In this commentary, we discuss three types of data manipulations that can occur within teacher evaluation methods: artificial inflation, artificial deflation, and artificial conflation. These types of manipulation are more popularly known in the education profession as instances of Campbell's Law (1976), which states that the higher the consequences or stakes surrounding almost any quantifiable event (e.g., one that is based on numerical scores or outcomes), the more likely the scores or outcomes are subject to pressures of corruption and distortion, as directly related to the relative importance or weight of the consequences attached. We examine each type of data manipulation and consider the greater impact of each on practice and policy.