Since Washington’s presidency, the Census has been an integral part of the United States Government. The Constitution’s sixth sentence introduces the idea of using the census to count the population. Redistricting, which is essential for our government’s smooth functioning and equity across the different states of population, is necessary. Redistricting must be nonpartisan and done by a neutral party who has only one interest in creating fair districts. Redistricting is a state legislative matter, which is then approved the governor. If one party is in power, it’s very simple for them to redistrict state so they can win future elections and votes.
Some people realized that Gerrymandering was the best way to redistrict a state so that one party has control. Although Gerrymandering might sound random, it was named after Elbridge Gerry in Massachusetts. Elbridge Gerry controlled the redistricting process in Massachusetts in 1812. Gerry redistricted counties surrounding Boston such that it created a bizarre shape of South Essex, which in turn allowed for the Democratic-Republican Candidates to hold power over the Federalists. Some Federalist writers referred to his creation as a monster. One even suggested that it was a Salamander. Federalist writers were quick to call the new creature Gerrymander. Gerrymandering was a portmanteau made of the Governor’s last and salamander names. However, it is often used to gain political and social power. Human nature is to associate with others who are like us. Ethnicities and races often live together due to socio-economic pressure. It was easy for some people to disadvantage minorities. It was made illegal for legislators to use redistricting power against black voters by the Voting Right Act of 1960. Shaw v. Reno, 1993 was an example. A North Carolina legislator consolidated all the cities into one district. This resulted in a reduction of votes and concentrated minority and urban voters in one district. Asking a Political Scientist about this is difficult. It is crucial to redistrict so that minorities are represented by people who have had similar experiences, but also to ensure that they are not suppressed. Redistricting cannot be done in square counties or states. The arbitrary lines create a situation where minorities are silenced, and the majority would be able to rule. Below is an example. The district appears to have been Gerrymandered. That is a common connotation that has a negative connotation. However, the green and space between them are both Latino communities. It would be possible to redistrict a country in such a way that every county and each district is perfectly square, but without political or social pushback. People don’t live in boxes. This country is home to a wide range of people from different geographical locations. First, it is important to understand the current structure of legislatures.
As I said, Gerrymander is prohibited from suppressing racial groups. Gerrymander is allowed to suppress the votes of other parties. Legislatives may either crack open or pack in order to favor one’s party. The cracking of a minority group spreads them out so they don’t have representatives. Packing is a method by which legislatures place all political minorities within a single district. This allows them to have as few representatives as possible. The Gerrymandered Michigan in 2010 was a prime example of packing. Despite the fact that the voting percentages of Republicans and Democrats were roughly the same, the redistricting process saw Democrats condensed into smaller districts which gave Republicans the ability to win elections. It is essential that every individual be represented equally in the state’s legislature to ensure fair elections. Representatives should, for example, be 40 percent blue and 60 percent red if there is a blue state.
In order to create a more equitable system, it is important to include economic, cultural, as well as racial and ethnic representatives. Mathematicians have turned to graph theory and geometry in order to find mathematical solutions to the republic’s problems. Although there are many possible solutions, the graph partitioning technique is the best. Understanding the various variables and vocabulary is essential to understand graph-partitioning. For graph-partitioning, vertices will be used. These vertices will represent census block groups. The government divides the country into Census Block groups. These Census Block Groups refer to small communities. Block Groups make up Census Block Groups.
Combine Census Block groups into graphs, G. This will make it possible to calculate how to create equal-weighted groups. Each vertex will be assigned a specific rank and weight depending on the area’s population. These vertices will be connected by edges. (Doyle, 42) Census Block group are the smallest of all political groups within an area. They are therefore typically one party. Each vertex can be denoted as either red or blue, which represents republican or democratic. This will allow me to show how it works. We will then be able, using computer programs, to display it on a larger scale. The government has determined that the area shown in figure 4 is made up of seven census blocks.
This map must be divided into two districts. To make sure that the block is fair, we will need to split the census blocks into two districts. The shown block is divided 50% democratically and 50% republican. This graph has been coarsened to make it simpler. In the original plan, each person would be represented as a vertex. This graph is then weighted. While there will always be enough people to populate each census block in real maps, we will not give them a weight other than 1-7. Each census block will have the weight of its number. The map can be converted into a graph. The weight of each edge will be 1.
