Modelling policy leverage points in the Victorian prison system.

This blog is a continuation of an earlier blog entitled

VICTORIAN GOVERNMENT MAY HAVE OVERESTIMATED THE 2023 PRISON POPULATION IN THEIR PLANNING

In this blog, I discussed how Victoria’s prison population has increased by 80% in the last decade, primarily as a result of a “tough on crime” approach by both sides of politics

This is a simple system dynamics model of the prison population used in that blog.

System dynamics models such as this one allow decision-makers to vary certain policy levers and understand how the system functions over a given time as a result of those changes.

The model produced two sets of data which indicated that the government may have overestimated prison numbers.

The projection of rates of Incarceration, Release and Recidivism.

The projection of the prison population to 2023..

While this simple model yields some insights into the problem, it provides no insight into the potential policy leverage points in the system. To do this requires simulation with a larger and more sophisticated model.

This simulation models the individual courts (Supreme, County, Magistrates) and their outputs.

It would also model people being held in remand awaiting trial. This element of the model is extremely important as, according to the Victorian Ombudsman, they represent 50% of the prison population. In addition 50% of this group is not convicted despite having been held in remand.

The model would also capture the feedback effect of recidivism which is particularly important with the rising prison populations.

The model of the Prison Sector would include length of incarceration for each one of Victoria’s prisons.

This would also model the impact of variations in release rates, such as early release as result of rehabilitation programs, from various Victorian prisons.

The power of such a model is that it allows decision-makers to identify and evaluate policy delivery points. Policy delivery points are located in the flows in and out of the stocks.

The following diagram indicates a set of policy levers relating to remand and diversion programs.

In this case the policy levers are

1 the rate at which bail is granted or not granted,

2 the rate at which individuals are put into diversion programs and

3 the rate at which they complete these programs

Each one of these can be varied in the model and the impact of the variation on the total system evaluated.

A separate model could also be developed to simulate the financial implications of the variations in the court and prison models.

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