The Source for Crime and Justice Data

Gangs in Rural America, 1996-1998 (ICPSR 3398)

Principal Investigator(s):

Summary:

This study was undertaken to enable cross-community analysis of gang trends in all areas of the United States. It was also designed to provide a comparative analysis of social, economic, and demographic differences among non-metropolitan jurisdictions in which gangs were reported to have been persistent problems, those in which gangs had been more transitory, and those that reported no gang problems. Data were collected from four separate sources and then merged into a single dataset using the county Federal Information Processing Standards (FIPS) code as the attribute of common identification. The data sources included: (1) local police agency responses to three waves (1996, 1997, and 1998) of the National Youth Gang Survey (NYGS), (2) rural-urban classification and county-level measures of primary economic activity from the Economic Research Service (ERS) of the United States Department of Agriculture, (3) county-level economic and demographic data from the County and City Data Book, 1994, and from USA Counties, 1998, produced by the United States Department of Commerce, and (4) county-level data on access to interstate highways provided by Tom Ricketts and Randy Randolph of the University of North Carolina at Chapel Hill. Variables include the FIPS codes for state, county, county subdivision, and sub-county, population in the agency jurisdiction, type of jurisdiction, and whether the county was dependent on farming, mining, manufacturing, or government. Other variables categorizing counties include retirement destination, federal lands, commuting, persistent poverty, and transfer payments. The year gang problems began in that jurisdiction, number of youth groups, number of active gangs, number of active gang members, percent of gang members who migrated, and the number of gangs in 1996, 1997, and 1998 are also available. Rounding out the variables are unemployment rates, median household income, percent of persons in county below poverty level, percent of family households that were one-parent households, percent of housing units in the county that were vacant, had no telephone, or were renter-occupied, resident population of the county in 1990 and 1997, change in unemployment rates, land area of county, percent of persons in the county speaking Spanish at home, and whether an interstate highway intersected the county.

Access Notes

  • These data are freely available.

Dataset(s)

Dataset - Download All Files (1.6 MB)
Documentation:
Data:

Study Description

Citation

Weisheit, Ralph A., and L. Edward Wells. GANGS IN RURAL AMERICA, 1996-1998. ICPSR version. Normal, IL: Illinois State University, Dept. of Criminal Justice [producer], 2001. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2002. http://doi.org/10.3886/ICPSR03398.v1

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Export Citation:

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Funding

This study was funded by:

  • United States Department of Justice. Office of Justice Programs. National Institute of Justice (99-IJ-CX-0036)

Scope of Study

Subject Terms:   demographic characteristics, economic indicators, gang members, gangs, police response, rural areas, rural crime, social indicators

Geographic Coverage:   United States

Time Period:  

  • 1996--1998

Date of Collection:  

  • 1999

Unit of Observation:   Police agencies and their associated jurisdictions.

Universe:   All police agencies included in the National Youth Gang Survey (NYGS) sample that provided usable responses to the NYGS survey.

Data Types:   survey data, and administrative records data

Data Collection Notes:

The user guide, codebook, and data collection instruments are provided by ICPSR as Portable Document Format (PDF) files. The PDF file format was developed by Adobe Systems Incorporated and can be accessed using PDF reader software, such as the Adobe Acrobat Reader. Information on how to obtain a copy of the Acrobat Reader is provided on the ICPSR Web site.

Methodology

Study Purpose:   The spread of youth gangs to non-metropolitan counties in the 1990s has been widely cited but difficult to document empirically and to interpret theoretically. The only gang data collection that utilizes a representative national sample, includes a substantial number of rural jurisdictions, and is collected annually is the National Youth Gang Survey (NYGS), conducted by the National Youth Gang Crime Center. NYGS is given to a near-census of urban or metropolitan police agencies and nationally representative samples of cities and counties in rural and non-metropolitan areas. These surveys show that gang problems are occurring in communities of all sizes and locations, although they are still most heavily concentrated in medium and large cities. There is currently no other dataset that is comparable in coverage or quality. The purpose of this study was to enable cross-community analysis of gang trends in all areas of the United States and to allow for between-community comparisons of when and where youth gang problems seem to develop. The study also permits a comparative analysis of social, economic, and demographic differences among non-metropolitan jurisdictions in which gangs were reported to have been persistent problems, those in which gangs had been more transitory, and those that reported no gang problems.

