Developed in 2006, the veil of darkness approach is one of the most widely accepted methods for assessing the impact of driver race on traffic stops. Building on the original methodology, we innovate in three important ways to enhance the veil of darkness approach: (a) invoke generalized linear mixed models to account for the lack of independence among observations in traffic stop data sets, (b) decompose the relationship between daylight and driver race to consider the role of driver sex, and (c) assess variability in racial disproportionality across law enforcement units. Nearly 20,000 traffic stops are analyzed for the Durham (NC) Police Department. Results indicate that more than 10% of the variability in the rate of Black drivers stopped is accounted for by officer-level factors, racial disproportionality was only for male drivers, and evidence of disproportionality was found among some units, but no evidence was found among others.
