Science
    Open Access
    You have digital access to this book
    Selected: Digital
    View content
    Add to cart View cart Buy from Cambridge.org
    Series:
    Elements in the Philosophy of Science

    Book description

    This Element presents a philosophical exploration of the notion of scientific representation. It does so by focussing on an important class of scientific representations, namely scientific models. Models are important in the scientific process because scientists can study a model to discover features of reality. But what does it mean for something to represent something else? This is the question discussed in this Element. The authors begin by disentangling different aspects of the problem of representation and then discuss the dominant accounts in the philosophical literature: the resemblance view and inferentialism. They find them both wanting and submit that their own preferred option, the so-called DEKI account, not only eschews the problems that beset these conceptions, but further provides a comprehensive answer to the question of how scientific representation works. This title is also available as Open Access on Cambridge Core.

    Reviews

    ‘The writing is clear, the argumentation is careful and compelling, the examples are engaging and on point. The book can be a very useful resource for undergraduate students taking philosophy of science courses, as well as for philosophers from other areas interested in getting a good, quick overview of the recent discussions around scientific representation and modelling … Overall, this is a very good book, and a precious resource for students and teachers alike.’

    Dimitri Coelho Mollo Source: Metascience

    ‘… this is an extremely lucid and well-written Element, and anyone interested in the philosophy of models and modeling would do well to pick up a copy.’

