Juvenile Delinquency
Essay by Guhan Wang • October 9, 2016 • Case Study • 5,491 Words (22 Pages) • 1,644 Views
BUS 354
Strategic Modeling and Social Dynamics 12 December 2013
Overview, Design Concepts, and Details (ODD) for the Effect of Policies on Juvenile Delinquency Rate within a Predefined Community Model
Group 6
Aiming Nie | Guhan Wang | Qi Wu
Table of Contents
- Executive Summary 3
- Purpose 4
- Method 5
- Results 11
- Discussion 18
- Reference 19
- Appendix 20
- Sensitivity Analysis 20
- Entity, State Variable 22
- Interface Design 23
- Process Overview and Schedule 25
- Design Concepts 27
Executive Summary
Our group is hired by a local government of a poor community in Georgia, which has experienced high juvenile delinquent rates over the past few years. Our client has an initial fund that is specifically devoted to control the high juvenile delinquent rate. They want an effective method to best utilize that fund.
Our group first identifies four possible investment methods based on an extensive study of academic literatures and the policies used by other communities. The four government options are: provide subsidy to families, increase police control in the community, invest in small to medium businesses, and invest in educational programs for juveniles. Then we build an agent-‐based simulation to test the effectiveness of each method. In our model, we take the major factors that contribute to juvenile delinquent behaviors into consideration and try to model the real environment of the community. The community status, a global variable that is influenced by the four options, describes the situation of the community. In addition, we assigned different attributes to each agent. These attributes are influenced by these global variables. In order to simulate our client’s real-‐world problem, the parameters in our model are chosen based on the conditions of a poor community. Having the effect of each factor, we can compute the delinquent likelihood for each agent. If an agent has high enough delinquent likelihood, he or she will commit a crime and increase the number-‐of-‐crimes by one. We record the total number-‐of-‐crimes in a 10-‐year time span and compute the crime rate for each year to evaluate the effectiveness of each government policy.
Because each run generates different results, we use BehaviorSpace, a parameter sweep function, to calculate the average number-‐of-‐crimes for each option. We tested different combinations, such as putting all the money on one investment option or having a balanced investment. As a result, we found that investing in police control is actually the most effective method in reducing the number-‐of-‐crimes in a poor community. According to the slope of “quarterly number of crimes” plot in our model, investing in police control is also the only effective way to reduce the crime rate over the years.
We also did two sensitivity analyses by controlling the population size and additional funding to see how sensitive are our results to the changes in parameters. Our model is not sensitive to the population size, which means it is also applicable to bigger communities. On the other hand, our model is very sensitive to additional funding, meaning that more funding could help to reduce the number-‐of-‐crimes substantially.
In conclusion, we suggest our client to invest the majority of the money on police control, such as increase the police crackdowns, community policing, police training and school police.
Purpose
A poor community in Georgia has been experiencing high juvenile delinquent rate over the past few years. The local government of that community came to us for suggestions to reduce the overall juvenile delinquent rate. Based on research journals about reducing crime and policies used in other counties, we came up with four government controls: provide subsidy to families, increase police control in the community, invest in small to medium businesses, and invest in educational programs for juveniles. However, we are not sure which is the most effective control for our client’s county since the same government control may have various effects in different counties.
Therefore, we decide to develop an agent-‐based simulation to explore the effects of different government controls on juvenile delinquency rate, therefore allow us to find the most effective government policy our client’s county. We think an agent-‐based model is particularly suitable in this case because it takes human interaction and adaptive learning into consideration, which is a more accurate simulation of the real life situation. The independent variable in our simulation is the four government controls we came up with. These government control options will have different effects on a juvenile’s personal stress, attachment to parents, exposure to delinquent peers, and other factors that will influence one’s decision of becoming delinquent or not. Therefore, the dependent variable is individual’s delinquency. We will calculate the annual crime rate of the community subsequent to government policy to evaluate the effectiveness of the government policy.
Our agent-‐based model uses Agnew’s book Juvenile Delinquency: Causes and Control as the major theoretical support. We also studied academic journals extensively when selecting our options, variables, and attributes. Our proposed four government options are designed to address the important aspects related to juvenile delinquency. The attributes of individual agents are selected based on the four major widely accepted theories explaining delinquent behaviors in sociology: strain theory, social learning theory, control theory and labeling theory. The attributes reflect these theories to different extend. The dynamics are based on assumption that different government options would influence various variables contributing to crime, and these variables would further affect the different attributes of individuals. A juvenile would commit delinquent behaviors when the sum of his or her attributes exceeds a certain amount.
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