We were fascinated to read about the family interactions in Rina's statement and how those impacted her map, which ended up being a strong entry. It also appears that Rina felt a great deal of efficiacy from this project, which is a wonderful conclusion for high schooler to make.
I first started my anti-gerrymandering map because it was an assignment in my AP Human Geography class. I assumed that I would somehow finish the project and be done with it. I never anticipated becoming so invested in my map. Gerrymandering is a very real issue in Pennsylvania; working on my map felt like I was making a difference as a future voter.
My primary concern for my map was reaching population equivalence. Population equivalence felt like the most sensible way to combat gerrymandering to me. I asked some family members as well, and they agreed. The US Constitution requires that districts have roughly equal populations so that everyone’s vote is equal. Equal representation for every member of the population is a fundamental principle of democracy. In reality, congressional districts must have almost equal populations. I followed this rule for my map so that it would be valid. I managed to get equal populations in 16 out of my 17 districts. The last district was missing 4 people, but there were no unassigned areas in my map. It was as close as Pennsylvania could come to equal population districts.
Reaching population equivalence caused some imbalances in other aspects of my map. I tried my best to make the districts look compact while still being equal in population. I asked my younger sister what she knew about gerrymandering; she told me that she knew the origin of a district being drawn like a salamander. In other words, people associate districts that are not compact with gerrymandering. In order to combat this perception, I kept my districts compact, with an average score of 39%. My compactness score is well above the competition’s median. Some of the edges seem jagged, but that was a side effect I anticipated from maximizing compactness and maintaining equal populations. I still created contiguous districts that looked compact. The districts are not very spread out, so people have more faith in my map’s fairness.
Compactness often combines people with similar views, which has pros and cons. It makes sense to combine people with aligning political opinions, but that can ruin competitiveness. However, trying to change compactness to increase competitiveness can make a map seem more gerrymandered, since lack of compactness can be a sign of gerrymandering. Because Pennsylvania has roughly equal populations of Republicans and Democrats, I wanted to create districts that would represent that. The first equal population map I created had 13 Republican districts, which I did not think was fair for the Democrat voters. To solve this problem, I tweaked my map so that 8 of my districts were Republican, and the other 9 were Democrat. Because I did not want to insert any personal bias, I asked others about my map. A Republican family friend told me that the map seems to be skewed to help Democrats, so I made 3 of the Democrat districts highly competitive to split the political parties as evenly as possible in Pennsylvania. These highly competitive districts were within 2%, so the results in those districts could go either way (Republican or Democrat). I know that competitiveness is a sign of a fair map and that I did not have very many competitive districts. I still tried to make the overall combination of districts split between the parties so that it’s representative of PA’s population. With my map, the majority political party still varies based on the people’s changing views. Almost all of my districts’ competitiveness is within 20%, so people in the minority political party of their district still have an incentive to vote. I worked to eliminate any party advantages so that their votes still count and can make a difference in elections.
When I used compactness to try and preserve communities of interest while keeping elections fair, I also used minority-majority districts for the same reason. Minority voices should be heard, especially where they are more prevalent. I created two minority-majority districts out of Philadelphia, which preserves minority interests. I strived towards equal representation using equal population in each district and minority-majority districts. Minorities can easily feel silenced, but having two minority-majority districts makes sure that minorities are encouraged to vote and that they have steadfast representation of their opinions in government.
My last priority in my map was county splits. Reaching equal populations made it difficult to prioritize less county splits; however, I wanted to group together the counties best I could so that it is more convenient, makes more sense, and feels fairer for voters. I had to go into blocks to get a standard deviation of 0 in my districts, but one or two blocks would often cross over into another county and increase the number of county splits. Because equal population was my top priority, I sacrificed and accepted that I would have more county splits. Despite the challenges that went along with equal population, I only had to split up 21 counties, which was fairly low considering my top priorities. I was able to preserve communities within the counties while still reaching an equal population.
Making a fair map proved to be more engaging and difficult than I imagined. I think that the values I balanced—equal population, county splits, minority representation, compactness, and competitiveness— were the most effective in promoting fairness and fighting gerrymandering. I’m very glad that I got the opportunity to make an anti-gerrymandering map through Draw the Lines; it has taught me the value of engaging in democracy and realizing the power within everyone’s vote.