Abstract
I argue that we cannot adequately characterize idealization and abstraction and the distinction between the two on the grounds that they have distinct semantic properties. By doing so, on the one hand, we focus on the conceptual products of the two processes in making the distinction and we overlook the importance of the nature of the thought processes that underlie model-simplifying assumptions. On the other hand, we implicitly rely on a sense of abstraction as subtraction, which is unsuitable for explicating scientific model construction. Instead, I argue that a sense of abstraction as extraction is more suitable. Finally, I suggest a different way to distinguish the two processes that avoids these problems. Namely, that both idealization and abstraction could be understood as particular modes of application of the same cognitive process: selective attention.
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Notes
Morrison’s choice of terms is exactly the opposite of how they are used here: she calls ‘idealization’ the omission of features and ‘abstraction’ the modification of features of physical systems.
Cartwright (1989) could also be read as conceiving idealization and abstraction in a way that is in the neighborhood of this view.
This is not to say that idealizations and abstractions do not carry any semantic import, but only that the semantic properties assigned to idealizations and abstractions by conception-X do not adequately do the job of distinguishing the two kinds of assumptions.
The rest of the authors associated with conception-X do not address the aforementioned problem explicitly, but from the examples they use one could conclude that they do not distance themselves from Jones’ view. For example, Cartwright (1989, p. 187) regards the omission of frictional effects in setting up the equation of motion of a body on an incline plane as an idealization, and proceeds to explain that abstractions should be identified with the omissions of irrelevant-to-the-scientific-task features. Also in the same spirit, Godfrey-Smith (2009, p. 49) feels the need to distinguish between omission of features and imagining features absent. He offers as examples of imagining-features-absent leaving out frictional effects or leaving out genetic drift, and implies that in both cases these left-out features should be understood as idealizations as opposed to abstractions.
Different examples can be found in Weisberg (2013).
Another example that falls into this category, which is described in detail by Earman (2017), is a presentation of the Aharonov–Bohm effect that involves the assumption of an infinitely long solenoid that perfectly contains its magnetic field and which is impenetrable to an external electron. The entity to which these assumptions refer is fictional, it is meant to illuminate the foundations of Quantum Mechanics and not to represent an actual target system.
Humphries (1995, p. 159) makes a similar point.
I think this is another reason why several philosophers of science (some of whom were mentioned in the introduction) do not seem to consider it important to distinguish between idealization and abstraction. Because they construe abstraction as omission-as-extraction and because they realize that it too can lead to deviations from reality they simply include it in their generic notion of idealization.
Since the selected set Δ is unspecified, a consequence of the above definition is that selective attention, and thus abstraction, comes in degrees. We could selectively attend to a set that includes only one relational property and thus be led e.g. to the linear harmonic oscillator, but we could also opt to attend selectively to a set that includes more relational properties and thus be led e.g. to the damped harmonic oscillator.
In the example of the pendulum these effects are, of course, antecedently known. This, however, is not the rule. The reader can imagine the complexity of the process of discovering the effects of abstracted features in modeling a not so familiar domain.
A detailed analysis of the corrections to the theoretical predictions of the simple harmonic oscillator for the purpose of measuring gravitational acceleration can be found in Nelson and Olsson (1986), from where all the examples above are taken.
References
Broadbent, D. E. (1958). Perception and communication. Oxford: Oxford University Press.
Cartwright, N. D. (1989). Nature’s capacities and their measurement. Oxford: Clarendon Press.
Cartwright, N. C. (1999). The dappled world: A study of the boundaries of science. Cambridge: Cambridge University Press.
Chakravartty, A. (2007). A metaphysics for scientific realism. Cambridge: Cambridge University Press.
Contessa, G. (2011). Scientific models and representation. In S. French & J. Saatsi (Eds.), The continuum companion to the philosophy of science (pp. 120–137). London: Continuum International Publishing Group.
Da Costa, N. C. A., & French, S. (2003). Science and partial truth. Oxford: Oxford University Press.
Deutsch, J. A., & Deutsch, D. (1963). Attention: Some theoretical considerations. Psychological Review, 87, 272–300.
