Gareth FULLER
ABSTRACT: It is commonly accepted that scientific models include many misrepresentations of their real-world target. One type of misrepresentation is that of an “idealizing assumption”. An idealizing assumption is a modeling assumption that omits some factor of the real-world target that is known or presumed of being causally relevant to the phenomenon of interest. Some find the inclusion of idealizing assumptions to render a model unable to count as evidence for hypotheses about the real-world target. To resolve this, it is held that a model must be completely de-idealized. I consider two challenges to this requirement to de-idealize. One argues that the requirement to de-idealize is committed to an unsavory account of model fidelity known as the Perfect Model Model. I argue that the requirement to de-idealize is not committed to any troubling version of the Perfect Model Model. The other is that, since models are never de-idealized, and models play a central role in science, too much science needs to be given up to satisfy the requirement to de-idealize. It should, therefore, be rejected. In response I argue that this turns on a lack of clarity about what it is to de-idealize a model.