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

1. Models
in philosophy of biology:
A pragmatic approach
Emanuele Serrelli
Università degli Studi di Milano Bicocca
SILFS 2010

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. 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. Adaptive landscapes
Sewall Wright (1932)

5. Adaptive landscapes

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. 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. y=
Ce4Nsqq4Nmqm-1(1-
q) 4Nm(1-qm)-1

9. Surface and metaphor?

10. Surface and metaphor
•

11. y=
Ce4Nsqq4Nmqm-1(1-
q) 4Nm(1-qm)-1

12. Restriction
«My idea is that Wright’s landscape was a diagram, a
graphical presentation of parameters’ and variables’
values of an underlying mathematical model. The
static image of the hilly surface wanted to display
numerical 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. y=
Ce4Nsqq4Nmqm-1(1-
q) 4Nm(1-qm)-1

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. Model: variable semantic
extension
y=
Ce4Nsqq4Nmq -1(1-
m
q)4Nm(1-q )-1
m

16. Kaplan JM (2008). The end of the adaptive landscape
metaphor? Biology and Philosophy 23(5): 625–638. doi:
10.1007/s10539-008-9116-z.

17. Skipper Jr., RA (2004). The heuristic role of Sewall Wright’s
1932 adaptive landscape diagram. Philosophy of Science 71(5),
1176-1188. doi: 10.1086/425240.

18. y=
Ce4Nsqq4Nmqm-1(1-
q) 4Nm(1-qm)-1

19. y=
Ce4Nsqq4Nmqm-1(1-
q) 4Nm(1-qm)-1

20. y=
Ce4Nsqq4Nmqm-1(1-
q) 4Nm(1-qm)-1
Model = «stable target
of explanation» (e.g.,
Keller 2002)

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. 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. Thank you.

24. Sewall Wright (1931). Evolution in Mendelian populations.
Δq = -uq+sq(1-q) = 0
q = 1-(u/s)
q = 1-(u/hs’) ...etc.

25. Sewall Wright (1931). Evolution in Mendelian populations.
y = Cy4Nsqq-1(1-q)-1

26. Sewall Wright (1931). Evolution in Mendelian populations.
y = Ce4Nsqq4Nmqm-1(1-q)4Nm(1-qm)-1

27. Adaptive landscapes
Sergey Gavrilets
(1997 sgg.)