Abstract
Street gangs continue to plague the nation. One focus of current gang prevention efforts is to strive to reduce the number of potential members recruited by local street gangs and to advocate for more resources to promote healthy communities. This research outlines the use of analytical modeling and decision analysis to aid in identifying potentially “at-risk” children likely to join a street gang. As an illustrative example, we use data developed from a particular Ohio county. We examine multiple demographic measures and, based on these data, identify children potentially at risk for gang membership. A stronger means of identification of at-risk children can lead to a more efficient placement of resources to reduce the number of street gang recruits. We then take a similar approach to identify communities in the same Ohio county at risk for increased incidence of youth gang membership. This analysis can support public policy decision making regarding social investments for gang prevention efforts. While developed for a specific county, the approaches can be modified and extended to different locales.
The views expressed in this chapter are those of the author and do not reflect the official policy or position of the United States Air Force, Department of Defense or the United States Government.
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Acknowledgments
The authors wish to thank the decision maker and subject matter experts for the time and effort they expended on this study. It would not have been possible without their assistance. We also wish to thank the editor and reviewers for their insightful comments.
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Appendices
Appendix A: Individual Single Dimension Value Functions
This appendix includes the plots of the single-dimension value functions (SDVFs) developed in this study for the individual at-risk child. An SDVF is a monotonically increasing or decreasing function for each measure used to convert a measure’s score on the x-axis to a value on the y-axis, denoted by v(x). The purpose of the SDVF is to provide a value of a measure, typically between 1.0 and 0.0, based on the score given by the decision maker (Kirkwood, 1997, p. 68). These value functions may be discrete, including categorical functions, piecewise linear, or continuous. Each measure was developed based on the literature review and discussions with the subject matter experts (SME). Each evaluation measure was also reviewed and approved by the decision maker (DM) and SMEs; SDVFs were then created and approved for each evaluation measure. A higher value score implies a higher risk for the individual. While these SDVFs are robust and should be extendable to other communities, they do represent the opinions of the SMEs and community used in the study. Before they are applied in a different setting, the measures and the weighting should be reviewed for their appropriateness in the community in question (Figs. A1–A12).
Value hierarchy for identifying potentially at-risk children
Income SDVF – individual
Drug charges SDVF – individual
Nondrug charges SDVF – individual
Affiliation SDVF – individual
Peers in gangs SDVF – individual
Extracurricular activities SDVF – individual
Crime rate SDVF – individual
Number of gangs SDVF – individual
Presence of abuse SDVF – individual
Family type SDVF – individual
Structure change SDVF – individual
Appendix B: Summary of Community Single-Dimension Value Functions (Table 9.5)
This appendix includes the plots of the single-dimension value functions developed in this study for the communities at risk. Each measure was developed based on the literature review and discussions with the subject matter experts (SMEs). Each evaluation measure was also reviewed and approved by the decision maker (DM) and SMEs; SDVFs were then created and approved for each evaluation measure. A higher value score implies a higher risk for the community. While these SDVFs are robust and should be extendable to other communities, they do represent the opinions of the SMEs and community used in the study. Before they are applied in a different setting, the measures and the weighting should be reviewed for their appropriateness in the community in question (Figs. B1–B11).
Value hierarchy for identifying potentially at-risk communities
Community average income SDVF – community
Percent household in community with drug charges
Percent of children in the community with a nondrug charge
Percent household in community with at least one gang member
Percent of school children in community in a street gang
Number of youth programs per 1,000 children in community
Number of street gangs in community
Percent of crime rate in community by street gangs
Number of abuse reports per 1,000 children in community
Percent of households in community with single parent or less
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Loeffelholz, B.J., Deckro, R.F., Knighton, S.A. (2012). Street Gangs: A Modeling Approach to Evaluating “At-Risk” Youth and Communities. In: Johnson, M. (eds) Community-Based Operations Research. International Series in Operations Research & Management Science, vol 167. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-0806-2_9
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