    Cory Wright Source: Journal for General Philosophy of Science

    References

    Ankeny, R. A., & Leonelli, S. (2021). Model organisms (Elements in the Philosophy of Biology). Cambridge: Cambridge University Press.
    Argyris, J. H., Faust, G., & Haase, M. (1994). An exploration of chaos. An introduction for natural scientists and engineers. Amsterdam: North-Holland.
    Baxter, R. J. (1982). Exactly solved models in statistical mechanics. London: Academic Press.
    Black, M. (1973). How do pictures represent? In Gombrich, E., Hochberg, J., & Black, M. (Eds.), Art, perception, and reality (pp. 95130). Baltimore and London: Johns Hopkins University Press.
    Boesch, B. (2017). There is a special problem of scientific representation. Philosophy of Science, 84(5), 970–81.
    Bogen, J., & Woodward, J. (1988). Saving the phenomena. Philosophical Review, 97(3), 303–52.
    Bolinska, A. (2013). Epistemic representation, informativeness and the aim of faithful representation. Synthese, 190(2), 219–34.
    Brading, K., & Landry, E. (2006). Scientific structuralism: Presentation and representation. Philosophy of Science, 73(5), 571–81.
    Brandom, R. B. (1994). Making it explicit: Reasoning, representing and discursive commitment. Cambridge, MA: Harvard University Press.
    Brandom, R. B. (2000). Articulating reasons: An introduction to inferentialism. Cambridge, MA: Harvard University Press.
    Bueno, O. (2010). Models and scientific representations. In Magnus, P. D., & Busch, J. (Eds.), New waves in philosophy of science (pp. 94111). Hampshire: Palgrave MacMillan.
    Bueno, O., & French, S. (2011). How theories represent. The British Journal for the Philosophy of Science, 62(4), 857894.
    Butterfield, J. (2011). Less is different: emergence and reduction reconciled. Foundations of Physics, 41, 1065–135.
    Callender, C., & Cohen, J. (2006). There is no special problem about scientific representation. Theoria, 21(55), 725.
    Carlton, J. S. (2007). Marine propellers and propulsion. Oxford: Butterworth-Heineman.
    Chakravartty, A. (2010). Informational versus functional theories of scientific representation. Synthese, 172(2), 197213.
    Contessa, G. (2007). Scientific representation, interpretation, and surrogative reasoning. Philosophy of Science, 74(1), 4868.
    de Donato Rodriguez, X., & Zamora Bonilla, J. (2009). Credibility, idealisation, and model building: An inferential approach. Erkenntnis, 70(1), 101–18.
    Decock, L., & Douven, I. (2011). Similarity after Goodman. Review of Philosophy and Psychology, 2(1), 6175.
    Díez, J. (2020). An ensemble-plus-standing-for account of scientific representation: no need for (unnecessary) abstract objects. In Martínez-Vidal, C., & Falguera, J. L. (Eds.), Abstract objects. For and against (pp. 133–49). Cham: Springer.
    Ducheyne, S. (2012). Scientific representations as limiting cases. Erkenntnis, 76(1), 7389.
    Einstein, A. (1920/1999). Relativity: The special and general theory. London: Methuen.
    Elgin, C. Z. (1983). With reference to reference. Indianapolis and Cambridge: Hackett.
    Elgin, C. Z. (2010). Telling instances. In Frigg, R., & Hunter, M. C. (Eds.), Beyond mimesis and convention: Representation in art and science (pp. 118). Berlin and New York: Springer.
    Elgin, C. Z. (2017). True enough. Cambridge, MA: MIT Press.
    French, S. (2020). Imagination in scientific practice. European Journal for Philosophy of Science, 10(3), 119.
    French, S. (2021). Identity conditions, idealisations and isomorphisms: A defence of the Semantic Approach. Synthese, 198, 5897–917.
    French, S., & Ladyman, J. (1999). Reinflating the semantic approach. International Studies in the Philosophy of Science, 13, 103–21.
    Friend, S. (2007). Fictional characters. Philosophy Compass, 2(2), 141–56.
    Frigg, R. (2006). Scientific representation and the semantic view of theories. Theoria, 55(1), 4965.
    Frigg, R. (2022). Models and theories. London: Routledge (forthcoming).
    Frigg, R., & Nguyen, J. (2017). Scientific representation is representation as. In Chao, H.-K., & Julian, R. (Eds.), Philosophy of science in practice: Nancy Cartwright and the nature of scientific reasoning (pp. 149–79). Cham: Springer.
    Frigg, R., & Nguyen, J. (2019). Of barrels and pipes: representation-as in art and science. In Wuppuluri, S. (Ed.), On art and science. Tango of an eternally inseparable duo (pp. 181202). Cham: Springer.
    Frigg, R., & Nguyen, J. (2020). Modelling nature. An opinionated introduction to scientific representation. Berlin and New York: Springer.
    Frigg, R., & Votsis, I. (2011). Everything you always wanted to know about structural realism but were afraid to ask. European Journal for Philosophy of Science, 1(2), 227–76.
    Gelfert, A. (2017). The ontology of models. In Magnani, L., & Bertolotti, T. (Eds.), Springer handbook of model-based science (pp. 523). Dordrecht Heidelberg: Springer.
    Giere, R. N. (1988). Explaining science: A cognitive approach. Chicago and London: University of Chicago Press.
    Giere, R. N. (2004). How models are used to represent reality. Philosophy of Science, 71(4), 742–52.
    Giere, R. N. (2010). An agent-based conception of models and scientific representation. Synthese, 172(1), 269–81.
    Godfrey-Smith, P. (2006). The strategy of model-based science. Biology and Philosophy, 21(5), 725–40.
