Several recent arguments by philosophers of biology have challenged the traditional view that evolutionary factors, such as drift and selection, are genuine causes of evolutionary outcomes. In the case of drift, advocates of the statistical theory argue that drift is merely the sampling error inherent in the other stochastic processes of evolution and thus denotes a mathematical, rather than causal, feature of populations. This debate has largely centered around one particular model of drift, the Wright–Fisher model, and this has contributed to the plausibility of the statisticalists’ arguments. However, an examination of alternative, predictively inequivalent models shows that drift is a genuine cause that can be manipulated to change population outcomes. This case study illustrates the influence of methodological assumptions on ontological judgments, particularly the pernicious effect of focusing on a particular model at the expense of others and confusing its assumptions and idealizations for true claims about the phenomena being modeled.