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.