This page contains the code and data to reproduce the core results in the following paper:
Language from Police Body Camera Footage Shows Racial Disparities in Officer Respect
Rob Voigt, Nicholas P. Camp, Vinodumar Prabhakaran, William L. Hamilton, Rebecca C. Hetey, Camilla M. Griffiths, David Jurgens, Dan Jurafsky, and Jennifer L. Eberhardt.
Proceedings of the National Academy of Sciences, 2017.
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.
The code is available as a script (in R/Python) and corresponding Jupyter Notebook for each of the three studies in the paper, explaining how to regenerate the results from the paper.
The data are available as three anonymized ".csv" files, one for each study in the paper. Due to privacy concerns we are not able to release any raw textual data from transcripts; however for each study we provide the following: