It was the summer of George Floyd that really shook my confidence in the police. Like most white kids, I was raised on the image of the friendly policeman -- if you ever have trouble, find a policeman (they were always men back then) and he will help you. But as more and more stories emerged... as more and more departments were revealed to have covered up, condoned, and even rewarded the most grotesque racism... and as I really listened to people of color talking about their own experiences, my childhood image was shaken.
I respect all of those lived experiences. They are real and true. At the same time, the thing that I can offer to help is data analysis. That's not a very splashy gift; sorry about that. But it's what I have, so it's what I bring.
One thing about data analysis is that you really can't do it in a vacuum, without context. It's not a machine, where you pour numbers in at the top and get crisp and unambiguous answers out the bottom. You have to know the thing you are analyzing, even before you start. For mean, that means starting at home, in neighborhoods and towns I know well.
Thanks to cooperation from the cities of Los Altos and Mountain View, I now have RIPA data from all their stops. I set out to look at the how often people of various races get stopped in these two towns. In order to keep everything fresh, I limited it to just 2023 so far; this data goes through the end of September.
It's worth looking at this data in two different ways. Reading across, we can see which races are stopped the most and the least. Reading vertically, we can see how Mountain View and Los Altos compare. Notice that the scales are different for the two cities.
As we might expect, there are more stops overall in Mountain View than Los Altos; it's a bigger town. Los Altos stops more White people than any other race; Mountain View stops more Hispanic/Latino(a) than any other race.
This makes sense in Los Altos -- there are more White people here than any other race. If both policing and criming are not racially-based, then we would expect the proportion of stops of each race to match the populations. If they don't match, then we have to suspect some bias.
Adjusting for the population
In order to look at stop rates on a per-capita basis, we need to know what that population is. As a first cut, we'll use the resident population of each town, by race. This is not quite as simple as it sounds. There are multiple sources on the web, none of which precisely agree. And populations are dynamic. Furthermore, "Hispanic/Latino(a)" is not a race; Latino people can be of many races. In order to come up with a population number that matches each race category in the RIPA data, we have to make some assumptions. By making some reasonable ones,* we can come up with this chart:
Out of 1000 White people in Mountain View, about 20 were stopped in the first 3 quarters of 2023. Out of 1000 Black people, about 100 were stopped. That's a pretty big difference.
It is also notable that the Los Altos police make many more stops per capita than the Mountain View police. There could be many reasons for this, but one clear implication is that Los Altos is spending relatively more resources on stops than Mountain View is.
The next level
One criticism of this analysis could be that using the resident population to find per-capita rates isn't the right thing to do. After all, many people come into Los Altos and Mountain View during the day to work, even if they live elsewhere. Perhaps the apparent differences in the chart above are because we aren't using the appropriate population numbers.
One way to address that question would be to look at the ratio of equipment violations to moving violations. The story would be like this: most moving violations, for things like speeding or illegal turns, are evident to officers from far away, before they know the race of the driver. On the other hand, equipment violations are much more likely to be "pretext stops." Pretext stops are when an officer pulls someone over for one reason (like an expired registration) but actually they suspect the driver of some other criminality. If there is racial bias in the pretext stops, we would see a higher ratio of equipment violations to moving violations for people of color.
Using a ratio allows us to get around the population problem. Whatever the population of drivers is, that population will be the same for both moving and equipment violations. We no longer need to know exactly what that population is.
Now this won't be perfect. There will be some times when the officer knows the race of the person before they pull them over for a moving violation. There will be some times when the officer doesn't know the race of a person they pull over for an equipment violation. And there may be confounding variables -- socioeconomic status can correlate with race, and also with how likely one is to have their car in perfect shape. So we can't come to any final conclusions from this, but we can use it as an arrow, to indicate direction.**
The pattern emerges once again. In Los Altos, for every 100 stops of White people for moving violations, there are about 20 stops for equipment violations. But for Black people, there are 90. The pattern in Mountain View is the same.
This data certainly lends plausibility to the idea that people of color are preferentially stopped for "equipment violations." Stories abound of Black folks being stopped on pretext violations, only because officers thought "they didn't belong in this neighborhood" or "looked suspicious."
I had hoped that those stories were just things that happened elsewhere, in big cities or in the South. But it looks like they may well be happening right here at home.
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* We started with the data at worldpopulationreview.com, then made some adjustments based on US Census data. Details can be found in the code
here.
**In addition, Mountain View and Los Altos use different fields to indicate the kind of violation. The definitions may not be exactly the same between cities.
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