 Another implication of this approach is that judgments about the magnitudes of genetic vs environmental contributions are relative to a specific population and to a particular environment. Changing either one of these contextual factors can alter the extent to which some trait is deemed genetic. For example, suppose that a quantitative geneticist is interested in growing large corn plants. She sets out to compare two different corn genotypes (G1 and G2) across two different fertilizer treatments (E1 and E2). Suppose that G2 grows larger than G1 by exactly 5 units in both E1 and E2. This would lead our researcher to conclude that the observed variation in corn height is due entirely to genetic differences. We might further infer that the trait of height in corn plants is more strongly influenced by genetic than by environmental factors. However, this judgment is contingent on the comparison class that our researcher has chosen. Imagine another scenario in which G2 is compared to yet another genotype (G3). This time, our researcher compares E2 to E3, a third fertilizer treatment distinct from E1. Further suppose that G2 and G3 grow to the same height in E2, but that G3 is five units larger than G2 in E3. In this case, a comparison based on population differences suggests that the focal trait is more strongly influenced by environmental than by genetic factors. Let us now focus just on G2 in E2, and ask whether height in these corn plants is more strongly influenced by genetic or environmental factors? Sober (1988) uses a similar example to illustrate that any answer to this question is contingent on the comparison class one chooses. If we compare G2/E2 to G1/E1, then height differences come out as genetically influenced; but if we compare G2/E2 to G3/E3, then height differences come out as environmentally influenced. Hence, judgments about the relative magnitudes of genetic versus environmental contributions are inherently “non-local” or context sensitive.