In 2016, special correspondent Jackie Judd interviewed Jennifer Eberhardt about a two-year-long study into the department, confirming that Oakland officers exhibit significant racial biases in their day-to-day work. The Oakland police department’s history of misconduct has made it the subject of federal oversight for 14 years. By leveraging body camera footage for a better understanding of police-community relations, “we can learn a lot more about the millions of interactions happening during these routine stops than we can from the popularized isolated cases.” “We don’t know of any other department right now taking this kind of approach to the footage,” Eberhardt said of her study published Monday in PNAS.Researchers reviewed 183 hours - 7.5 days - worth of body camera footage, from which they examined the language used in 36,000 exchanges between drivers and cops.The stops involved 245 different officers of varying races (102 white, 39 black, 36 Asian, 57 Hispanic and 11 marked as “other.”) A large majority - 224 of the officers - were male.Of the 26 million traffic stops recorded each year, a higher percentage are black drivers. These numbers mirror that national trend. They examined 981 stops, involving 682 black and 299 white drivers.Stanford psychologist Jennifer Eberhardt led a team of linguists and computer scientists who examined police body camera footage from one month - April 2014 - of routine traffic stops in the racially diverse city of Oakland, California.But it remains unclear if these videos represent isolated incidents or a general pattern of racial bias.īy relying on computers, this new study from Stanford University provides an impartial take on policing during traffic stops as well as a new automated method for assessing the behavior of cops based on the language they use. Videotape footage of police exchanges with people of color has quickly become a mainstay of public - and often viral - stories about law enforcement practices in the U.S. Police show more respect to whites than blacks during traffic stops, according to a computer analysis of conversations recorded by police body cameras in Oakland, California.
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