Last week, the San Francisco Bay Guardian published an article by Alex Emslie titled, Compstat vs. community policing.
In the article, Emslie notes that “District 5 Sup. Ross Mirkarimi
introduced a proposed ballot measure on June 7 that would require the
police chief to institute foot patrols in all districts and ask the
Police Commission to establish a written community policing policy.”
Mirkarimi’s proposal is one that, according to Emslie, is prompting “a
looming debate involving the mayor and his police chief, who favor the
high-tech yet impersonal CompStat model, and progressive members of the
Board of Supervisors who are pushing for a community-based,
cops-walking-beats blueprint for SFPD.”
In other words, the debate our supervisors will be having is one
that seeks to answer the question: Is data more useful than community
involvement when it comes to reducing criminal activity?
As I read the information about CompStat, which Emslie describes as
“computerized crime mapping software” that “emphasizes lowering a
city’s crime rate by centralizing authority, spotting statistical
trends, and targeting crime hot spots,” I couldn’t help but be reminded
of Don DeLillo’s novel, White Noise, when the main character is
told, after hearing that a few minutes spent outside may have exposed
him to harmful chemicals in the air, “You are the sum total of your
data. No man escapes that.”
The point of this scene in the book is in part to support DeLillo’s
notion that we aren’t simply sum totals of data–that even in an
increasingly technological age, we ourselves are human, and our central
humanity must not be ceded to machines. It seems from Emslie’s
article, though, that our police chief and Mayor Newsom want us to
believe that we are “the sum total of [our] data.”
Obviously, data is essential to our lives, and it does indeed help
us solve problems. In education, we need data on what our students do
or do not understand in order to teach them what they need to know. In
our daily lives, we rely on information about the weather, traffic
delays, transit problems in order to plan out what we will wear to work
and how we will get there.
But statistical data only gives a part of the picture, and if we’re
only looking at a part of the picture, we will fail in our endeavors to
change what that picture looks like–whether we’re talking about a
portrait of crime, our schools, or our transit system. Consider this
information, which Emslie quotes from “a 2003 study commissioned by the
national Police Foundation.”
The Foundation (after studying CompStat’s
use in three cities) came to the conclusion that “Compstat seemed to
engender a pattern of organizational response to crime spikes in hot
spots that was analogous to the Whack-a-Mole game found at fairs and
carnivals.” I can’t imagine anyone who would think it would be a good
idea for our approach to policing to resemble Whack-a-Mole, though the
metaphor is an apt one: Police look at the data from CompStat and then
use that information to act on trends.
If, for example, prostitution is spiking along Shotwell Street,
then police will react to that, presumably responding by patrolling the
area and making arrests, and the same goes for other types of crimes,
like theft and vandalism, that affect various neighborhoods throughout
the city.
On the one hand, this seems like a smart use of both human and
monetary resources: concentrate your efforts on the places that need
them most. But as the “whack-a-mole” analogy implies, any data-driven
approach to a problem results in a lack of understanding of an issue as
a whole.
We might know that theft is a problem in the Central District, but unless we know why it’s a problem, we will likely not see thefts decrease (despite the fact that the Central District Captain is pretty convinced that only two or three people are responsible for the widespread thievery there).
The same is true for other issues that plague our society. Here we are
in the year 2010, and we continue to worry about the achievement gap in
our schools that continues to reveal a disparity in success between
white and Asian students on one side and Latino and African American
students on the other. Without understanding and addressing the
institutional underpinnings that are responsible for that gap, though,
we won’t get any closer to closing it.
“Community policing,” the practice that emphasizes foot patrols that
allow officers to “develop relationships on their beats” and thereby
“lets the community help set law enforcement priorities,” seems, to me
at least, the policing approach that might allow us to understand the
“why” of crime rather than the simple “what, where, and how often” that
CompStat data offers. And if we start to understand the why, we might
actually prevent crime, rather than simply create a means for punishing it after the fact. Imagine that.
At the end of the article, Emslie informs readers that “The Board of
Supervisors will consider Mirkarimi’s measure and SFPD budget in July,
airing a debate that could continue on to the November ballot, when
voters would decide whether to maintain their faith in CompStat and the
SFPD or ask for more community policing and foot patrols.”
In using
CompStat, the SFPD seems be saying that you can’t escape “the sum total
of your data.” What we need to remember, however, is that statistics
do not provide us all the data we need; some of the most crucial
information can only be gleaned through human interaction–exactly the
kind of “data” that will determine how we proceed in ensuring the
safety of each of San Francisco’s districts.
