Did You Know?: Traffic Stop Analysis for Weston

Not in Weston. Photo by Erik Mclean on Unsplash

This week the Massachusetts Executive Office of Public Safety and Security (EOPSS) released findings from a baseline analysis of police traffic stop data at the local and state level. These data were collected as part of Chapter 122 of the Acts of 2019 which included the Hands Free Use of Mobile Telephones While Driving (now THAT’s an acronym HFUMTWD).  As a result of the HFUMTWD act, an annual analysis of police traffic stop data is required along with a public report of findings. 

The Owl read the report yesterday, and in an effort to condense its 400+ pages, pulled out some relevant points and some ideas for bettering the report in the future (are you listening, Governor Charlie, go NU ‘cats?) . If you are concerned about the Owl’s objectivity, let me suggest that you read it yourself–you get to learn cool new terms like Intertwilight Period (ITP) and Veil of Darkness stops. The latter term is somewhat more menacing-sounding than it actually is–we are not living a goth romance here, Weston. In any case, here is a link to the report –Weston town data is page 327 of said report. 

In addition to report reading, the Owl flapped over to the Weston Police Station, obeying all traffic laws and therefore arriving 5 minutes late (thank you Highland crossing) to talk live and in-person with Interim Police Chief (IPC) Tom Kelly, and Lt. Mike Forti who puts up with more than his fair share of shenanigans from the Wes-TEN and the Owl. I will say it once and then about a thousand more times, if you have a question about policing, large black shepherds, or unbridled mode on a Mustang, pick up the phone – our police department is always happy to chat (this was reinforced by IPC Kelly). Remember that both of these two officers have been here in Weston for 22 years–and are every bit members of the community. 

So, first of all, let’s take a look at the contents of the “2020 Uniform Citation Data Analysis Report” (okay, I cry uncle on the acronym. Hereafter, “the report”).  This report includes collected data from all law enforcement citations issued, including demographics of the stopped motorist (gender, age, race/ethnicity) and information about the stop (the traffic infraction, the date and time of offense, whether the stop resulted in warning, citation or arrest). Because the law took effect on February 23, 2020, the time period included is not a full-year, but February 23-December 31, 2020. 

According to the report introduction: “the overall goal of this study is to learn more about potential patterns of racial disparities in traffic stops and understanding the causes of these disparities. It is not supposed to be an “answer” but an opening to further discussion and awareness.” Or as Appendix A of the report so aptly worded it: “The analyses contained in this report cannot be used as either absolute proof that a law enforcement agency engaged in racially-biased conduct or vice versa. Instead they serve as a starting point for reflection and further learning and discussion.”

Page 327 of report

You will note that of the 306 stops in Weston in the time period, 82.7% of them were “passing through” and 17.3% were intown (resident zip code). As a comparison, Massachusetts has 67.9% of stops as intown motorists, and 32.1% passing through. The way I read this is that Weston Police are pretty busy on our major passthrough roads- Route 20, Route 30 and Route 117. Maybe the north-souths at Highland and Wellesley, Church Street, and on the Boston Post Road. I would also say that I am not sure this percentage is so relevant in the very weird year of 2020–many of us were hardly going out unless we had to.

In Weston, there were 33.9 stops per 1000 residents (18+) while the state stop rate was 36.9. We are solidly average here. The mean age for all stops in Weston is 38.4 (state is 37.2), gender breaks 37.5% female, 62.5% male (state is 34% female, 65% male, rest nonbinary). For race, the Weston breakdown is 7.7% African American/Black, 9.1% Hispanic, 71.4% White, 11.8% Other. If you look at that as compared to our town demographics (see Comparative Analyses), you will see a higher rate of blacks and hispanic stops versus demographics, while White and Other show fewer stops compared to demographics. What does that mean? Well, that is for discussion. Again, officers are the ones who mark race/ethnicity on the traffic stops while demographics are self-reported in the census. There is some natural non-agreement there.

Intertwilight on the soccer field.

One of the more interesting parts of the study is in the analysis of the “Intertwilight (ITP)” stops –these are stops in the dawn ITP period (4:35 am- 7:16 am) and dusk ITP times (4:14pm-9:02 pm) which coincidentally occur at major morning and evening commute times. Not sure why they don’t just call it dusk and dawn but no one asked me. The gloaming perhaps. Ready for some chi-square analysis? Well, you’re on your own. The Veil of Darkness (VoD) Analysis shows racial breakdown (just White and Non-White now to get statistical significance) in the ITP period. This compares stops made during the day when it is light to those made at night when it is dark–which could show disparities when officers can more easily determine the race/ethnicity of the driver. The underlying assumption here, as stated in the report, is that if law enforcement officers are profiling motorists, they are better able to do it in daylight hours when race is more easily observed. 

