Abstract
This paper addresses a specific way of using representational models to construct other models, named ‘generative constructive use’. This use is distinguished from other ways of using models to construct new models. In particular, the case study shows how the model, in coordination with its target, opens up or extends a domain of investigation by suggesting and generating new targets and thereby prompting and enabling new forms of empirical investigation. That suggests that, in this case, it is the model in coordination to its target, rather than the model alone, that should be regarded as an epistemic tool. This use is philosophically important because it is what makes some models scientifically significant. Even though these models are successful representations, to make sense of their scientific significance we then need to go beyond their success as representation and adopt a perspective large enough to include the models and targets that they are used to produce.
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Notes
‘To some extent’ in the sense that if models are not contained in or derived from theories (Cartwright et al. 1995; Morgan and Morrison 1999; Suárez and Cartwright 2008), that does not mean that theories have no role to play in the construction of models. Theories provide structural resources and constraints (Morrison 2007) as well as a narrative that characterizes the entities of the domain of application of the theory (Morgan 2001; Peschard 2007).
This is not to claim that the use of abstract models to construct more specific models always takes place along a line relating a theory to the world. For instance, Boumans (1999) shows how the construction of economic models might involve a diversity of theoretical models or principles. The use of template models (Humphreys 2004) would also be a counter-example to that claim.
By contrast, for instance, with Steven French’s (2003) view that something may be a representation in and by itself.
Another necessary condition is the existence of a representational force directed from the source towards the target.
See, for instance, Frigg (2010) for a compelling criticism of this account.
This distinction will be useful in the context of this paper but is not claimed to cover all types of uses.
The anti-phase mode corresponds to the fingers moving towards and away from the midline at the same time, whereas in the in-phase mode the fingers move in the same direction at the same time.
It is not to say that the representational content of the fictional model or fictional assumption is irrelevant but rather to say that the use of the fictional model or assumption does not rely on the existence of what is represented or the truth of the assumption.
I will use ‘cognitive value’ and ‘epistemic value’ to refer to the value that accrues to models from their capacity to generate knowledge.
As Joseph Rouse writes, “Science as an ongoing practice of inquiry discounts truths that are trivial, marginal, anomalous, arcane, or otherwise ‘uninteresting’, in order to focus resources and attention upon others that are taken to be significantly revealing” (Rouse 2002, 157).
As we will see, they are abstract not only in the sense that they are abstract entities but in the sense that they are not fully specified (Giere 2010 125).
Decisive for ending the controversy was the thoroughgoing experimental study of Chas Williamson (1989).
For recent discussion of mechanistic approach in science see (Machamer et al. 2000).
Obviously, what it means that the model ‘works’ depends on the precision needed in the predictions. In this case it was deemed sufficient to only keep the first non-linear term of the development.
The analysis must be realized here via simulation.
See for instance Strogatz (2003).
See Cartwright (1983) for the idea of models as simulacra.
These two perspectives on the use of the discrete mathematical model to learn about the continuous physical system may reflect two different requirements on the epistemic function of the model: accuracy and correctness (Boumans 2005).
Such a case of construction also finds a nice illustration also in the recent technique of construction of models of climate system by coupling models of the different elements of the system (Küppers and Lenhard 2006).
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Acknowledgments
The author wishes to acknowledge support for this research by National Science Foundation (NSF) grant SES-1026183 and to thank Marcel Boumans and anonymous referees for helpful comments and suggestions.
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Peschard, I. Making sense of modeling: beyond representation. Euro Jnl Phil Sci 1, 335 (2011). https://doi.org/10.1007/s13194-011-0032-8
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DOI: https://doi.org/10.1007/s13194-011-0032-8