Duncan, J., & Humphries, G. W. (1989). Visual search and stimulus similarity. Psychological Review, 96, 433–458.
Duncan, J., & Humphries, G. W. (1992). Beyond the surface search: Visual search and attentional engagement. Journal of Experimental Psychology: Human Perception and Performance, 18, 578–588.
Earman, J. (2017). The role of idealizations in the Aharonov–Bohm effect. Synthese. https://doi.org/10.1007/s11229-017-1522-9.
French, S., & Ladyman, J. (1998). Semantic perspective on idealisation in quantum mechanics. In N. Shanks (Ed.), Idealisation IX: Idealisation in contemporary physics, Poznan studies (Vol. 63, pp. 51–73). Amsterdam: Rodopi.
Giere, R. N. (1988). Explaining science: A cognitive approach. Chicago: The University of Chicago Press.
Godfrey-Smith, P. (2009). Abstractions, idealizations and evolutionary biology. In A. Barberousse, M. Morange, & T. Pradue (Eds.), Mapping the future of biology: Evolving concepts and theories. Boston studies in the philosophy of science (pp. 47–55). Boston: Springer.
Humphries, P. (1995). Abstract and concrete. Philosophy and Phenomenological Research, 55(1), 157–161.
Jones, M. (2005). Idealization and abstraction: A framework. In M. Jones & N. Cartwright (Eds.), Idealization XII: Correcting the model, idealization and abstraction in the sciences (pp. 173–217). New York: Rodopi.
Laymon, R. (1985). Idealisation and the testing of theories by experimentation. In P. Achinstein & O. Hannaway (Eds.), Observation, experiment, and hypothesis in modern physical science (pp. 147–173). Massachusetts: MIT Press.
Laymon, R. (1995). Experimentation and the legitimacy of idealisation. Philosophical Studies, 77, 353–375.
Levy, A., & Bechtel, W. (2013). Abstraction and the organization of mechanisms. Philosophy of Science, 80(2), 241–261.
Mackie, J. L. (1976). Problems from Locke. Oxford: Clarendon Press.
Mcmullin, E. (1985). Galilean idealisation. Studies in History and Philosophy of Science, 16, 247–273.
Morrison, M. (2015). Reconstructing reality. Oxford: Oxford University Press.
Nelson, R. A., & Olsson, M. G. (1986). The pendulum—Rich physics from a simple system. American Journal of Physics, 54(2), 112–121.
Nersessian, N. (2002). Abstraction via generic modeling in concept formation in science. Mind & Society, 5(3), 129–154.
Portides, D. (2005). Scientific models and the semantic view of scientific theories. Philosophy of Science, 72(5), 1287–1298.
Portides, D. (2011). Seeking representations of phenomena: Phenomenological models. Studies in History and Philosophy of Science, 42, 334–341.
Suppe, F. (1989). The semantic conception of theories and scientific realism. Urbana: University of Illinois Press.
Teller, P. (2004). The Law-idealization. Philosophy of Science, 71(5), 730–741.
Teller, P. (2009). Fictions, fictionalization, and truth in science. In M. Suarez (Ed.), Fictions in science: Philosophical essays on modeling and idealization (pp. 235–247). New York: Routledge.
Treisman, A. (1969). Strategies and models of selective attention. Psychological Review, 76, 282–299.
Treisman, A. (1998). Feature binding, attention and object perception. Philosophical Transactions of the Royal Society, London B, 353(1373), 1295–1306.
Treisman, A., & Gelade, G. (1980). A feature-integration theory of attention. Cognitive Psychology, 12, 97–136.
Weisberg, M. (2013). Simulation and similarity. Oxford: Oxford University Press.
Acknowledgements
I wish to thank two anonymous referees for their comments and well-argued objections on an earlier version of this paper that helped me improve the paper significantly.
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Portides, D. Idealization and abstraction in scientific modeling. Synthese 198 (Suppl 24), 5873–5895 (2021). https://doi.org/10.1007/s11229-018-01919-7
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DOI: https://doi.org/10.1007/s11229-018-01919-7