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Pragmatismo, ficcionalismo y la construcción de modelos científicos

Nélida Gentile
Universidad de Buenos Aires, Buenos Aires, Argentina.
Susana Lucero
Universidad Nacional de Luján, Buenos Aires, Argentina.

Publicado 2025-07-23

Palabras clave

  • Modelos científicos,
  • Pragmatismo metodológico,
  • Pluralismo científico,
  • Relación representacional,
  • Ficcionalismo,
  • Función cognitiva
  • ...Más
    Menos
  • Scientific Models,
  • Methodological Pragmatism,
  • Scientific Pluralism,
  • Representational Relationship,
  • Fictionalism,
  • Cognitive Function
  • ...Más
    Menos

Resumen

En el presente artículo, ofrecemos en primer término una revisión crítica de la concepción pragmática de la ciencia y cómo esta doctrina ha evolucionado hasta la actualidad. En segundo lugar, nos proponemos examinar la relación modelo-target cuyo valor epistémico ha sido cuestionado por algunos defensores de la visión pragmática. Uno de los principales objetivos del trabajo es mostrar que incluir la relación modelo-target en algunos contextos particulares —por ejemplo, en la concepción inferencial de modelos— no es en absoluto incompatible con la visión pragmática. Por otra parte, exploramos la relación entre pragmatismo y ficcionalismo en el contexto de la construcción de modelos. Con respecto a este tópico, rechazamos la posición que hemos denominado “ficcionalismo completo” y asumimos una actitud deflacionaria, “ficcionalismo estrecho”, el cual admite solo una clase de componentes no realísticos de un modelo: los que refieren a entidades no existentes.

