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Computer model helps California cops prevent crime

A new computer model in California may be able to help police officers target their patrols toward criminal "hot spots" in Riverside. The model, which was developed by the University of California, Riverside, can help police identify areas in which crimes such as robbery are most likely to occur. The use of the model has helped decrease thefts in the area by about 8 percent during the first three quarters of this year, according to local authorities.

This predictive crime software uses statistics to identify locations where theft is more likely to occur. As a result, police officers are able to employ prevention strategies in those areas, instead of arresting people after they have committed the crime.

Several unexpected results have helped officers learn more about crime trends, especially among young people in the area. After a decade of data was analyzed, a geographic representation of truancy was found to coincide with an increase in burglary. As truancy arrests increased in an area, the burglary rate would also experience a delayed rise, perhaps after one or two years. Instead of allowing that young population to turn to property theft, police officers can implement interventions that would dissuade truants from turning to a life of crime.

This is a positive move for the community according to experts because it will allow for weekly updates to criminal activity trends. The change could affect the number of defendants who are arrested for more serious crimes, promoting safer neighborhoods through community development and outreach.

Young people deserve second chances even after they have been arrested for robbery or truancy. Criminal defense experts say that young defendants can often be successfully rehabilitated. Crime models such as the one in Riverside could reduce the incidence of juvenile property theft, ultimately leading to a better life for everyone in the community.

Source: www.upi.com, "Police turn to computers to anticipate crime hot spots" No author given, Nov. 04, 2013

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