The Proceedings of the National Academy of Sciences (PNAS) has published a study based on the content analysis of body cam footage from Oakland police that shows racial disparities in the “respect” and “formality” police officers show to citizens they interact with. Hoo boy—you can guess right away where this is heading.
Here’s the abstract of the study, “Language from police body camera footage shows racial disparities in officer respect”:
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. (Emphasis added.)
You can bet that this study is going to be abused by Black Lives Matter and other race demagogues as proof that the police are systemically racist, though to their credit, the authors of this study (a team of nine Stanford academics drawn from linguistics, psychology, and computer science) do not assert any claim of proof of racism.
It is worth getting into the internals of the complete text to flesh this out and make some observations, starting with this clause in the abstract: “even after controlling for the race of the officer . . .” This is a very important passage, as it clearly implies that black officers exhibit the same statistical disparity as white officers. I’ll come back to this point.
The two main variables the analysis tested for were “respect” and “formality” (though there are several more attributes they measure), and you can dive into the whole study if you want to see how they defined and quantified these variables.
The first thing I wondered was whether there were any statistical differences between officer demeanor to older citizens and to women. Sure enough, there on pages 3-4:
Officer utterances were also higher in Respect when spoken to older community members and when a citation was issued. [Data coefficients omitted here.]
Ditto for “formality”:
[W]e found that race was not associated with the formality of officers’ utterances. Instead, utterances were higher in Formality in interactions with older and female community members.
Now why might police officers be more respectful and formal with the elderly and women? Once upon a time we could rely on common sense to provide a range of answers, but now it is apparently a puzzle for social science. A puzzle the authors of this study have no hypothesis to offer.
Let’s move on to race, where the study says:
Officer race did not contribute a significant effect. Furthermore, in an additional model on 965 stops for which geographic information was available, neither the crime rate nor density of businesses in the area of the stop were significant, although a higher crime rate was indicative of increased Formality. (Emphasis added.)
The authors offer no comment or analysis about that last clause about higher crime rates being associated with high degrees of formality. Once again, common sense might supply an answer. Police have been turned into bureaucrats too much these days in my opinion, but they still tend to be rather street smart, and size up a situation based on what some social scientists otherwise call “pattern recognition.” Maybe Dan Kahneman’s Thinking Fast and Slow comes into play in explaining how police officers talk depending on how they assess the circumstances.
The authors concede that while “racial disparities in officer respect are clear and consistent, the causes of these disparities are less clear.”
It is certainly possible that some of these disparities are prompted by the language and behavior of the community members themselves [Comment: the authors offer no data or references for this possibility—isn’t this stereotyping?], particularly as historical tensions in Oakland and preexisting beliefs about the legitimacy of the police may induce fear, anger, or stereotype threat. However, community member speech cannot be the sole cause of these disparities. Study 1 found racial disparities in police language even when annotators judged that language in the context of the community member’s utterances. We observe racial disparities in officer respect even in police utterances from the initial 5% of an interaction, suggesting that officers speak differently to community members of different races even before the driver has had the opportunity to say much at all.
Again, is this necessarily indicative of latent, systemic racism, or does it reflect the collective experience of police professionals? It would be interesting if the authors could run their analysis on just rookie police officers versus grizzled veterans. That might reveal something significant.
The study concludes with the categorical imperative of all social science research:
Future research could expand body camera analysis beyond text to include information from the audio such as speech intonation and emotional prosody, and video, such as the citizen’s facial expressions and body movement, offering even more insight into how interactions progress and can sometimes go awry. In addition, footage analysis could help us better understand what linguistic acts lead interactions to go well, which can inform police training and quantify its impacts over time.
Yes, and it would be nice to send another hundred astronauts to the moon to scoop up more soil samples to understand cosmic geology. Are we really proposing to require police academy training now to include advanced linguistics? Or how about a study that connects electrodes to officers on the beat to measure their stress levels when they’re on a stop? This study is yet another example of finely sliced social science that provides a data-rich description of an unsurprising phenomenon, but little understanding of causation or remedy.
I have a better suggestion: How about all nine Stanford academics who worked on this study go on a nighttime ride along with Oakland police, where they’d learn a lot real fast about how real officers size up situations. I’d be willing to bet that none of them have ever done so.
Bonus: Female Philadelphia reporter goes off on the police. Film at 11!