Citas

  1. Bokulich, A. (2011). How scientific models can explain. Synthese, 180, 33-45. https://doi.org/10.1007/s11229-009-9565-1
  2. Bokulich, A. (2018). Searching for non-causal explanations in a sea of causes. In A. Reutlinger & J. Saatsi (Eds), Explanation beyond causation: Philosophical perspectives on non-causal explanations (pp. 141-163). Oxford University Press. https://doi.org/10.1093/oso/9780198777946.003.0008
  3. Cassini, A. (2013). Modelos, idealizaciones y ficciones: Una crítica del ficcionalismo. Principia, 17(3): 345-364. https://doi.org/10.5007/1808-1711.2013v17n3p345
  4. Chakravartty, A. (2010). Informational versus functional theories of scientific representation. Synthese, 172: 197-213. https://doi.org/10.1007/s11229-009-9502-3
  5. Dewey, J. (1938). Unity of science as a social problem. In O. Neurath, C. W. Morris & R. Carnap (Eds.), International Encyclopedia of Unified Science (Volume I, No. 1, pp. 29-38). Chicago University Press. Reprinted in J. Dewey (1988), The Later Works of John Dewey (Volume 13: 1938-1939, pp. 271-280). Southern Illinois University Press.
  6. Díez, J. A. (2021). Scientific representation as ensemble-plus-standing-for: A moderate fictionalist account. In A. Cassini & J. Redmond (Eds.), Models and idealizations in science: Artefactual and fictional approaches (pp. 115-131). Springer. https://doi.org/10.1007/978-3-030-65802-1_5
  7. Dupré, J. (1993). The disorder of things: Metaphysical foundations of the disunity of science. Harvard University Press. Cited by S. H. Kellert, H. E. Longino, & C. K. Waters, (Eds.) (2006), Scientific pluralism. University of Minnesota Press.
  8. Fang, W. (2019). An inferential account of model explanation. Philosophia, 47, 99-116. https://doi.org/10.1007/s11406-018-9958-9
  9. Frigg, R. (2006). Scientific representation and the semantic view of theories. Theoria: An International Journal for Theory, History and Foundations of Science, 21(1), 49-65. https://doi.org/10.1387/theoria.553
  10. Frigg, R. (2010a). Models and fictions. Synthese, 172, 251-268. https://doi.org/10.1007/s11229-009-9505-0
  11. Frigg, R. (2010b). Fiction and scientific representation. In R. Frigg & M. Hunter (Eds.), Beyond mimesis and convention: Representation in art and science (pp. 97-138). Springer. https://doi.org/10.1007/978-90-481-3851-7_6
  12. Frigg, R., & Salis, F. (2020). Of rabbits and men: Fiction and scientific modeling. In B. Armour-Garb & F. Kroon (Eds.), Fictionalism in philosophy (pp. 187-206). Oxford. https://doi.org/10.1093/oso/9780190689605.003.0010
  13. Giere, R. (2004). How models are used to represent reality. Philosophy of Science, 71(5). 742-752. https://doi.org/10.1086/425063
  14. Giere, R. (2009). Why scientific models should not be regarded as works of fiction. In M. Suárez (Ed.), Fictions in science: Philosophical essays in modeling and idealization (pp. 248-258). Routledge.
  15. Giere, R. (2010). An agent-based conception of models and scientific representation. Synthese, 172(269). https://doi.org/10.1007/s11229-009-9506-z
  16. Gillespie, A., Glăveanu, V., & de Saint Laurent, C. (2024). Pragmatism and methodology: Doing research that matters with mixed methods. Cambridge University Press. https://doi.org/10.1017/9781009031066
  17. Godfrey-Smith, P. (2006). The strategy of model-based science. Biology and Philosophy, 21, 725-740. https://doi.org/10.1007/s10539-006-9054-6
  18. Godfrey-Smith, P. (2017). Dewey and anti-representationalism. In S. Fesmire (Ed.), The Oxford handbook of Dewey (pp. 151-172). Oxford University Press.
  19. Gonzalez, W. J. (2020). Pragmatism and pluralism as methodological alternatives to monism, reductionism and universalism. In W. J. González (Ed.), Methodological prospects for scientific research: From pragmatism to pluralism (pp. 1-18). Springer. https://doi.org/10.1007/978-3-030-52500-2_1
  20. Greene, J. C., & Caracelli, V. J. (2003). Making paradigmatic sense of mixed methods practice. In A. Tashakkori & C. Teddlie (Eds.), Handbook of mixed methods in social and behavioral research (pp. 91-110). Sage. Cited by V. Kaushik, & C. Walsh (2019), Pragmatism as a research paradigm and its implications for social work research. Social Sciences, 8(9), 255.
  21. Hughes, R. I. G. (1997). Models and representation. Philosophy of Science, 64, S325-S336. http://www.jstor.org/stable/188414
  22. Isaac, A. M. C. (2013). Modeling without representation. Synthese, 190, 3611-3623. https://doi.org/10.1007/s11229-012-0213-9
  23. James, W. (1909). A pluralistic universe. Longmans, Green & Company.
  24. Kaushik, V., & Walsh, C. (2019). Pragmatism as a research paradigm and its implications for social work research. Social Sciences, 8(9), 255. https://doi.org/10.3390/socsci8090255
  25. Kellert, S. H., Longino, H. E., &Waters, C. K. (Eds.) (2006). Scientific pluralism. University of Minnesota Press.
  26. Kitcher, P. (1993). The advancement of science: Science without legend, objectivity without illusions. Oxford University Press.
  27. Kitcher, P. (2001). Science, truth, and democracy. Oxford University Press. Cited by S. H. Kellert, H. E. Longino, & C. K. Waters, (Eds.) (2006), Scientific pluralism. University of Minnesota Press.
  28. Knuuttila, T. (2009). Representation, idealization, and fiction in economics. In M. Suárez (Ed.), Fictions in science: Philosophical essays in modeling and idealization (pp. 205-231). Routledge.
