Post by Police on Dec 5, 2006 3:47:48 GMT -5
www.philly.com/mld/philly/news/local/16104571.htm?template=contentModules/printstory.jsp
University of Pennsylvania criminologist Richard Berk, a trained statistician, never met a data set he didn't like.
Now, using fresh data from the Philadelphia probation department, Berk and three colleagues have built an innovative model for predicting which troublemakers already in the system are most likely to kill or attempt a killing.
With the homicide rate in Philadelphia outpacing last year's by at least 7 percent, a computer model for "forecasting murder" is in the works, Berk said, to be delivered to the probation department in the new year, with clinical trials of the new tool to begin in the spring.
Initial research suggests the software-based system can make it 40 times more likely for caseworkers to accurately predict future lethality than they can using current practices.
The project is funded with a private grant and the software is in the public domain, so the product will be delivered to the city free.
"This will help stratify our caseload and target our resources to the most dangerous people," probation department director of research Ellen Kurtz said. "I don't care as much about [targeting] the shoplifter. I care a lot about the murderer, obviously."
Sociologists have produced hundreds of studies using discrete pieces of information about offenders to try to come up with the means to identify probationers most likely to commit future felonies.
But homicide, because it is a relatively rare event, has been very hard to predict. Of all probationers in Philadelphia, only about one in 100 will commit homicide. But for obvious reasons it is crucial to find that needle in the haystack, Berk said.
Though it is well known that the probability of becoming a killer falls off with age, especially between 18 and 30, Berk's innovation is that he uses the relatively new statistical technique called "step-function" analysis to show how fast and when the dropoffs occur.
"In reality the risk doesn't decline in a smooth, straight line" but falls precipitously at certain points for certain reasons, he said.
The tool works by plugging 30 to 40 variables into a computerized checklist, which in turn produces a score associated with future lethality.
University of Pennsylvania criminologist Richard Berk, a trained statistician, never met a data set he didn't like.
Now, using fresh data from the Philadelphia probation department, Berk and three colleagues have built an innovative model for predicting which troublemakers already in the system are most likely to kill or attempt a killing.
With the homicide rate in Philadelphia outpacing last year's by at least 7 percent, a computer model for "forecasting murder" is in the works, Berk said, to be delivered to the probation department in the new year, with clinical trials of the new tool to begin in the spring.
Initial research suggests the software-based system can make it 40 times more likely for caseworkers to accurately predict future lethality than they can using current practices.
The project is funded with a private grant and the software is in the public domain, so the product will be delivered to the city free.
"This will help stratify our caseload and target our resources to the most dangerous people," probation department director of research Ellen Kurtz said. "I don't care as much about [targeting] the shoplifter. I care a lot about the murderer, obviously."
Sociologists have produced hundreds of studies using discrete pieces of information about offenders to try to come up with the means to identify probationers most likely to commit future felonies.
But homicide, because it is a relatively rare event, has been very hard to predict. Of all probationers in Philadelphia, only about one in 100 will commit homicide. But for obvious reasons it is crucial to find that needle in the haystack, Berk said.
Though it is well known that the probability of becoming a killer falls off with age, especially between 18 and 30, Berk's innovation is that he uses the relatively new statistical technique called "step-function" analysis to show how fast and when the dropoffs occur.
"In reality the risk doesn't decline in a smooth, straight line" but falls precipitously at certain points for certain reasons, he said.
The tool works by plugging 30 to 40 variables into a computerized checklist, which in turn produces a score associated with future lethality.