Language from police body camera footage shows racial disparities in officer respect

Abstract

Using footage from body-worn cameras, we analyze the respectfulness of police officer language toward white and black community members during routine traffic stops. We develop computational linguistic methods that extract levels of respect automatically from transcripts, informed by a thin-slicing study of participant ratings of officer utterances. We find that officers speak with consistently less respect toward black versus white community members, even after controlling for the race of the officer, the severity of the infraction, the location of the stop, and the outcome of the stop. Such disparities in common, everyday interactions between police and the communities they serve have important implications for procedural justice and the building of police-community trust.

Keywords: natural language processing; policing; procedural justice; racial disparities; traffic stops.

Fig. 1.

(Left) Differences in raw participant ratings between interactions with black and white community members. (Right) When collapsed to two uncorrelated components, Respect and Formality, we find a significant difference for Respect but none for Formality. Error bars represent 95% confidence intervals. PC, principal component.

Fig. 2.

(Left) Respect weights assigned by final model to linguistic features and (Right) the corresponding log-odds of those features occurring in officer speech directed toward black versus white community members, calculated using Fisher’s exact test. ^†P < 0.1; ^∗P < 0.05; ^∗∗P < 0.01; ^∗∗∗P < 0.001.

Fig. 3.

Sample sentences with automatically generated Respect scores. Features in blue have positive coefficients in the model and connote respect, such as offering reassurance (“no problem”) or mentioning community member well-being (“drive safe”). Features in red have negative coefficients in the model and connote disrespect, like informal titles (“my man”), or disfluencies (“that- that’s”).

Fig. 4.

Kernel density estimate of individual officer-level differences in Respect when talking to white as opposed to black community members, for the 90 officers in our dataset who have interactions with both blacks and whites. More positive numbers on the x axis represent a greater positive shift in Respect toward white community members.

Fig. 5.

Loess-smoothed estimates of the (Left) Respect and (Right) Formality of officers’ utterances relative to the point in an interaction at which they occur. Respect tends to start low and increase over an interaction, whereas the opposite is true for Formality. The race discrepancy in Respect is consistent throughout the interactions in our dataset.