  29. Knuuttila, T. (2010). Some consequences of the pragmatist approach to representation: Decoupling the model-target dyad and indirect reasoning. In M. Dorato, M. Suárez & M. Rédei (Eds.): EPSA Epistemology and Methodology of Science: Launch of the European Philosophy of Science Association (Volume I, Epistemology and Methodology of Science, pp. 139-148). Springer.
  30. Knuuttila, T. (2011). Modeling and representing: An artefactual approach to model-based representation. Study in History and Philosophy of Science, Part A, 42(2), 262-271. https://doi.org/10.1016/j.shpsa.2010.11.034
  31. Knuuttila, T. (2021). Epistemic artifacts and the modal dimension of modeling. European Journal for Philosophy of Science, 11, 65. https://doi.org/10.1007/s13194-021-00374-5
  32. Kuorikoski, J., & Ylikoski, P. (2015). External representation and scientific understanding. Synthese, 192, 3817-3837. https://doi.org/10.1007/s11229-014-0591-2
  33. Legg, C., & Hookway, C. (2024). Pragmatism. In E. N. Zalta & U. Nodelman (Eds.), The Encyclopedia of Philosophy (Winter 2024 ed.). https://plato.stanford.edu/archives/win2024/entries/pragmatism/
  34. Levy, A. (2012). Models, fictions, and realism: Two packages. Philosophy of Science, 79(5), 738-748. https://doi.org/10.1086/667992
  35. Levy, A. (2015). Modeling without models. Philosophical Studies, 172(3), 781-798. https://doi.org/10.1007/s11098-014-0333-9
  36. Ludwig, D., & Ruphy, S. (2021). Scientific pluralism. In E. N. Zalta (Ed.), The Stanford Encyclopedia of Philosophy (Winter 2021 ed.). https://plato.stanford.edu/archives/win2021/entries/scientific-pluralism/
  37. Misak, C. J. (1991). Truth and the end of inquiry: Peircean account of truth. Oxford University Press. https://doi.org/10.1093/0199270597.001.0001
  38. Mitchell, S. (2002). Integrative pluralism. Biology & Philosophy, 17, 55-70. https://doi.org/10.1023/A:1012990030867. Cited by S. H. Kellert, H. E. Longino, & C. K. Waters, (Eds.) (2006), Scientific pluralism. University of Minnesota Press.
  39. Morrison, M. (2009). Fictions, representations, and reality. In M. Suárez (Ed.), Fictions in science: Philosophical essays in modeling and idealization (pp. 110-135). Routledge.
  40. Nguyen, J. (2020). Do fictions explain? Synthese, 199, 3219-3244. https://doi.org/10.1007/s11229-020-02931-6
  41. Patton, M. Q. (2002). Qualitative research and evaluation methods (3rd ed.). Sage. Cited by V. Kaushik, & C. Walsh (2019), Pragmatism as a research paradigm and its implications for social work research. Social Sciences, 8(9), 255.
  42. Psillos, S. (1999). Scientific realism: How science tracks truth. Routledge.
  43. Rescher, N. (2020). Methodological pragmatism. In W. J. González (Ed.), Methodological prospects for scientific research: From pragmatism to pluralism (pp. 69-80). Springer. https://doi.org/10.1007/978-3-030-52500-2_4
  44. Robson, C. (1993). Real world research. Blackwell. Cited by V. Kaushik, & C. Walsh (2019), Pragmatism as a research paradigm and its implications for social work research. Social Sciences, 8(9), 255.
  45. Schlick, M. (1925). Allgemeine Erkenntnislehre (2nd ed.). Springer.
  46. Suárez, M. (2004). An inferential conception of scientific representation. Philosophy of Science, 71(5), 767-779. https://doi.org/10.1086/421415
  47. Suárez, M. (2009). Scientific fictions as rules of inference. In M. Suárez (Ed.), Fictions in science: Philosophical essays in modeling and idealization (pp. 158-178). Routledge.
  48. Suárez, M. (2010). Fictions, inference, and realism. In J. Woods (Ed.), Fictions and models: New essays (pp. 225-245). Philosophia. https://doi.org/10.2307/j.ctv2nrzgsf.9
  49. Suárez, M. (2015). Scientific representation, denotation, and fictional entities. In U. Mäki, I. Votsis, S. Ruphy & G. Schurz (Eds.), Recent developments in the philosophy of science: EPSA13 Helsinki (European Studies in Philosophy of Science, volume 1, pp. 331-341). Springer. https://doi.org/10.1007/978-3-319-23015-3_25
  50. Suppes, P. (1978). The plurality of science. PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association, 1978(2), 2-16. https://doi.org/10.1086/psaprocbienmeetp.1978.2.192459
  51. Teddlie, C., & Tashakkori, A. (2009). Foundations of mixed methods research. Sage. Cited by V. Kaushik, & C. Walsh (2019), Pragmatism as a research paradigm and its implications for social work research. Social Sciences, 8(9), 255.
  52. Teller, P. (2009). Fictions, fictionalization, and truth in science. In M. Suárez (Ed.), Fictions in science: Philosophical essays in modeling and idealization (pp. 235-247). Routledge.
  53. Toon, A. (2012a). Models as make-believe. In R. Frigg & M. Hunter (Eds.), Beyond mimesis and convention: Representation in art and science (pp. 71-96). Springer. https://doi.org/10.1007/978-90-481-3851-7_5
  54. Toon, A. (2012b). Models as make-believe: Imagination, fiction and scientific representation. Palgrave Macmillan. https://doi.org/10.1057/9781137292230
  55. Toon, A. (2016). Imagination in scientific modeling. In A. Kind (Ed.), The Routledge handbook of philosophy of imagination (pp. 451-462). Routledge.
  56. Vaihinger, H. (1935). The philosophy of ‘As if’. Kegan Paul, Trench, Trubner, & Company.
  57. Van Fraassen, B. (2008). Scientific representation: Paradoxes of perspective. Oxford University Press. https://doi.org/10.1093/acprof:oso/9780199278220.001.0001
  58. Walton, K. (1990). Mimesis as make-believe: On the foundations of the representational arts. Harvard University Press.
  59. Weisberg, M. (2007). Who is a modeler? The British Journal for the Philosophy of Science, 58(2), 207-233. https://doi.org/10.1093/bjps/axm011