    Goodman, N. (1972). Seven strictures on similarity. In Goodman, N. (Ed.), Problems and projects (pp. 437–46). Indianapolis and New York: Bobbs-Merrill.
    Goodman, N. (1976). Languages of art (2nd ed.). Indianapolis and Cambridge: Hackett.
    Hacking, I. (1983). Representing and intervening: Introductory topics in the philosophy of natural science. Cambridge: Cambridge University Press.
    Hartmann, S. (1995). Models as a tool for theory construction: Some strategies of preliminary physics. In Herfel, W. E., Krajewski, W., Niiniluoto, I., & Wojcicki, R. (Eds.), Theories and models in scientific processes (Poznan Studies in the Philosophy of Science and the Humanities 44) (pp. 4967). Amsterdam and Atlanta: Rodopi.
    Hesse, M. (1963). Models and analogies in science. London: Sheed and Ward.
    Hodges, W. (1997). A shorter model theory. Cambridge: Cambridge University Press.
    Hughes, R. I. G. (1997). Models and representation. Philosophy of Science, 64, S325S336.
    Khalifa, K., Millson, J., & Risjord, M. (2022). Scientific representation: An inferentialist-expressivist Manifesto. In Khalifa, K., Lawler, I., & Shech, E. (Eds.), Scientific understanding and representation: Modeling in the physical sciences (pp. TBC). TBC: Routledge.
    Khosrowi, D. (2020). Getting serious about shared features. The British Journal for the Philosophy of Science, 71(2), 523–46.
    Kirkham, R. L. (1992). Theories of truth: a critical introduction. Cambridge, MA: MIT Press.
    Knuuttila, T. (2021. Imagination extended and embedded: artifactual versus fictional accounts of models. Synthese, 198, 5077–97.
    Kroon, F., & Voltolini, A. (2018). Fictional entities. In E. N. Zalta (Ed.), The Stanford encyclopedia of philosophy, https://plato.stanford.edu/archives/win2018/entries/fictional-entities/.
    Kuhn, T. S. (1957). The Copernican Revolution. Planetary astronomy in the development of Western thought (2nd ed.). Massachusetts: Harvard University Press.
    Kulvicki, J. (2006). Pictorial representation. Philosophy Compass, 1(6), 535–46.
    Kuorikoski, J., & Lehtinen, A. (2009). Incredible worlds, credible results. Erkenntnis, 70(1), 119–31.
    Levy, A. (2015). Modeling without models. Philosophical Studies, 152(3), 781–98.
    McCullough-Benner, C. (2020). Representing the world with inconsistent mathematics. The British Journal for the Philosophy of Science, 71(4), 1331–58.
    Molland, A. F. (Ed.). (2008). The maritime engineering reference book. A guide to ship design, construction and operation. Oxford: Butterworth-Heineman.
    Morgan, M. (2012). The world in the model. How economists work and think. Cambridge: Cambridge University Press.
    Morgan, M., & Morrison, M. (Eds.). (1999). Models as mediators: Perspectives on natural and social science. Cambridge: Cambridge University Press.
    Murphy, A. (2020). Towards a pluralist account of the imagination in science. Philosophy of Science, 87(5), 957–67.
    Murzi, J., & Steinberger, F. (2017). Inferentialism. In Hale, B., Wright, C., & Miller, A. (Eds.), A companion to the philosophy of language (2nd ed., Vol. 1). Chichester: Wiley Blackwell.
    Nguyen, J. (2016). On the pragmatic equivalence between representing data and phenomena. Philosophy of Science, 83(2), 171–91.
    Nguyen, J. (2020). It’s not a game: accurate representation with toy models. The British Journal for the Philosophy of Science, 71(3), 1013–41.
    Nguyen, J., & Frigg, R. (2021). Mathematics is not the only language in the book of nature. Synthese, 198, 59415962.
    Nguyen, J., & Frigg, R. (2020). Unlocking limits. Argumenta, 6(1), 3145.
    Nguyen, J., & Frigg, R. (2022). Maps, models, and representation. In Khalifa, K., Lawler, I., & Shech, E. (Eds.), Scientific understanding and representation: Modeling in the physical sciences (pp. TBC). TBC: Routledge.
    Niiniluoto, I. (1988). Analogy and similarity in scientific reasoning. In Helman, D. H. (Ed.), Analogical reasoning: Perspectives of artificial intelligence, cognitive science, and philosophy (pp. 271–98). Dordrecht: Kluwer.
    Niven, W. D. (1965). The scientific papers of James Clerk Maxwell. New York: Dover.
    Norton, J. (2008). The dome: An unexpectedly simple failure of determinism. Philosophy of Science, 75(5), 786–98.
    Parker, W. (2015). Getting (even more) serious about similarity. Biology & Philosophy, 30, 267–76
    Pero, F., & Suárez, M. (2016). Varieties of misrepresentation and homomorphism. European Journal for Philosophy of Science, 6(1), 7190.
    Pincock, C. (2005). Overextending partial structures: Idealization and abstraction. Philosophy of Science, 72(5), 1248–59.
    Pincock, C. (2012). Mathematics and scientific representation. Oxford: Oxford University Press.
    Pincock, C. (2022). Concrete Scale Models, Essential Idealization, and Causal Explanation. The British Journal for the Philosophy of Science, 73(2), 299323
    Potochnik, A. (2017). Idealization and the aims of science. Chicago and London: University of Chicago Press.
    Putnam, H. (1981). Reason, truth, and history. Cambridge: Cambridge University Press.
    Quine, W. V. O. (1969). Ontological relativity and other essays. New York: Columbia University Press.
    Russell, B. (1919/1993). Introduction to mathematical philosophy. London and New York: Routledge.
