Scientific Models as Abstract Epistemic Toolsfor Learning how to Reason

Main Article Content

Juan Bautista Bengoetxea Cousillas

Abstract

The variety of scientific methodologies aimed at obtaining knowledge, generating beliefs,and promoting action is very wide. Both philosophy of science and science education havebeen concerned with critically assessing the virtues of the various scientific methods, especiallythe inductive and deductive ones. However, the emergence of new procedures specific to nonacademicsciences has encouraged the development of new reflective perspectives that can analyzethose virtues. From randomized controlled trials to epidemiological or clinical procedures, thePhilosophy of Science has been concerned with examining the virtues and also the defects of theirpractical set-up. The article assumes that modeling based on empirical evidence is a practice of high interest in linguistics. In order to substantiate this assumption, two philosophical approaches to scientific modeling distinguished by their respective research lines on the notion of representationare compared: the Representational and the Pragmatic. These accounts are then illustrated with abrief case taken from linguistics called language parsing, aimed at examining several particularsamples collected as evidence in early stages of experimental modeling. By way of conclusion, it isemphasized that both philosophical accounts provide analytical elements that are relevant for thekind of scientific reasoning around models and whose scope in science education may be of greatpractical interest.

Article Details

Section
Miscellaneous
Author Biography

Juan Bautista Bengoetxea Cousillas, Universidad del País Vasco/Euskal Herriko Unibertsitatea

Doctor en Filosofía y Profesor Titular del Departamento de Filosofía de la Universidad de lasIslas Baleares. El presente texto de investigación es deudor del apoyo financiero de los Fondos FEDERpara el Desarrollo Regional de la Comunidad Europea y del Ministerio de Ciencia, Innovación yUniversidades (Gobierno de España, Agencia Estatal de Investigación (AEI)), así como del Proyecto deInvestigación ‘Estándares de prueba y elecciones metodólogicas en la fundamentación científica de lasdeclaraciones de salud’ (FFI2017-83543-P). El autor agradece el respaldo de todas las institucionesmencionadas. Algunas publicaciones del autor son Ética e ingeniería (2010, con C. Mitcham),‘Knowledge and Moral Responsibility for Online Technology’ (2015, Springer), ‘Chemistry’ (2015,Macmillan), ‘Culture and Technology in Spain: From Philosophical Analysis to STS’ (2006, con C.Mitcham) (Technology and Culture) e ‘Intuition and Evidential Facts in Carnap’s Analysis of Space’(2019, Revista de Filosofia Aurora).

References

Abbuhl, R., Gass, S., & Mackey, A. (2013). Experimental research design. En R. Podesva y D. Sharma (Eds.), Research Methods in Linguistics (pp. 116-134). Cambridge: Cambridge University Press. https://doi.org/10.1017/CBO9781139013734

Baggio, G., van Lambalgen, M., & Hagoort, P. (2012). Language, Linguistics and Cognition. En R. Kempson, Fernando, T., & Asher, N. (Eds.), Philosophy of Linguistics (pp. 325-355). Amsterdam: Elsevier. https://doi.org/10.1016/C2009-0-16474-7

Bailer-Jones, D.M. (2009). Scientific Models in Philosophy of Science. Pittsburgh: University of Pittsburgh Press.

Baird, D. (2004). Thing Knowledge: A Philosophy of Scientific Instruments. Berkeley: University of California Press.

Baker, P. (2010). Corpus Methods in Linguistics. En L. Litosseliti (Ed.), Research Methods in Linguistics (pp. 93-113). London: Continuum.

Bengoetxea, J.B. (2024). Complex networks, structural explanations, and the role of values in experimental linguistics. Principia: An international journal of epistemology, 28(4) (en prensa).

Bengoetxea, J.B. (2023). Modelación, representación lingüística y redes complejas. Veritas, 56, 109-133.

Bengoetxea, J.B., & Todt, O. (2021). Decision-making in the nutrition sciences: A critical analysis of scientific evidence for assessing health-claims. Manuscrito, 44(3), 42-69. https://doi.org/10.1590/0100-6045.2021.V44N3.JB

Bird, A. (1998). Philosophy of Science. London: UCL Press.

Bokulich, A. (2012). Distinguishing Explanatory from Nonexplanatory Fictions. Philosophy of Science, 179, 725-737. https://doi.org/10.1086/667991

Bokulich, A. (2017). Models and Explanation. In L. Magnani, & T. Bertolotti (Eds.), Handbook of Model-Based Science (pp. 103-118). Cham: Springer. https://doi.org/10.1007/978-3-319-30526-4

Boon, M., & Knuuttila, T. (2009). Models as Epistemic Tools in Engineering: A Pragmatic Approach. En A. Meijers (Ed.), Handbook of the Philosophy of Science, Vol. 9: Philosophy of Technology and Engineering Sciences (pp. 687-719). Amsterdam: Elsevier.

