Every two elections (~8 years), the NSW Electoral Commission re-draws the boundaries of seats in our State.
This is done so that each seat in the NSW Parliament has a roughly equal number of voters (generally within 10% of the average of 57,193). Demographic change and urban growth cause population distortions in some seats (like Riverstone and Camden, which are oversubscribed by about a third).
It is important to note these are changes to the NSW State seats, not Federal seats relevant to a Federal election.
The process is undertaken by the Commission, which is a statutory authority and forbids gerrymandering, which is a very stark contrast to the broken and corrupt systems used abroad.
This process can be painful for elected MPs, as suburbs they represent are transferred to neighbouring seats (or, heaven forbid, weaken their margins or necessitate the reallocation of party branches into or out of their seats.)
But it affects voters as well, as the MP they are used to may no longer represent them, or it may change the complexion of an electorate, so it’s worth paying attention to it.
The Commission has just released the draft boundaries they want to employ for the next State Election due in 2023, and they are now on public exhibition. You’re welcome to give feedback until the 23rd of December 2020.
Many people find this process confusing, so I thought I would offer an guide, and provide some resources for people who like to play with Google Earth.
The above link will take you to a ZIP file which decompresses to a Google Earth .KMZ file that can be double clicked if you have the free Google Earth program for MAC or PC.
My visualisation allows you to toggle the old and new seat boundaries, the strength of the two-party-preferred vote in individual polling places, and suburb names, allowing you to explore the changes across NSW.
I’m offering this video and downloadable map layers in an effort to help people understand this process. I’ve confined my more detailed analysis to a few seats in north and western Sydney.
I have drawn this data from places such as:
This analysis is like other ones I have done in the past like: