Jacksonville Sheriff John Rutherford said that kind of assessment is an essential part of fighting crime.
"That's where I wanted us to go in 2003, because I knew at that point we had to start using data to fight crime," he said. "And you couldn't just go in and saturate an area and expect that crime was going to go down. It doesn't work that way. We've done that before."
Other elements, from solving community problems to following criminals when they move, are critical to get a jump on crime.
"Now this provides an opportunity to possibly predict where it is going to go and if they can do that, that would be excellent," he said.
The research, categorized as predictive analysis, is an area of wide interest now, said Joe Ryan, the Jacksonville Sheriff's Office crime analysis administrator.
Ryan's unit does some of that now, collecting information including vacant housing numbers to bus stops and shopping center locations, then applying that to other parts of the city that are similar in makeup.
"It's community data, it's other types of data that we can look at in relation to crime events and come up with our own types of models," Ryan said.
Social patterns, conditions
The work being done at UCLA is intriguing, but the next step will be critical, he said.
It is important that the research, which is based on data from Los Angeles and Long Beach police departments, can be replicated in other cities, Ryan said.
"The academics who wrote this need to do this in other jurisdictions to prove that this is something that will work universally," he said.
At the heart of the system is the development of mathematical formulas that fold social patterns of criminals and victims together with other conditions to show whether an area is a brew pot for crime.
By digging deeply into the data, the system improves on a long-standing approach that uses historical information about past crimes to predict where criminals are apt to hit next.
Crimes are classified into two types of hot spots Brantingham called subcritical and supercritical hot spots.
Neighborhoods known for open drug dealing fall into the subcritical range that can be dealt with by a hefty police presence to knock down the activity. Brantingham said it is more likely the drug activity will at least take time to re-emerge at high levels in those cases.
By contrast, activities such as burglaries and auto thefts fall into the supercritical range because they will move from one area to another part of a city, according to an explanation of the research published in the March issue of the Proceedings of the National Academy of Sciences.
Predicting what kind of hot spot is developing could mean savings to law enforcement agencies already stretching dollars to put cops on the street in the places they are most needed.
The premise is that both criminals and victims move in predictable ways that can be used to predict where crimes may happen.
Careful not to profile
Some of that research could show promise, said Clay County Sheriff Rick Beseler, but he sees possible concerns.
Looking at patterns of people's behavior in a particular community and not past conduct could raise issues of profiling, he said.
Studying how people act amounts to "profiling what you might do as opposed to what you have done," he said.
Brantingham said profiling isn't an issue because the focus is not on individuals but on places and general behavior patterns, not such things as race or poverty.
"The components the model works with are the same from one area to another," he said.
By looking at crime problems before they evolve, police can decide what resources to use.
"This is exactly the sort of way you would hope policing would move to in the 21st century," he said.
Craig Uchida, a former executive at the U.S. Department of Justice and professor of criminology at the University of Maryland, is president of a Washington, D.C., consulting firm working with Brantingham to promote the project.
Uchida said the research also can help provide a snapshot of neighborhoods and how they will evolve.
"To me this level of work can show how bad neighborhoods are going to be," he said.
He said the key to the work is using past patterns to predict the future rather than relying on those patterns he called "putting dots on a map" to show where things are already bad.
"It's a lot of 'this is what happened last week, this is what happened last month,'" he said. |