Boumans, M. (1999). Built-In Justification. En M.S. Morgan, & M. Morrison (Eds.), Models as Mediators: Perspectives on Natural and Social Science (pp. 66-96). Cambridge: Cambridge University Press. https://doi.org/10.1017/CBO9780511660108.003

Buchstaller, I., & Khattab, G. (2013). Population samples. En R. Podesva, & D. Sharma (Eds.), Research Methods in Linguistics (pp. 74-95). Cambridge: Cambridge University Press. https://doi.org/10.1017/CBO9781139013734

Bueno, O. 2014. Computer Simulations: An Inferential Conception. The Monist, 97(3), 378-398. https://doi.org/10.5840/monist201497324

Bueno, O., & French, S. (2018). Applying Mathematics: Immersion, Inference, Interpretation. Oxford: Oxford University Press.

Bunge, M. (1984). Philosophical Problems in Linguistics. Erkenntnis, 21, 107-173. https://doi.org/10.1007/bf00166382

Bunge, M. (1963). The Myth of Simplicity. Englewood, NJ: Prentice-Hall.

Cartwright, N. (2015). Evidence: for Policy. London: LSE.

Cartwright, N., & Hardy, J. (2012). Evidence-based policy: a practical guide to doing it better. New York: Oxford University Press. https://doi.org/10.1093/acprof:osobl/9780199841608.001.0001

Chakravartty, A. (2010). Informational versus functional theories of scientific representation. Synthese, 172, 197-213. https://doi.org/10.1007/s11229-009-9502-3

Cheng, M.F., Wu, T.Y., & Lin, S.F. (2019). Investigating the Relationship Between Views of Scientific Models and Modeling Practice. Research in Science Education, 51, 307-323. https://doi.org/10.1007/s11165-019-09880-2

Chomsky, N. (1965). Aspects of the Theory of Syntax. Cambridge, MA: MIT Press.

Chomsky, N., & Miller, G.A. 1963. Introduction to the formal analysis of natural languages. En D. Luce, R.R. Bush, & E. Galanter (Eds.), Handbook of mathematical psychology (pp. 269–321). New York: John Wiley.

Contessa, G. (2011). Scientific Models and Representation. En S. French, & J. Saatsi (Eds.), The Bloomsbury Companion to the Philosophy of Science (pp. 120-137). London: Bloomsbury.

De Boer, B., & Zuidema, W. (2013). Modelling in the language sciences. En R. Podesva, & D. Sharma (Eds.), Research Methods in Linguistics (pp. 428-445). Cambridge: Cambridge University Press. https://doi.org/10.1017/CBO9781139013734

De Regt, H.W. (2017). Understanding Scientific Understanding. Oxford: Oxford University Press.

DeRose, S.J. (1988). Grammatical Category Disambiguation by Statistical Optimization. Computational Linguistics, 14(1), 31–39

Derwing, B.L. (1979). Psycholinguistic evidence and linguistic theory. En G.D. Prideaux (Ed.), Perspectives in experimental linguistics (pp. 113-138). Amsterdam: John Benjamins.

Diethelm, P., & McKee, M. (2009). Denialism: what is it and how should scientists respond? The European Journal of Public Health, 19(1), 2-4.

Eco, U. (1992). Interpretación y sobreinterpretación. Madrid: Cambridge University Press, 1995.

Egré, P. (2015). Explanation in Linguistics. Philosophy Compass, 10(7), 451-462. https://doi.org/10.1111/phc3.12225

Fine, E.M., Delis, D.C., Paul, B.P., & Filoteo, J.V. (2011). Reduced verbal fluency for proper names in nondemented patients with Parkinson’s disease: a quantitative and qualitative analysis. Journal of Clinical and Experimental Neuropsychology, 33, 226-233. https://doi.org/10.1080/13803395.2010.507185

Fox-Keller, E. (2000). Models of and Models for: Theory and Practice in Contemporary Biology. Philosophy of Science, 67, 72-86. https://doi.org/10.1086/392810

French, S. (2013). The Structure of the World. Oxford: Oxford University Press.

Frigg, R. (2006). Scientific representation and the semantic view of theories. Theoria, 21(1), 49-65.

