The use of models in the construction of scientific theories is as wide-spread as it is philosophically interesting (and, one might say, vexing). Neither in philosophical analysis nor scientific practice do we find a univocal concept of model; but there is an established usage in which a model is constituted, at least in part, by the theorist's idealizations and abstractions. Idealizations are expressed by statements known to be false. Abstractions are achieved by suppressing what is known to be true. Idealizations, we might say, over-represent empirical phenomena, whereas abstractions under represent them. Accordingly, we might think of idealizations and abstractions as one another's duals. In saying what is false and failing to say what is true, idealization and abstraction introduce distortions into scientific theories. Even so, the received and deeply entrenched view of scientists and philosophers is that these distortions are both necessary and virtuous. A good many people who hold this view see the good of models as merely instrumental, in a sense intended to contrast with "cognitive". Others, however, take the stronger and more philosophically challenging position that the good done by these aspects of scientific modeling is cognitive in nature. Roughly speaking, something has instrumental value when it helps produce a result that "works". Something has cognitive value when it helps produce knowledge. Accordingly, a short way of making the cognitive virtue claim is as follows: Saying what's false and suppressing what is true is, for wide ranges of cases, indispensable to the production of scientific knowledge. Given the sheer volume of traffic in the modeling literature, focused discussions of what makes these distortions facilitators of scientific knowledge attracts comparatively slight analytical attention by philosophers of science and philosophically-minded scientists. This is perhaps less true of the distortions effected by abstraction than those constituted by idealization. Still, in relation to the scale of use of the models methodology, these discussions aren't remotely as widespread and, when even they do occur, are not particularly "thick". The principal purpose of this paper is to thicken the analysis of the cognitive virtuosity of falsehood-telling and truth-suppression. The analysis will emphasize the influence of these factors on scientific understanding.
Woods, J. (2010)., Virtuous distortion, in L. Magnani, W. Carnielli & C. Pizzi (eds.), Model-based reasoning in science and technology, Dordrecht, Springer, pp. 3-30.
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