ABSTRACT
Scientific models can be deidealized in several ways. For instance, by adding new constants, parameters, or variables to their equations, or by resetting the values of their parameters. According to most realist views, deidealized models provide more accurate and truthlike descriptions of their targets than their more idealized counterparts. By contrast, most pragmatic approaches tend to assess the costs and benefits of deidealizing in light of the purposes for which the models are built. From this point of view, deidealizing a model may be counterproductive because deidealized models are generally more complex, and sometimes more mathematically intractable, than simpler and highly idealized models. Several controversies have recently arisen concerning the very possibility of deidealizing some models that represent their targets holistically. The explanatory power of idealizations has also been questioned.
