I couldn't spot whether the paper normalize for dash-cam density. If one neighborhood has more dash-cams, is this paper over counting police cars in that neighborhood?
The paper covers this quite explicitly in sections 3 and 4.1.
> we are reweighting the Nexar data sample, which is sampled from a non-representative set of locations, so that it matches the locations where different demographic groups actually live. For example, to calculate the police deployment levels that Asian residents of New York City experience, we reweight the original data sample to upsample neighborhoods with larger Asian populations.
and
> For example, if vehicles are prohibited from driving near protest areas, which also have larger police presences, we will not have images of large police presences near protests. It is not possible to correct for this bias with the data we have because 1) the true distribution may differ from the Nexar sampling distribution along unobservable dimensions which we cannot reweight along and 2) we may simply have no Nexar images in some regions of the true distribution (e.g. if all vehicles are banned near protests). A second potential bias is that police vehicles represent only a subset of overall police activity: for example, they do not capture officers on foot. We return to both these points below.
Not sure whether you meant this by "explicitly" but I guess the answer is that they didn't correct for it.