Authors: Alina Ristea*, Boston Area Research Initiative (BARI), School of Public Policy and Urban Affairs, Northeastern University, Dan O'Brien, Boston Area Research Initiative (BARI), School of Public Policy and Urban Affairs & School of Criminology and Criminal Justice, Northeastern University, Forrest Hangen, Boston Area Research Initiative (BARI), School of Public Policy and Urban Affairs, Northeastern University
Topics: Urban Geography, Social Geography, Geographic Information Science and Systems
Keywords: problem properties, micro spatial analysis, crime and disorder, neighborhood
Session Type: Paper
Start / End Time: 1:45 PM / 3:00 PM
Room: Tower Court A, Sheraton, IM Pei Tower, Second Floor Level
Presentation File: No File Uploaded
Recent literature shows new evidence that even in high-crime neighborhoods crime clusters on specific street blocks, justifying policing tactics that focus on particular hotspots. A longitudinal study of crime in Seattle, Washington showed that half of all Seattle crime each year occurs on just 5-6 percent of the city's street segments, located in various areas of the city. However, there has been little existing work on crime and disorder at smaller scales (e.g., properties).
This paper will advance work on the micro spatial dynamics of crime by analyzing the prevalence of crime at the parcel (i.e., property) level. One of the questions raised is does the concentration of crime observed across parcels help to explain the disparities between neighborhoods? To answer this question: parcel typologies are created separately for residential and commercial land use for four 911 ecometrics (i.e., neighborhood characteristics) in the city of Boston: social disorder (e.g. panhandlers), private conflict (e.g., domestic violence), violence (e.g., fight) and guns (e.g., shooting). For example, one typology can include high amount of social disorder and private conflict while other typology can have majority of private conflict. In order to understand these typologies, we will consider spatial, social, economic and demographic explanatory variables. Moreover, the resulting typologies will be compared with problem properties designed by the Task Force from the City of Boston helping to define proactive measures for future interventions.