Abstract: Causal inference is hard, and everyone knows it. It is less recognized that descriptive and comparative scholarship also rely upon causal inference. How data are sampled and curated influences how we should process the data, in order to accurately describe or compare the people, times, and places of interest. I’ll present some examples to illustrate the problems that ignoring causal structure can create, along with some solutions.