We felt that Borna’s map and his premise were provocative, in a good way. His submission was a case study in prioritizing the use of data and a focus on party proportionality to produce legislative maps. His map looks gerrymandered, although he drew 12 competitive districts. His map is a great example to show those people who argue that redistricting should be done by computers using only algorithms. That may work in some ways, but it doesn’t adequately reflect the humans living in the districts. Borna proved that good legislative map drawing is both an art and a science.
My objective for redistricting of the congressional districts in Pennsylvania was to apportion the districts to reflect the voter registration of the state. We're redistricting 17 districts instead of the now 18 congressional districts in Pennsylvania. I used a more recent count of the voter registration which was counted November 5th, 2019 (citation). I followed the continuity and population criteria as the guidelines instructed. Choosing the proportional redistricting method will provide voters with a sense of fairness. This method might result in more competitive elections instead of legislatures drawing the map in favor of their current majority party. Furthermore, I am aware of not being able to always proportion the voter registration data with a 1:1 ratio, meaning if a party gets 40% of the vote then it will get 40% of the seats or in this case districts. Proportionality is my priority behind this map.
With the information I tried to evenly split the Other vote, as tracking voter history would be intrusive and impractical.