Now, as you can tell, things are getting mathy–which means the Owl is getting her feathers ruffled. The bottom line is that on the “all stops” side of the coin, there is no statistical significance (which means the numbers could be chance alone). The ITP stops side does show statistical significance and by my HIGHLY ADVANCED MATH (HAM) capabilities, it shows that Non-Whites are less likely to be stopped in daylight than in darkness (1.000-.391=.609 or 61% less likely to be stopped in daylight than in darkness). The data show no evidence of racial profiling. If you can find evidence here, let me know. Please use very few numbers.

Now onto the part that gets wiggly, my friends: Traffic Stop Outcomes by Race. Before looking too closely, it behooves (be-talons?) the Owl to point out that some traffic stops REQUIRE citations to be issued–these are reasons such as driving on a suspended license or driving a non-registered vehicle. There is no officer discretion on these infractions–they must issue a ticket. IPC Kelly confirmed this point today–if an officer notes one of these bigger infractions, he or she MUST cite it or that would be dereliction of duty (one of my favorite phrases). This point is incredibly important–because it takes subjectivity out of the situation. If we must, we must. 

Interim Police Chief Kelly explained that Weston police officers, while required to cite in suspended license cases, do not often arrest (except in extreme cases) or tow.  The officers have no discretion as far as letting the unlawful act continue (i.e., let the operator drive away with no license).  In most cases, though, the operator is given a chance to call a friend or family member to pick them up. 

Some stops do not require a citation but are rather officer discretion (such as use of seat belts, equipment failure like tail lights). 

While the report for Weston shows that there is no pattern to the racial disparity, there was one number that very much bothered the Owl.  African American/Black, White and Other hover in the 70 percentage points for Warnings, but Hispanic is down in the 48% zone, and up to 30% in Criminal. What’s going on there? IPC Kelly had the answer for me. Of the 8 criminal outcome stops for Hispanics, 5 were actually incoming calls to the station and not officer-led stops. The criminal citations were results of suspended or unlicensed drivers–and the Weston police were called in; they did not initiate the stop.

The new ‘stang, in Bridled and Stationary mode. Photo credit: Weston Police

This fact brings up the number of limitations to the analysis, and reminds us all that we need to look behind the summaries. Some of the biggest limitations I note in the study are: 

1-The study was held from February 23, 2020-December 31, 2020. It includes only a partial year of reporting, and of course it was a year of non-normal traffic patterns because of the pandemic.  In speaking with Interim Police Chief Kelly and Lt. Forti, the 306 stops in Weston (and by the way, Weston keeps records much more detailed that the ones in the state report) are way under the “usual” number of stops. Future years may be more representative.

2-The Massachusetts Registry of Motor Vehicles does not collect info on race/ethnicity and therefore it is not on drivers’ licenses. Because of this, motorist race/ethnicity is determined by officer’s perception–no, they don’t ask, hey are you Hispanic or Latino? As we all know, Hispanic is not a race, and one does get tired of it being termed as such. In addition, the state makes no effort to break out “other” beyond the simple “if you are not White, Black/African American or Hispanic, you are “Other.” I see a major issue here. Just to give one example– there are Brazilians of Japanese descent, Brazilians of African heritage, and then Brazilians who are “White” from Italian descent, or Lebanese descent, but then are they “White”? In other words, by dint of the categories allowed by the state, the officer does his or her best to categorize. That is one of the most subjective data points I have seen on a study. 

3-Regarding “stop outcomes” of warning, civil, criminal, etc. there is no breakdown between officer stops and calls that are made to the station requesting assistance. For example, some could be calls to the station requesting assistance because the driver in an accident was unlicensed/suspended. I do not think an officer can be accused of a racial profiling stop if they in fact were called in post-stop. 

4-Verbal warnings are not included in the data (but, I should note, the Weston Police Department records ALL stops, they just don’t report the verbal warnings because they are nice that way).

5-Updated February 12. Since 83% of the stops are “pass-through” motorists, it’s unclear what the value is of comparing our town’s demographics with the stop demographics.

While I think this first traffic stop study was interesting, I am personally not sure how accurate it can be given the pandemic and some of the limitations of the “race buckets.”  There is a lot more behind these numbers, and as I have said, the police are always willing to discuss it (barring privacy issues). Perception is not always reality, and the stories behind numbers are pretty important. Keep looking at the fine print.  

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