Abstract

Integrative experiment design assumes that we can effectively design a space of factors that cause contextual variation. However, this is impossible to do so in a sufficiently objective way, resulting inevitably in observations laden with surrogate models. Consequently, integrative experiment design may even deepen the problem of incommensurability. In comparison, one-at-a-time approaches make much more tentative assumptions about the factors excluded from experiment design, hence still seem better suited to deal with incommensurability.