Vue Con 2017
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Methods and Materials
In order to generate the new redistricting schemes, voter registration data was sorted on Excel and mapped using Quantum GIS.
First, data on how many Democrats and Republicans in each county of Colorado and Arizona was collected from each state’s state secretary website. Because county organization needed to be preserved, data was collected on the county level. Then, the data was transferred to Excel and sorted. For each state, two lists were generated with one list containing a list of counties in ascending order by the number of Democratic voters and the other list doing the same for Republican voters. Using this data, redesigned congressional districts were created, where relatively equal amounts of voters from both parties were placed in the same district. If this was done, then candidates running from differing political parties would have about the same chances of attaining the seat in the House of Representatives.
Next, the redesigned district data on Excel was mapped using QGIS. Mapping using GIS systems requires the use of data in a special format called a shapefile. Shapefiles, which are essentially ways of storing spatial data, for Colorado’s counties and Arizona’s counties were generated. This was done through loading a shapefile for all of U.S. counties and running a clip algorithm in order to only produce layers of the required states.
After the necessary layers were produced, the attribute table was opened where specific sections of the clipped states layers could be color coded. A color coding process was completed so that each color in the newly generated map would correspond to a certain congressional district. The fully completed maps are shown in the figures to the right.
Once the redistricting schemes were created, competiveness scores were recorded for both states through finding the percentage difference of voters in each congressional district and then averaging them. Then, for Arizona, compactness scores were recorded using the Polsby-Popper test. The geometry measures needed for the test were attained through the usage of QGIS’s field calculator.
First, data on how many Democrats and Republicans in each county of Colorado and Arizona was collected from each state’s state secretary website. Because county organization needed to be preserved, data was collected on the county level. Then, the data was transferred to Excel and sorted. For each state, two lists were generated with one list containing a list of counties in ascending order by the number of Democratic voters and the other list doing the same for Republican voters. Using this data, redesigned congressional districts were created, where relatively equal amounts of voters from both parties were placed in the same district. If this was done, then candidates running from differing political parties would have about the same chances of attaining the seat in the House of Representatives.
Next, the redesigned district data on Excel was mapped using QGIS. Mapping using GIS systems requires the use of data in a special format called a shapefile. Shapefiles, which are essentially ways of storing spatial data, for Colorado’s counties and Arizona’s counties were generated. This was done through loading a shapefile for all of U.S. counties and running a clip algorithm in order to only produce layers of the required states.
After the necessary layers were produced, the attribute table was opened where specific sections of the clipped states layers could be color coded. A color coding process was completed so that each color in the newly generated map would correspond to a certain congressional district. The fully completed maps are shown in the figures to the right.
Once the redistricting schemes were created, competiveness scores were recorded for both states through finding the percentage difference of voters in each congressional district and then averaging them. Then, for Arizona, compactness scores were recorded using the Polsby-Popper test. The geometry measures needed for the test were attained through the usage of QGIS’s field calculator.