Emanuele Serrelli, SILFS 2010, "Models in philosophy of biology: a pragmatic approach"

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Paper at the triennial conference of the Italian Society for Logics and Philosophy of Science. More info on http://www.epistemologia.eu

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  • fitness landscapes are (a) a family of related models that share some core defining features, and that (b) these models are used to address a wide variety of related, but different, questions about evolutionary change (Calcott 2008, p. 640)\nThe adaptive landscape diagram, as a visualization of common, core assumptions of all themodels, iswhere the evaluation of the behaviors of the models takes place; the diagram is the heuristic with which the evaluation is being made. A model is positively evaluated in case a system described by it can traverse the landscape, shifting from one adaptive peak to the highest adaptive peak. (Skipper 2004, p. 1185)\n\n
  • fitness landscapes are (a) a family of related models that share some core defining features, and that (b) these models are used to address a wide variety of related, but different, questions about evolutionary change (Calcott 2008, p. 640)\nThe adaptive landscape diagram, as a visualization of common, core assumptions of all themodels, iswhere the evaluation of the behaviors of the models takes place; the diagram is the heuristic with which the evaluation is being made. A model is positively evaluated in case a system described by it can traverse the landscape, shifting from one adaptive peak to the highest adaptive peak. (Skipper 2004, p. 1185)\n«...but the more recent metaphor, and I must point out that it is indeed a metaphor not a model, is of a holey landscape» (2007, p. 251, my emphasis).\n\n
  • «the metaphorical understanding of the models in terms of “landscapes”» (p. 632, my emphasis) related to «our inability to generate visual images that accurately portray more than a very few significant aspects of the models» (p. 637, my emphasis).\n\n
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  • Emanuele Serrelli, SILFS 2010, "Models in philosophy of biology: a pragmatic approach"

    1. 1. Modelsin philosophy of biology: A pragmatic approach Emanuele Serrelli Università degli Studi di Milano Bicocca SILFS 2010
    2. 2. OUTLINE• Definition of “pragmatic approach”• Case study from evolutionary biology: adaptive landscapes • Brief description • Use of the term “model” • Problems and possible solutions • Motivations to a pragmatic approach: general and case-specific• Applicability of pragmatic approach
    3. 3. Pragmatic approach to models in philosophy of biology• Acknowledgement of the availability of multiple notions of “model”• Explicit selection of the notion most fit to the case under consideration• Fidelity to the choice made in the beginning• (with opportunity to do other analyses making different choices)
    4. 4. Adaptive landscapesSewall Wright (1932)
    5. 5. Adaptive landscapes
    6. 6. Landscape and model? «The adaptive landscape model» «Fitness landscapes are a family of related models» (Calcott 2008, p. 640) «The landscape diagram is where the evaluation of the behaviors of the model takes place» (Skipper 2004, p. 1185)
    7. 7. Landscape and model? «...I must point out that it is indeed a metaphor not a model» (Wilkins 2007, p. 251) «the metaphorical understanding of the models in terms of “landscapes”» related to «our inability to generate visual images that accurately portray more than a very few significant aspects of the models» (Kaplan 2008, pp. 632, 637)
    8. 8. y=Ce4Nsqq4Nmqm-1(1- q) 4Nm(1-qm)-1
    9. 9. Surface and metaphor?
    10. 10. Surface and metaphor•
    11. 11. y=Ce4Nsqq4Nmqm-1(1- q) 4Nm(1-qm)-1
    12. 12. Restriction«My idea is that Wright’s landscape was a diagram, agraphical presentation of parameters’ and variables’ values of an underlying mathematical model. The static image of the hilly surface wanted to displaynumerical features of the model. The dynamics of the “cloud” on the landscape was meant to show the behavior of the underlying mathematical model of a population. Confusion between the model and its graphical presentation yields confusion» (Serrelli 2010, p. 7, emphasis original)
    13. 13. y=Ce4Nsqq4Nmqm-1(1- q) 4Nm(1-qm)-1
    14. 14. Model in philosophy of biology• Centrality and pluralization y=• Foundational to PoB (Hull 1969), “semantic view of evolutionary theory” (Van Ce4Nsqq4Nmq -1(1- Fraassen 1980, Beatty 1981, Lloyd 1984, 1988, Thompson 1989) m• Downes SM (1992). The Importance of Models in Theorizing: A Deflationary q)4Nm(1-q )-1 m Semantic View. In PSA: Proceedings, pp. 142–153. • Griesemer JR (1990). Modeling in the Museum: On the Role of Remnant Models in the Work of Joseph Grinnell. Biology and Philosophy 5: 3-36. • Giere RN (1988), Explaining Science: A Cognitive Approach. Chicago: University of Chicago Press.• Godfrey-Smith P (2006). The strategy of model-based science. Biology & Philosophy, 21(5): 725-740. • Nersessian N (1999) Model-based reasoning in conceptual change. In: Magani L, Nersessian N, Thagard P (eds) Model-based reasoning in scientific discovery. Kluwer/Plenum, New York, pp 5–22• Casti J, Karlqvist A (1989). Newton to Aristotle: Towards a Theory of Models for Living Systems. Boston: Birkhäuser.• Morgan MS, Morrison M, eds. (1999). Models as Mediators. Perspectives on Natural and Social Science. Cambridge: Cambridge University Press.
    15. 15. Model: variable semantic extension y= Ce4Nsqq4Nmq -1(1- m q)4Nm(1-q )-1 m
    16. 16. Kaplan JM (2008). The end of the adaptive landscapemetaphor? Biology and Philosophy 23(5): 625–638. doi: 10.1007/s10539-008-9116-z.
    17. 17. Skipper Jr., RA (2004). The heuristic role of Sewall Wright’s1932 adaptive landscape diagram. Philosophy of Science 71(5), 1176-1188. doi: 10.1086/425240.
    18. 18. y=Ce4Nsqq4Nmqm-1(1- q) 4Nm(1-qm)-1
    19. 19. y=Ce4Nsqq4Nmqm-1(1- q) 4Nm(1-qm)-1
    20. 20. y=Ce4Nsqq4Nmqm-1(1- q) 4Nm(1-qm)-1Model = «stable target of explanation» (e.g., Keller 2002)
    21. 21. Pragmatic approach to models in philosophy of biology• Acknowledgement of the availability of multiple notions of “model”• Explicit selection of the notion most fit to the case under consideration• Fidelity to the choice made in the beginning• (with opportunity to do other analyses making different choices)
    22. 22. Applicability of pragmatic approach• Building or defense of general model-based visions of science (e.g.,Van Fraassen, Giere, semantic view) ➙ NO• Case-based, bottom-up analyses of modeling ➙ ?• Discussion of cases, where the interest is the case ➙ ABSOLUTELY YES
    23. 23. Thank you.
    24. 24. Sewall Wright (1931). Evolution in Mendelian populations. Δq = -uq+sq(1-q) = 0 q = 1-(u/s) q = 1-(u/hs’) ...etc.
    25. 25. Sewall Wright (1931). Evolution in Mendelian populations. y = Cy4Nsqq-1(1-q)-1
    26. 26. Sewall Wright (1931). Evolution in Mendelian populations. y = Ce4Nsqq4Nmqm-1(1-q)4Nm(1-qm)-1
    27. 27. Adaptive landscapesSergey Gavrilets (1997 sgg.)

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