Detection of Crime, Resource Deployment, and Predictors of Success: A Multi-Level Analysis of CCTV in Newark, New Jersey, 2007-2011 (ICPSR 34619)
The Detection of Crime, Resource Deployment, and Predictors of Success: A Multi-Level Analysis of Closed-Circuit Television (CCTV) in Newark, NJ collection represents the findings of a multi-level analysis of the Newark, New Jersey Police Department's video surveillance system. This collection contains multiple quantitative data files (Datasets 1-14) as well as spatial data files (Dataset 15 and Dataset 16). The overall project was separated into three components:
- Component 1 (Dataset 1, Individual CCTV Detections and Calls-For-Service Data and Dataset 2, Weekly CCTV Detections in Newark Data) evaluates CCTV's ability to increase the "certainty of punishment" in target areas;
- Component 2 (Dataset 3, Overall Crime Incidents Data; Dataset 4, Auto Theft Incidents Data; Dataset 5, Property Crime Incidents Data; Dataset 6, Robbery Incidents Data; Dataset 7, Theft From Auto Incidents Data; Dataset 8, Violent Crime Incidents Data; Dataset 9, Attributes of CCTV Catchment Zones Data; Dataset 10, Attributes of CCTV Camera Viewsheds Data; and Dataset 15, Impact of Micro-Level Features Spatial Data) analyzes the context under which CCTV cameras best deter crime. Micro-level factors were grouped into five categories: environmental features, line-of-sight, camera design and enforcement activity (including both crime and arrests); and
- Component 3 (Dataset 11, Calls-for-service Occurring Within CCTV Scheme Catchment Zones During the Experimental Period Data; Dataset 12, Calls-for-service Occurring Within CCTV Schemes During the Experimental Period Data; Dataset 13, Targeted Surveillances Conducted by the Experimental Operators Data; Dataset 14, Weekly Surveillance Activity Data; and Dataset 16, Randomized Controlled Trial Spatial Data) was a randomized, controlled trial measuring the effects of coupling proactive CCTV monitoring with directed patrol units.
Over 40 separate four-hour tours of duty, an additional camera operator was funded to monitor specific CCTV cameras in Newark. Two patrol units were dedicated solely to the operators and were tasked with exclusively responding to incidents of concern detected on the experimental cameras. Variables included throughout the datasets include police report and incident dates, crime type, disposition code, number of each type of incident that occurred in a viewshed precinct, number of CCTV detections that resulted in any police enforcement, and number of schools, retail stores, bars and public transit within the catchment zone.
Evaluation of the Community Supervision Mapping System for Released Prisoners in Rhode Island, 2008-2010 (ICPSR 32004)
National Law Enforcement and Corrections Technology Center's (NLECTC) Information and Geospatial Technology Center of Excellence (COE), [United States], 2014 - 2015 (ICPSR 36224)
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 study includes data collected with the purpose of determining the geospatial capabilities of the nation's law enforcement agencies (LEAs) with regards to the tools, techniques, and practices used by these agencies.
The collection includes two Excel files. The file "Geospatial Capabilities Survey Data To NACJD V2.xlsx" provides the actual data obtained from the completed surveys (n=311; 314 variables). The other file "Coding Scheme.xlsx" provides a coding scheme to be used with the data.
Police Arrest Decisions in Intimate Partner Violence Cases in the United States, 2000 and 2003 (ICPSR 31333)
Space-time Study of Youth and School Violence - STARS for Schools, Philadelphia, Pennsylvania, 2018-2020 (ICPSR 38014)
School violence, including violence en route to and from school, can make students afraid to go to school and frequently results in serious injury. These assaults occur in a context where the landscape that students navigate each day often includes bullying, substance use, and weapon carrying. Understanding the locations and times when students are vulnerable to assault as they proceed through their school-day routine could identify opportunities for more targeted, evidence-based prevention strategies.
The research team employed a mixed-methods, case-time-control design with GIS-assisted activity path mapping to understand risk factors and protective factors for school assault in the United States. Children aged 12-18 years requiring treatment at the emergency department of The Children's Hospital of Philadelphia (Philadelphia, Pennsylvania) for an assault-related injury, or who attended Philadelphia schools serving as recruitment sites during the study period, were recruited for the study (n=63). Participants were interviewed using a survey questionnaire and GIS technology to recreate details of the path of their activities, indoors during school and outdoors before and after, from the time they awoke in the morning up until the time they were assaulted. In addition, participants were asked to describe their activities sequentially during that period, including companions and weapon carrying, and site-line features of each location (prospect, refuge, and escape). To include individual- and environmental-level context, participants' paths were appended with data characterizing streets, buildings, neighborhood populations, and the weather that day.
This collection contains data from the quantitative survey measures (DS1) and qualitative interview transcripts (DS2) from the path mapping section of the interview. While GIS data were collected, they were not deposited to ICPSR. Qualitative data will be released at a future date.