 Others agree that idealizations enable scientists to understand the world even though, strictly speaking, the idealizations misrepresent their target systems. According to Angela Potochnik (2017), this is because the systems studied by scientists are enormously complex networks of causal patterns and interactions. Particular interests and cognitive limitations will lead scientists to focus on some of these causal patterns and neglect others, and they might get those particular patterns right. In the process, however, they will misrepresent the actual messy complexity of the target system, and the understanding of phenomena that results will thereby be non-factive.