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Raleigh, N.C. – WRAL News used early voting locations for 2018 and 2014, as well as voter registration data, to assess the potential impact of mid-term changes. Among these changes, there is a 2018 law requiring all advance polls to be open from 7 am to 7 pm. in Week. A subsequent law reinstated the last Saturday before the advance vote.
Advance voting locations, or so-called "one-stop shopping", allow eligible county citizens to vote anywhere, instead of voting in a given electoral district.
Republican lawmakers said the changes were important to ensure consistency within counties and reduce electoral confusion. Opponents of the measure, however, said that it reduced the county's flexibility and feared that it would reduce the voting possibilities for those who could not afford to keep the sites open for 12 hours at a time.
In practice, the number of hours available in all states to vote early in one-stop shops has almost doubled since 2014 – from 25,887 to 49,696. The total number of hours of advance voting has increased in all but six counties: Henderson, Bladen, Stanly, Polk and McDowell and Halifax.
However, the total number of first parking spots decreased by approximately 17% between 2014 and 2014, from 368 to 304. In total, 43 counties lost at least one polling place. Two counties – Henderson and Buncombe – lost four.
But one question remains: has the change in the anticipated voting location had a disproportionate impact on a particular group of voters?
We sought to answer the question using data on more than 7 million registered voters.
The data
WRAL News has used the following publicly available data from the Elections and Ethics Board of Directors:
Methodology
The latitude and longitude coordinates for the 2018 advance voting locations were obtained with the help of the State Council law enforcement research tool. code of ethics, with the help of a Python script.
Because contact information is not available for 2014 through this tool, most of these locations were generated using the US Census Geocoding Tool. Unmatched addresses were manually searched for and saved using the Google geocoder tool.
In 30 counties in North Carolina, no change in anticipated voting location was observed between 2014 and 2018, so these counties were left out of analysis. This left 580 sites for both mid-term elections. Voters in these counties were also excluded from this analysis, leaving 6,433,969 active and inactive voters, both of whom are eligible to vote, according to state election officials.
Some early voting locations may have been relocated due to hurricanes Florence or Michael, but this analysis only takes into account the anticipated early voting locations approved by the Local Elections Board and the Board of Trustees. ;State.
The latitude and longitude coordinates were then compared to active and inactive registered voters at addresses, city, county and ZIP using MySQL database software. The request did not match the addresses of 145,645 electors, a correspondence rate of 97.7%.
We used the Open Route Service free application programming interface (API) to generate isochrones – polygons for geographic information systems used to determine driving distances radiating to the Earth. 39, outside from a point source. The isochrones were programmatically generated with the help of a Python script.
Open Route Service limits requests through its API to 10 shapefiles at a time. The service also limits the total number of API requests to 2,500 per day.
Because of these limitations, the Python script executes queries for each site four times in order to produce a collection of geojson entities with shape files at a distance of half a mile from 0.5 to 20, each polygon describing a range of driving distance.
For example, a point that appears in the isochron with a mile value of 5, but not in an isochron with a mile value of 4.5, is within 4.5 and 5 miles of the location of early voting.
Voter registration data, in CSV format, is loaded into the database and a separate Python script was used to import geojsons from the isochron using ogr2ogr and its Pygdaltools wrapper with a Python script.
SQL queries can then generate mile values for each isochron that intersects each voter, by county. By deduplicating the table according to the voter and keeping the smallest value, we can find the nearest site and distance for each voter in 2014 and 2018.
We then used database software to calculate the change in distance between the nearest polling place in 2014 and the nearest anticipated polling place in 2018 for each active and inactive voter.
Given that driving distances were limited to 20 miles from each polling place, 62,325 voters could not be matched with an isochron of 2014 or 2018 because they were outside the 20 mile range. This represents less than 1% of registered voters in the study for whom the difference in driving distance could not be calculated.
Using these values, we can calculate mean, median, maximum and standard deviation values for each of the following subgroup types defined in the voter registration data:
- Political party
- Race
- Ethnicity
We can also calculate mean, median, maximum, and standard deviation values for two types of county designations:
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