Assignment 3: Complex SystemsJason Nguyen 43711448Justice Reinvestment in Bourke
Insight maker was used to model the effects that community development (in the form of TAFE Funding) and extra policing had on the petty crime and juvenile detention rates for the youth of Bourke. By examining trends in certain relationships associated with the youth of Bourke (i.e. trade skill effectiveness vs. crime rates), we can assume that they parallel with adult community development programs should they be implemented.
About the modelThe model works with the youth of Bourke having temptation to commit petty crime (i.e. stealing, assault), since there is not much to do in the town. The amount of crime committed is largely influenced by the amount of TAFE funding and policing implemented. However, not all youth who commit crime are caught. Those who are caught are sent to juvenile detention, where they serve 6 months (not representative of all crimes, but is the average). A delay represents the 6 months in juvenile detention. 
The justice reinvestment plan in Bourke will focus on implementing trade skills via TAFE that the youth can partake in. It is assumed that the more youth that undertake a trade skill, the less crime that will be committed in Bourke. There is a 6 month period where the youth become satisfied with learning the trade skill (represented as a delay), and crime is reduced. 
The simulation presents results on 4 types of relationships and their trends. They consist of the default view, trade skill effectiveness on juvenile detention, trade skill effectiveness on crime, and policing vs. caught and not caught rates.
Variables/relationshipsThe variables are shown in yellow, and relationships are shown as arrows. Variables consist of:

• TAFE Funding: As TAFE Funding increases, the amount of youth that undertake a trade skill increases, and crime rates decrease conversely.
• Policing: As policing increases, the amount of youth committing crime decreases, while the amount of youth that are caught committing crime and sent to juvenile detention increases.

What is important to note is that any changes to the fixed variables/relationships in this model will cause incorrect simulation of the model for the user. This is because the variables/relationships relate directly to the information produced.
Interesting parametersAs the user increases the values in the sliders, we see a trend of youth committing less crime (which also means less in juvenile detention). The TAFE funding variable seems to have a greater impact on decreasing crime rates rather than the policing variable.For example: Set the sliders to these values:

• Policing: 25
• TAFE Funding: 26

Look at the trade skills vs. juvenile detention simulation. We can see crime rates rise when trade skills aren't largely funded. Then, increase TAFE Funding to 75. Notice that juvenile detention is very low and stays consistently low. 
Important notes

• The youth that are caught by police and sent to juvenile detention are released 6 months later.
• After undertaking a trade skill at TAFE, the youth are engaged for a 6 month period.
• These periods are both represented by delays. 
• No other factors are currently being implemented to reduce crime rates for youth.
• The community development program (TAFE funding) and policing effectiveness are assumed to parallel the same effect on the adult population of Bourke. Therefore, we don't need to visually show the adult population.

ConclusionFrom the model, we can gather that TAFE funding is highly effective in reducing crime rates in the youth of Bourke.

Bourke Crime Rates Youth Community Development

This model shows the interdependent relationship between Disengaged Youth, Crime Rates and Police Detecting within the youth population of Bourke, NSW.

Assumptions

This model assumes that total youth population of Bourke is 1,000 people.

Variables

Detected by Police – can be adjusted upwards or downwards to simulate the effect on engagement and crime levels.

Youth Engagement Crime Rates Police Detecting

This model shows the interdependent relationship between Disengaged Youth, Crime Rates and Police Detecting within the youth population of Bourke, NSW.

Assumptions

This model assumes that total youth population of Bourke is 1,000 people.

Variables

Detected by Police – can be adjusted upwards or downwards to simulate the effect on engagement and crime levels.

Youth Engagement Crime Rates Police Detecting