Giere, R.N. (2004). How models are used to represent physical reality. Philosophy of Science, 71, S742-S752. https://doi.org/10.1086/425063

Glymour, B. (2000). Data and Phenomena: A Distinction Reconsidered. Erkenntnis, 52, 29-37. https://doi.org/10.1023/A:1005499609332

Gouvea, J., & Passmore, C. (2017). ‘Models of’ versus ‘Models for’. Science & Education, 26, 49-63. https://doi.org/10.1007/s11191-017-9884-4

Gries, S.T., & Newman, J. (2013). Creating and using corpora. En R.J. Podesva, & D. Sharma (Eds.), Research Methods in Linguistics (pp. 257-287). Cambridge: Cambridge University Press. https://doi.org/10.1017/CBO9781139013734

Hacking, I. (1983). Representing and Intervening: Introductory topics in the philosophy of natural science. Cambridge: Cambridge University Press.

Hauser, R. 2006. A Computational Model of Natural Language Communication: Interpretation, Inference, and Production in Database semantics. Berlin: Springer.

Hintikka, J. (1988). What is the Logic of Experimental Inquiry? En J. Hintikka (1999), Inquiry as Inquiry: A Logic of Scientific Discovery (pp. 143-160). Dordrecht: Springer.

Hughes, R.I.G. (2010). The Theoretical Practices of Physics. Oxford: Clarendon Press.

Humphreys, P. (2004). Extending Ourselves: Computational Science, Empiricism, and Scientific Method. Oxford: Oxford University Press.

Humphreys, P., & Imbert, C. (Eds.) (2012). Models, Simulations, and Representations. New York: Routledge.

Karlsson, F., Voutilainen, A., Heikkilä, J., & Anttila, A. (Eds.) (1995). Constraint Grammar: A Language-Independent System for Parsing Unrestricted Text. Berlin: Mouton de Gruyter.

Kepser, S., & Reis, M. (2005). Evidence in Linguistics. En S. Kepser, & M. Reis (Eds.), Linguistic Evidence: Empirical, Theoretical and Computational Perspectives (pp. 1-6). Berlin: De Gruyter.

Knuuttila, T. (2021). Models, fictions and artifacts. In W.J. González (Ed.), Language and Scientific Research (pp. 199-220). Cham: Palgrave-Macmillan. https://doi.org/10.1007/978-3-030-60537-7.

Knuuttila, T. (2006). From Representation to Production: Parsers and Parsing in Language Technology. En J. Lenhard, G. Küpers, & T. Shinn (Eds.), Simulation: Pragmatic Construction of Reality (pp. 41-55). Dordrecht: Springer. https://doi.org/10.1007/1-4020-5375-4

Knuuttila, T. & Loettgers, A. (2012). The Productive Tension: Mechanisms vs. Templates in Modeling the Phenomena. En P. Humphreys, & C. Imbert (Eds.), Models, Simulations, and Representations (pp. 3-24). New York: Routledge.

Knuuttila, T., & Merz, M. (2009). Understanding by Modeling: An Objectual Approach. En H.W. de Regt, S. Leonelli, & K. Eigner (Eds.), Scientific Understanding: Philosophical Perspectives (pp. 146-168). Pittsburgh, Pa: University of Pittsburgh Press.

Knuuttila, T., & Voutilainen, A. (2003). A Parser as an Epistemic Artifact: A material view on models. Philosophy of Science, 70, S1484-S1495. https://doi.org/10.1086/377424

Krell, M., Redman, C., Mathesius, S., Krüger, D., & van Driel, J. (2020). Assessing Pre-Service Science Teachers’ Scientific Reasoning Competencies. Research in Science Education, 50, 2035-2329. https://doi.org/10.1007/s11165-018-9780-1

Latour, B. (2005). Reensamblar lo social: Una introducción a la teoría del actor-red. Buenos Aires: Manantial, 2008.

Machery. É. (2017). Philosophy Within Its Proper Bounds. Oxford: Oxford University Press.

Magnani, L., & Bertolotti, T. (Eds.) (2017). Handbook of Model-Based Science. Dordrecht: Springer. https://doi.org/10.1007/978-3-319-30526-4

Mäki, U. (2011). Models and the locus of their truth. Synthese, 180, 47-63. https://doi.org/10.1007/s11229-009-9566-0

Matthews, M.R. (2007). Models in Science and in Science Education: An Introduction. Science & Education, 16, 647-652. https://doi.org/10.1007/s11191-007-9089-3

McMullin, E. (2014). The Virtues of a Good Theory. En M. Curd, & S. Psillos (Eds.), The Routledge Companion to the Philosophy of Science (pp. 561-571). London: Routledge.

