Live Poster Session: Zoom Link
Abstract: With the more recent killings of Breonna Taylor and George Floyd, as well as the prominent Black Lives Matter movement, racial discrimination in law enforcement has been a hot spot for media and public attention. “Despite new attention to racial equity, black drivers are still 63% more likely to be stopped and 115% more likely to be searched during a traffic stop” (Horn, 2020). This project looks at the relationship between race of a driver and likelihood that their vehicle will be searched during a traffic stop with and without controlling for gender. The dataset looks at 3.1 million traffic stops from the 2022 CT Traffic Stops Study. 96.8% of traffic stops did not result in a search and 80% of stops were with a white driver. In comparing SearchStatus of the vehicle to the Race of the driver, black drivers have a likelihood of being searched that is 6.7 times higher than asian drivers while white driver have an expected odds of being searched that is only 2.8 times higher than asian drivers. Additionally, The odds of being searched are expected to increase by a factor of 2.5 if the driver is male, holding all other variables fixed. Black drivers have a significantly higher likelihood of their vehicle being searched during a traffic stop than white drivers and male drivers also have a significantly higher likelihood of their vehicle being searched during a traffic stop than female drivers. Policy makers in all levels of government, as well as police forces might use this information to identify the prevalence of race and gender based profiling and understanding the need for anti-discrimination training.
KELLY_QAC-final-poster-PDF