    Ruyant, Q. (2021). True Griceanism: Filling the gaps in Callender and Cohen’s account of scientific representation. Philosophy of Science, 88(3), 533–53.
    Salis, F. (2013). Fictional entities. In J. Branquinho, & R. Santos (Eds.), Online companion to problems in analytical philosophy. http://compendioemlinha.letras.ulisboa.pt.
    Salis, F., & Frigg, R. (2020). Capturing the scientific imagination. In Godfrey-Smith, P., & Levy, A. (Eds.), The scientific imagination. Philosophical and psychological perspectives (pp. 1750). New York: Oxford University Press.
    Salis, F., Frigg, R., & Nguyen, J. (2020). Models and denotation. In Martínez-Vidal, C., & Falguera, J. L. (Eds.), Abstract objects: For and against (pp. 197219). Cham: Springer.
    Shapiro, S. (1983). Mathematics and reality. Philosophy of Science, 50(4), 523–48.
    Shech, E. (2015). Scientific misrepresentation and guides to ontology: The need for representational code and contents. Synthese, 192, 3463–85.
    Slutkin, G. (2013). Violence is a contagious disease. In Patel DM, S. M., Taylor, R. A. (Eds.), Contagion of violence: Workshop summary (pp. 94111). Washington, DC: National Academies Press.
    Sterrett, S. G. (2009). Similarity and dimensional analysis. In Mejers, A. (Ed.), Philosophy of technology and engineering sciences (pp. 799823). Amsterdam: Elsevier/North Holland.
    Sterrett, S. G. (2017a). Experimentation on analogue models. In Magnani, L., & Bertolotti, T. (Eds.), Springer handbook of model-based science (pp. 857–78). Cham: Springer.
    Sterrett, S. G. (2017b). Physically similar systems – A history of the concept. In Magnani, L., & Bertolotti, T. (Eds.), Springer handbook of model-based science (pp. 377411. Cham: Springer.
    Sterrett, S. G. (2020). Scale modeling. In Michelfelder, D., & Doorn, N. (Eds.), Routledge handbook of philosophy of engineering (pp. Ch. 29). London: Routledge. https://doi.org/10.4324/9781315276502
    Stuart, M. T. (2018). Thought experiments: The state of the art. In Stuart, M., Fehige, Y., & Brown, J. (Eds.), The Routledge companion to thought experiments (pp. 128). London: Routledge.
    Suárez, M. (2003). Scientific representation: Against similarity and isomorphism. International Studies in the Philosophy of Science, 17(3), 225–44.
    Suárez, M. (2004). An inferential conception of scientific representation. Philosophy of Science, 71(5), 767–79.
    Suárez, M. (2015). Deflationary representation, inference, and practice. Studies in History and Philosophy of Science, 49, 3647.
    Suárez, M., & Solé, A. (2006). On the analogy between cognitive representation and truth. Theoria, 55(1), 3948.
    Swoyer, C. (1991). Structural representation and surrogative reasoning. Synthese, 87(3), 449508.
    Tegmark, M. (2008). The mathematical universe. Foundations of Physics, 38(2), 101–50.
    Teller, P. (2001). Twilight of the perfect model model. Erkenntnis, 55(3), 393415.
    Thomasson, A. L. (2020). If models were fictions, then what would they be? In Levy, A., & Godfrey-Smith, P. (Eds.), The scientific imagination. Philosophical and psychological perspectives (pp. 5174). New York: Oxford University Press.
    Thomson-Jones, M. (2010). Missing systems and face value practice. Synthese, 172(2), 283–99.
    Toon, A. (2012). Models as make-believe. Imagination, fiction and scientific representation. Basingstoke: Palgrave Macmillan.
    Tversky, A. (1977). Features of similarity. Psychological Review, 84(4), 327–52.
    van Fraassen, B. C. (1980). The scientific image. Oxford: Oxford University Press.
    van Fraassen, B. C. (2008). Scientific representation: Paradoxes of perspective. Oxford: Clarendon Press.
    Weisberg, M. (2007). Who is a modeler? The British Journal for the Philosophy of Science, 58(2), 207–33.
    Weisberg, M. (2012). Getting serious about similarity. Philosophy of Science, 79(5), 785–94.
    Weisberg, M. (2013). Simulation and similarity: Using models to understand the world. Oxford: Oxford University Press.
    Weisberg, M. (2015). Biology and philosophy symposium on simulation and similarity: Using models to understand the world: Response to critics. Biology and Philosophy, 30(2), 299310.
    Wiley, S. A., Levy, M. Z., & Branas, C. C. (2016). The impact of violence interruption on the diffusion of violence: A mathematical modeling approach. In Letzer, G.. et. al. (Eds.), Advances in the mathematical sciences (Vol. 6, pp. 225–49, Association for Women in Mathematics Series). Cham: Springer.
    Xia, Z. (1992). The existence of noncollision singularities in Newtonian systems. Annals of Mathematics, 135(3), 411–68.

    Metrics

    Altmetric attention score

    Full text views

    Total number of HTML views: 0
    Total number of PDF views: 0 *
    Loading metrics...

    Book summary page views

    Total views: 0 *
    Loading metrics...

    * Views captured on Cambridge Core between #date#. This data will be updated every 24 hours.

    Usage data cannot currently be displayed.

    Accessibility standard: Unknown

    Why this information is here

    This section outlines the accessibility features of this content - including support for screen readers, full keyboard navigation and high-contrast display options. This may not be relevant for you.

    Accessibility Information

    Accessibility compliance for the PDF of this book is currently unknown and may be updated in the future.