McNamara, T. (2006). Validity and values: Inferences and generalizability in language testing. En M. Chalhoub-Deville, C.A. Chapelle, & P. Duff (Eds.), Inference and Generalizability in Applied Linguistics (pp. 27-45). Amsterdam: John Benjamins. https://doi.org/10.1075/lllt.12

Morgan, M.S., & Morrison, M. (1999). Models as Mediators. Cambridge: Cambridge University Press.

Oliva, J.M., del Mar Aragón, M., & Cuesta, J. (2015). The Competence of Modelling in Learning Chemical Change. International Journal of Science and Mathematics Education, 13, 751-791. https://doi.org/10.1007/s10763-014-9583-4

Poznic, M. (2016). Representation and Similarity: Suárez on Necessary and Sufficient Conditions of Scientific Representation. Journal for General Philosophy of Science, 47, 331-347. https://doi.org/10.1007/s10838-015-9307-7

Prideaux, G. (Ed.) (1979). Perspectives in Experimental Linguistics. Amsterdam: John Benjamins.

Radder, H. (2003). Technology and Theory in Experimental Science. En H. Radder (Ed.), The Philosophy of Scientific Experimentation (pp. 152-173). Pittsburgh: University of Pittsburgh Press.

Reith, M., & Nehring, A. (2020). Scientific Reasoning and Views on the Nature of Scientific Inquiry: Testing a New Framework to Understand and Model Epistemic Cognition in Science. International Journal of Science Education, 42, 2716-2741. https://doi.org/10.1080/09500693.2020.1834168

Rost, M., & Knuuttila, T. (2022). Models as Epistemic Artifacts for Scientific Reasoning in Science Education Research. Education Sciences, 12, 276. https://doi.org/10.3390/educsci12040276.

Rouse, W.B. (2015). Modeling and Visualization of Complex Systems and Enterprises: Explorations of Physical, Human, Economic, and Social Phenomena. Hoboken, NJ: Wiley. https://doi.org/10.1002/9781118982747

Sackett, D.L., Rosenberg, W.M.C., Gray, J.A.M., Haynes, R.B., & Richardson, W.S. (1996). Evidence based medicine: what it is and what it isn't. British Medical Journal, 312, 71-72. http://doi.org/10.1136/bmj.312.7023.71

Schulz, R.M. (2014). Philosophy of Education and Science Education: A Vital but Underdeveloped Relationship. En M.R. Matthews (Ed.), International Handbook of Research in History, Philosophy and Science Teaching (pp. 1259-1316). Dordrecht: Springer. http://doi.org/10.1007/978-94-007-7654-8_39.

Shannon, P., Markiel, A., Ozier, O., Baliga, N.S., Wang, J.T., Ramage, D., Amin, N., Schwikowski, B., & Ideker, T. (2003). Cytoscape: A Software Environment for Integrated Models of Biomolecular Interaction Networks. Genome Research, 13, 2498-2504. https://10.1101/gr.1239303

Stanley, J. (2011). Know How. Oxford: Oxford University Press.

Stieff, M., Scopelitis, S., Lira, M.E., & Desutter, D. (2016). Improving Representational Competence with Concrete Models. Science & Education, 100, 344-363. https://doi.org/10.1002/sce.21203

Stubbs, M. (2006). Language Corpora. En A. Davies, & C. Elder (Eds.), The Handbook of Applied Linguistics (pp. 106-132). Malden, MA: Wiley-Blackwell. http://doi.org/10.1002/9780470757000

Suárez, M. (2015). Deflationary representation, inference, and practice. Studies in History and Philosophy of Science, 49, 36-47. https://doi.org/10.1016/j.shpsa.2014.11.001

Svetlova, E. (2015). Modeling as a Case for the Empirical Philosophy of Science. En S. Wagenknecht, N.J. Nercessian, & H. Andersen (Eds.), Empirical Philosophy of Science: Introducing Qualitative Methods into Philosophy of Science (pp. 65-82). Cham: Springer. https://doi.org/10.1007/978-3-319-18600-9

Sytsma, J., & Buckwalter, W. (Eds.) (2016). A Companion to Experimental Philosophy. Hoboken, NJ: Wiley-Blackwell.

Thagard, P. (1993). Computational Tractability and Conceptual Coherence. Canadian Journal of Philosophy, 23(3), 349-363.

Teller, P. (2001). Twilight of the perfect model. Erkenntnis, 55, 393-415. https://doi.org/10.1023/A:1013349314515

Trusswell, S. (2001). Levels and kinds of evidence for public-health nutrition. The Lancet, 357, 1061-1062. https://doi.org/10.1016/S0140-6736(00)04308-7

Van Fraassen, B.C. (2008). Scientific Representation. Oxford: Oxford University Press.