If you’re like me, you may have had two academic articles with seemingly conflicting arguments run through your Facebook feed lately.  The first, an article by Cody T. Ross published via PLOS ONE uses a multi-level Bayesian analysis to conclude that there exists

evidence of a significant bias in the killing of unarmed black Americans relative to unarmed white Americans, in that the probability of being {black, unarmed, and shot by police} is about 3.49 times the probability of being {white, unarmed, and shot by police} on average

The other, written by economist Roland G. Fryer and covered extensively in the New York Times Upshot column, concludes that in the case of “the most extreme use of force – officer-involved shootings – we find no racial differences in either the raw data or when contextual factors are taken into account.”

How can such diametrically opposed claims be made simultaneously in reputable scientific journals?  While much of these claims seems to rest in a domain of advanced statistics with which anthropologists typically feel less confident, the key to understanding their different claims actually might depend on a more “ethnographic” sense of the data sets they build upon.

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