The maximum amount of matching is necessary to reduce edge cutting. (Soberon). The graph shows that we can find matchings for 1 & 2, 3 + 4, and 5+6. 7 is our most weighted vertice, so it’s possible to see the graph. This will allow us to create a minimal number of Republican and Democratic groupings. The weights of these new vertices can be combined to create a better way to divide the section into Republican or Democratic districts. One can create two separate districts by denoting 1 &2 & 5 & 6, 3 &4 7 & 6 as republican districts and 3 &4 6 & 7, as 1 +2 + 5 +6 = 3 +4 + 7, respectively.
Next, we need to uncoarse this graph. Red lines indicate edges connecting like colored vertices. It is not possible to connect districts when they are created. Local refinement can be used to ensure that the districts are always connected. Local refinement can be achieved by measuring the edge size. This is the sum of edge weights per edge cut. The districts’ weight must also be maintained in order to maintain the ratio. You can switch 3 and 4 by 1 and 6. You can do this by replacing 3 and 4 with 1 and 6. Although it may sound like a good system, it isn’t perfect. This paper was started by introducing the delicate balance between redistricting and racial oppression. There are ways to create blocks with weights but this is not a foolproof method. Many minorities will be scattered among white majorities communities, particularly in the Midwest.
Gerrymandering can be solved in a number of ways without using computer algorithms. Graph-partitioning is a way to show that we can make fair political lines by breaking down a county into sections. You could alter the color percentage or divide the weights so that they represent economic stature, party, and density. Even with computers, it would be difficult to create an equitable system with weighted cities that meet all our criteria.
The graph partitioning method may be a mathematical solution to our Gerrymandering problem, but it is not feasible. Our Gerrymandering problem can be solved by looking at the efforts of some states such as California. Instead of having partisan legislatures set boundaries, they have turned to non-partisan and bipartisan groups for division. It is impossible to create bipartisan maps. Even math, though it is the least political method, can have issues with creating fair lines. They can however gather intelligent, educated citizens who are not loyal to any party to make fair redistricting.
Works cited
“A Commission’s Guide To Redistricting Michigan”.?Princeton University. Trustees of Princeton University.
Gerrymandering Over Graphs. At the proceedings of… Proceedings of the 17th International Conference on Autonomous Agents and Multiagent Systems, Stockholm, Sweden, July 15 – 15, 2018, IFAAMAS, 9 Pages.
James Trecothick Austin. ?The Life and Times of Elbridge Gerry: With Current Letters?. Wells and Lilly wrote a book in 1828.
Bazelon, Emily. “The New Front In The Gerrymandering Wars: Democracy vs. Math”
Cavell, Nic. “Gerrymandering is even more frustrating when you can actually see it.” Cavell, Nic.
Shawn Doyle (2015) ‘A Graph Paritioning Model for Congressional Redistricting.’
Rose-Hulman Undergraduate Mathematics Journal: Vol. 16 : Iss. Two, according to Article Three.
Gerrymandering Group. “Metric Geometry and Gerrymandering Group.” http://www.mggg.org/
Elmer C. Griffith’s article, “The Rise and Development of the Gerrymander,” looks into the origins and evolution of this practice. Sagwan Press, 2015.
Miller, Greg. “The Map That Popularized The Word ‘Gerrymander’.”?This Is What It Takes to Popularize the Word?Gerrymander?. 6 Nov. 2018.
Prokop, Andrew. “Who Actually Does the Gerrymandering?” Vox, Vox, 14 November 2018.
Schulz, Christian. Graph Partitioning or Graph Clustering as a Theory or Practice? Karlsruhe Institute of Technology Institute for Theoretical Informatics, 2016.
Soberon, Pablo. “Gerrymandering and Sandwiches”?Notices to the American Mathematical Society? vol. 64, no. 09, 2017, pp. 1010-1013., doi:10.1090/noti1582.
Supreme Court. ?Shaw v. Reno?. 20 Apr. 1993.
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