How should we measure racial discrimination?
A 2018 National Academy of Sciences report on American policing begins its section on racial bias by noting the abundance of scholarship that records disparities in the criminal justice system. But shortly thereafter, the authors make a strange clarification: “In many cases there is little informative quantitative data on whether… policing is influenced by the racial or ethnic identity of citizens in a causal sense.”
On the one hand, troves of studies demonstrating racial disparities across a range of policing situations. On the other, a lack of data showing policing to be causally influenced by race. What accounts for the gap between evidence of racial disparities and proof of race as a causal influence on those disparities? The report presents a vignette that offers some clues:
"[A] police officer may decide to stop and question or frisk a Black citizen but may decide not to question a White citizen, creating a racial disparity in stops… Based solely on measures of officer’s behavior, however, it is impossible to know whether this behavior was actually racially biased. If the Black and White pedestrians, for instance, acted differently as the officer approached (e.g., nervous versus calm), or if the officer encountered them in different surroundings (at night in an alley versus at noon in the park), or if the officer was searching for a suspect described as Black, an objective observer might conclude that the officer was simply responding to the situation at hand."
The takeaway is that robust correlations in observational data offer satisfactory descriptive statistics, but they cannot, at least not on their own, meet the gold standard of scientific explanation—causal explanation. Only social scientists pursuing causal inference methods are equipped to answer sought-after “why” questions: Why are there racial disparities in policing? Is the disparity because of race or because of something else?