'Near Repeat' Theory into a Geospatial Policing Strategy: A Randomized Experiment Testing a Theoretically-Informed Strategy for Preventing Residential Burglary, Baltimore County, Maryland and Redlands, California, 2014-2015 (ICPSR 37108)

Version Date: May 30, 2019 View help for published

Principal Investigator(s): View help for Principal Investigator(s)
Elizabeth (Elizabeth R.) Groff, Temple University; Travis Taniguchi, Research Triangle Institute; Police Foundation (U.S.)

https://doi.org/10.3886/ICPSR37108.v1

Version V1

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These data are part of NACJD's Fast Track Release and are distributed as they were received from the data depositor. The files have been zipped by NACJD for release, but not checked or processed except for the removal of direct identifiers. Users should refer to the accompanying readme file for a brief description of the files available with this collection and consult the investigator(s) if further information is needed.

This data collection represents an experimental micro-level geospatial crime prevention strategy that attempted to interrupt the near repeat (NR) pattern in residential burglary by creating a NR space-time high risk zone around residential burglaries as they occurred and then using uniformed volunteers to notify residents of their increased risk and provide burglary prevention tips. The research used a randomized controlled trial to test whether high risk zones that received the notification had fewer subsequent burglaries than those that did not. In addition, two surveys were administered to gauge the impact of the program, one of residents of the treatment areas and one of treatment providers.

The collection contains 6 Stata datasets:

  1. BCo_FinalData_20180118_Archiving.dta(n = 484, 8 variables)
  2. Red_FinalData_20180117_Archiving.dta (n = 268, 8 variables)
  3. BCo_FinalDatasetOtherCrime_ForArchiving_v2.dta(n = 484, 8 variables)
  4. Redlands_FinalDataSecondary_ForArchiving_v2.dta (n = 266, 8 variables)
  5. ResidentSurvey_AllResponses_V1.4_ArchiveCleaned.dta (n = 457, 42 variables)
  6. VolunteerSurvey_V1.2_ArchiveCleaned.dta (n = 38, 16 variables)
The collection also includes 5 sets of geographic information system (GIS) data:
  1. BaltimoreCounty_Bnd.zip
  2. BC_NR_HRZs.zip
  3. BurglaryAreaMinus800_NoApts.zip
  4. Redlands_CityBnd.zip
  5. RedlandsNR_HRZs.shp.zip

Groff, Elizabeth (Elizabeth R.), Taniguchi, Travis, and Police Foundation (U.S.). “Near Repeat” Theory into a Geospatial Policing Strategy: A Randomized Experiment Testing a Theoretically-Informed Strategy for Preventing Residential Burglary, Baltimore County, Maryland and Redlands, California, 2014-2015. Inter-university Consortium for Political and Social Research [distributor], 2019-05-30. https://doi.org/10.3886/ICPSR37108.v1

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United States Department of Justice. Office of Justice Programs. National Institute of Justice (2012-IJ-CX-0039)

Geocoded street location

Access to these data is restricted. Users interested in obtaining these data must complete a Restricted Data Use Agreement, specify the reason for the request, and obtain IRB approval or notice of exemption for their research.

Inter-university Consortium for Political and Social Research
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2014 -- 2015
2014-09-10 -- 2015-12-31
  1. These data are part of NACJD's Fast Track Release and are distributed as they were received from the data depositor. The files have been zipped by NACJD for release, but not checked or processed except for the removal of direct identifiers. Users should refer to the accompanying readme file for a brief description of the files available with this collection and consult the investigator(s) if further information is needed.

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The purpose of this study was to test the efficacy of swift resident notification for preventing subsequent burglaries within near repeat high risk zones (NR-HRZ). Research questions included:

  • What is the spatial and temporal extent of near-repeat burglary in the jurisdictions?
  • Does providing crime prevention material quickly after a burglary reduce the number of burglaries that occur in the near-repeat-high-risk zone over the near-repeat-high-risk period and beyond?
  • What impact does notification of increased risk have on actions taken by residents and their perception of safety?
  • What are the impacts of participating in the study on treatment providers?