Study Design:   Data were collected from four separate sources and merged into a single dataset using the county Federal Information Processing Standards (FIPS) code as the attribute of common identification. The data sources include: (1) local police agency responses to three waves (1996, 1997, and 1998) of the National Youth Gang Survey (NYGS), (2) rural-urban classification and county-level measures of primary economic activity from the Economic Research Service (ERS) of the United States Department of Agriculture, (3) county-level economic and demographic data from the County and City Data Book, 1994, and from USA Counties, 1998, produced by the United States Department of Commerce, and (4) county-level data on access to interstate highways provided by Tom Ricketts and Randy Randolph of the University of North Carolina at Chapel Hill. Researchers constructed the dataset in seven steps. First, the base data file was extracted from the 1996 National Youth Gang Survey, a copy of which was obtained from the National Youth Gang Center. The researchers then extracted the organizational and locational attributes of the respondent agency and its policing jurisdiction, as well as selected variables representing a subset of the gang-related questions on the survey. Not all gang-related responses were included in this extraction, only those judged relevant to the research project that seemed plausibly and reliably measured by police respondent reports. Two modifications were made to the data extracted from the 1996 NYGS data file. The first involved a slight recode of the item indicating the presence of gangs in the agency's jurisdiction in 1996 to clearly distinguish between missing data and meaningful negative answers. Based on patterns of responses to other items in the survey (e.g., estimated number of gangs, estimated year in which gangs first appeared), non-responses were separated and coded distinctly from negative responses. Logical tests (using cross-tabulations with logically related items) were applied to ensure consistency and coherence of the recodes. The other modification involved manually adding county FIPS codes to the data records for municipal police agencies. County FIPS codes for a few agencies in Alaska and Hawaii could not be identified. These were excluded from the data file (since they involved small remote jurisdictions with substantial missing data on other items). Secondly, the edited 1996 NYGS data extract was merged with the rural taxonomy codes (commonly called the Beale codes) of the Economic Research Service of the United States Department of Agriculture. These codes indicate the metropolitan location of each county on a ten-category urban-to-rural continuum, reflecting the size of the urban population in the county and its proximity to large metropolitan centers. The appropriate Beale codes were matched with each police agency by using the county FIPS codes as a common identifying variable, and by using the ERS data file as a "lookup table." Thirdly, gang-related items from the 1997 NYGS were extracted and merged with the results of steps 1 and 2. To accomplish this, data records for county agencies and municipal agencies were divided into separate files, which were merged in separate operations using different key identifier variables. County-level agencies were merged by using the county FIPS codes, while municipal agencies were merged by using the place FIPS code that uniquely identified each municipality. Gang-related items extracted from the 1997 NYGS were essentially duplicates of the items used from the 1996 survey, plus an additional item about perceived gang trends during the previous year. These same procedures were repeated from the 1998 NYGS to combine its parallel gang-related items with those in the previously merged 1996-1997 data file. After items from all three waves of the NYGS had been merged, the data records for county and municipal agencies were recombined into a single overall data file. Next, several longitudinal gang-related variables were computed from the merged gang files to measure multi-wave trends and stability indexes. They combined parallel items from two or more of the NYGS files reported for the same police agencies. Subsequently, county-level data were extracted from two different data sources -- County and City Data Book, 1994, and USA Counties, 1998 -- both compiled and distributed by the United States Department of Commerce using data collected by the United States Census Bureau. Relevant county-level population, economic, and housing data were identified within each dataset. The identified variables were extracted and merged (using the county FIPS code) into a single data file containing data on the selected variables on all counties in the United States. Penultimately, after the separate gang surveys had been combined, the county-level census-based data were added to the merged three-wave gang data file by using the county FIPS code recorded for each agency (reflecting the county in which the agency was located). These census-based data provide quantitative measures of the social and economic community context for each agency. As a final step, county-level data on interstate highways were obtained from Tom Ricketts and Randy Randolph of the University of North Carolina at Chapel Hill. Data indicating the presence (or absence) of an interstate highway in each county of the United States were provided along with the county FIPS code and merged into the researchers' data file.

Sample:   inap.

Data Source:

self-enumerated questionnaires and official records

Description of Variables:   Variables include the FIPS codes for state, county, county subdivision, and sub-county, population in the agency jurisdiction, type of jurisdiction, and whether the county was dependent on farming, mining, manufacturing, or government. Other variables categorizing counties include retirement destination, federal lands, commuting, persistent poverty, and transfer payments. The year gang problems began in that jurisdiction, number of youth groups, number of active gangs, number of active gang members, percent of gang members who migrated, and the number of gangs in 1996, 1997, and 1998 are also available. Rounding out the variables are unemployment rates, median household incomes, percent of persons in county below poverty level, percent of family households that were one-parent households, percent of housing units in the county that were vacant, had no telephone, or were renter-occupied, resident population of the county in 1990 and 1997, change in unemployment rates, land area of county, percent of persons in the county speaking Spanish at home, and whether an interstate highway intersected the county.

Response Rates:   inap.

Presence of Common Scales:   inap.

Extent of Processing:  ICPSR data undergo a confidentiality review and are altered when necessary to limit the risk of disclosure. ICPSR also routinely creates ready-to-go data files along with setups in the major statistical software formats as well as standard codebooks to accompany the data. In addition to these procedures, ICPSR performed the following processing steps for this data collection:

  • Standardized missing values.
  • Checked for undocumented or out-of-range codes.

Version(s)

Original ICPSR Release:  

Version History:

  • 2002-07-30 Two related publications were added at the request of the principal investigators.

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