Justice Models
These models and simulations have been tagged “Justice”.
These models and simulations have been tagged “Justice”.
Justice Reinvestment in Bourke
A simple model of the township Bourke, showing the effects of community engagement within the youth population.
In-depth Explanation
This model uses the youth of Bourke and their temptation to commit crimes. These crimes are usually committed out of boredom and generally include: Breaking and entering, stealing, vandalism etc. The model depicts that the increase of police presents means that will be an increase of youths caught and convicted whilst also providing in the reduction in the temptation to commit a crime. Those youths that are caught and convicted are sent to juvenile detention where they undertake rehabilitation. Depending on this rehabilitation youths will either be released back into the community where they may attend school or youth activities or become bored again and re-commit or released back into a life of crime pending unsuccessful rehabilitation.
Taking into consideration the Justice Reinvestment plan some of the funds used to increase policing will be used instead to improve community development. This has a knock on effect on crime as there will be better youth activities running to keep youths engaged and free of boredom. This keeps youths out of juvenile detention and also encourages them to go to school.
School attendance also has an effect on the temptation to commit a crime, if a youth is attending school then they are less likely to be out and about committing crimes. It was noted by Bourke High school Annual report 2012 that their attendance was a little over 60%.
Upon simulation there are a number of graphs that have been generated, these include Crime & Detention, Crime vs School, Crime vs Youth Activities, Town, Detention & Youth Engagement and School vs Youth Activities. These graphs along with the variable sliders show what sort of impact increase and decreasing the variable will have on the town and the youth’s rate of crime and detention. These graphs can then be used to make a informed decision on where it’s best to spend the money of the Justice Reinvestment plan.
Variables
Assumptions
Initial values
Underlying assumptions:
Constants:
Things to note:
Initial values:
Youth in town: 1200.
Criminals: 100.
Juvenile Detention: 100.
Violent families: 300
Detected violent families: 100.
Portions
Government statistics from the Australian Bureau of Statistics (ABS) show that Bourke Shire Regional Council has approximately 3000 residents, made up of 65-63% adults and 35-37% youths.
Crime Rate
Police variable is in the denominator to create a hyperbolic trend. The aim was to achieve a lower crime rate if police expenditure was increased, thus also a higher crime rate if police expenditure was decreased. The figure in the numerator can be changed with the ‘maximum crime rate’ variable which represents the asymptotic crime rate percentage. Where police = 100 the selected crime rate is maximised.
Avoiding Gaol
Originally the formula incorporated the police as a variable, where the total amount of convicted crimes was subtracted from the total amount of crimes committed. However, the constant flow of crimes from repeat offender/a created an unrealistic fluctuation in the simulation. I settled for a constant avoidance rate of 25%. This assumes that an adult or youth committing a crime for the first time is just as likely to avoid conviction as a repeat offender.
Conviction
It is difficult to predict in a mathematical model how many adults or youths are convicted of crimes they commit. I determined a reasonable guess of maximum 75% conviction rate when Police = 100. In this formula, decreasing police spending equates into decreased conviction rate, which is considered a realistic representation.
Released
It is assumed that the average sentence for a youth is approximately 6 months detention. For an adult, it will be assumed that the average sentence is 12 months gaol. The discrepancy is due to a few basic considerations that include 1. Adults are more often involved in serious crime which carries a longer sentence 2. youths are convicted with shorter sentences for the same crime, in the hopes that they will have a higher probability of full rehabilitation.
Engagement
Rate of adult/youth engagement was estimated to be a linear relation. The maximum rate of engagement, assuming expenditure = 100, is set to 80%. This rate of engagement is a reasonable guess with consideration that there will also exist adults who refused to engage in the community and end up in crime, and adults or youth that refuse to engage in the community or crime.
Boredom
Engagement Expenditure variable is in the denominator to create a hyperbolic trend. The aim was to achieve a lower boredom rate with a higher engagement expenditure, and thus a higher boredom rate with a lower engagement expenditure. The figure in the numerator of 25 represents the asymptotic boredom rate percentage, where if engagement expenditure = 100 the adult/youth boredom rate is maximised at 25%.
NSW Bureau of Crime Statistics and Research. (2020). NSW Local Government Area excel crime tables.
Alexander, H. (2019, May 29). How NSW town labelled 'most dangerous in world' changed its destiny. Retrieved from Sydney Morning Herald: https://www.smh.com.au/national/nsw/how-nsw-town-labelled-most-dangerous-in-world-changed-its-destiny-20190527-p51ri6.html
Australian Bureau of Statistics. (2016). 2016 Census QuickStats. Retrieved from Australian Bureau of Statistics: https://quickstats.censusdata.abs.gov.au/census_services/getproduct/census/2016/quickstat/LGA11150?opendocument
Thompson, G., McGregor, L., & Davies, A. (2016, September 19). Backing Bourke: How a radical new approach is saving young people from a life of crime. Retrieved from ABC News: https://www.abc.net.au/news/2016-09-19/four-corners-bourkes-experiment-in-justice-reinvestment/7855114
Underlying assumptions:
Constants:
Things to note:
Initial values:
Youth in town: 1200.
Criminals: 100.
Juvenile Detention: 100.
Violent families: 300
Detected violent families: 100.
Underlying assumptions:
Constants:
Things to note:
Initial values:
Youth in town: 1200.
Criminals: 100.
Juvenile Detention: 100.
Violent families: 300
Detected violent families: 100.