The experiment was conducted in Baltimore County, Maryland and Redlands, California. As residential burglaries came to the attention of the police, a trickle randomization process was used to assign each micro-level near repeat high risk zones (NR-HRZ) (measured 800 feet, 244 meters from the burglary location) and associated buffer (400 feet, 122 meters) to treatment or control. Treatment was performed by uniform agency volunteers and consisted of swift notification to residents in the area of increased risk of burglary victimization. Treatment and control zones were compared for differences in the mean count of residential burglary using independent sample t-tests. Two surveys were administered to gauge the impact of the program, one targeted residents and one targeted the treatment providers.

For the non-survey data: Each day the previous day's reported burglaries were assessed for inclusion in the study based on whether a suitable near repeat high risk zone could be created for it.

For the survey data: All treatment providers were invited to respond to their survey. The first wave of the resident survey targeted a sub-sample of treatment zone residents, and the four subsequent waves targeted all residents of those zones.

Cross-sectional

Residential burglaries in Baltimore County, Maryland and Redlands, California

Near repeat high risk zones

The data file BCo_FinalData_20180118_Archiving.dta (n = 484, 8 variables) contains variables related to the number of burglaries in Baltimore County, Maryland near repeat high risk zones after assignment to treatment or control.

The data file Red_FinalData_20180117_Archiving.dta (n = 268, 8 variables) contains variables related to the number of burglaries in Redlands, California near repeat high risk zones after assignment to treatment or control.

The data file BCo_FinalDatasetOtherCrime_ForArchiving_v2.dta (n = 484, 8 variables) contains variables related to the number of non-burglary property crimes in Baltimore County, Maryland near repeat high risk zones after assignment to treatment or control.

The data file Redlands_FinalDataSecondary_ForArchiving_v2.dta (n = 266, 8 variables) contains variables related to the number of non-burglary property crimes in Redlands, California near repeat high risk zones after assignment to treatment or control.

The data file ResidentSurvey_AllResponses_V1.4_ArchiveCleaned.dta (n = 457, 42 variables) contains information collected in the resident survey, such as type of home, any previous experience of burglary, and experience with the treatment intervention.

The data file VolunteerSurvey_V1.2_ArchiveCleaned.dta (n = 38, 16 variables) contains information collected in the treatment provider survey, such as number of treatment deliveries and various opinions on the effectiveness of the program.

The data file BaltimoreCounty_Bnd.zip contains a boundary polygon for Baltimore County, Maryland.

The data file BurglaryAreaMinus800_NoApts.zip contains a boundary polygon for Baltimore County, Maryland omitting apartment parcels.

The data file Redlands_CityBnd.zip contains a boundary polygon for Redlands, California.

The data file BC_NR_HRZs.zip contains information such as line features showing street segments in each treatment target area, as well as dates relating to burglary incidents and allocation to treatment.

The data file RedlandsNR_HRZs.shp.zip contains information such as line features showing street segments in each treatment target area, as well as dates of burglary incidents.

Resident survey: 5.57% in Baltimore County and 7.23% in Redlands

Treatment provider survey: 31.3% (responses from both sites aggregated for analysis)

None

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2019-05-30

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Notes

  • These data are part of NACJD's Fast Track Release and are distributed as they were received from the data depositor. The files have been zipped by NACJD for release, but not checked or processed except for the removal of direct identifiers. Users should refer to the accompanying readme file for a brief description of the files available with this collection and consult the investigator(s) if further information is needed.

  • The public-use data files in this collection are available for access by the general public. Access does not require affiliation with an ICPSR member institution.

  • One or more files in this data collection have special restrictions. Restricted data files are not available for direct download from the website; click on the Restricted Data button to learn more.