Editing Gerrymandering (section)

==Use of databases and Computer Technology==
{{See also|Geographic information system}}

The introduction of modern computers alongside the development of elaborate [[voter database]]s and special districting software has made gerrymandering a far more precise science. Using such databases, political parties can obtain detailed information about every household including political party registration, previous campaign donations, and the number of times residents voted in previous elections and combine it with other predictors of voting behavior such as age, income, race, or education level. With this data, gerrymandering politicians can predict the voting behavior of each potential district with an astonishing degree of precision, leaving little chance for creating an accidentally competitive district.

On the other hand, the introduction of modern computers would allow the United States Census Bureau to calculate more equal populations in every voting district that are based only on districts being the most compact and equal populations. This could be done easily using their Block Centers based on the Global Positioning System rather than street addresses.  With this data, gerrymandering politicians will not be in charge, thus allowing competitive districts again.

Online web apps such as [[Dave's Redistricting]] have allowed users to simulate redistricting states into legislative districts as they wish.<ref>{{cite web |last1=Bradlee |first1=Dave |title=Dave Bradlee |url=http://gardow.com/davebradlee/default.html |archive-url=https://web.archive.org/web/20180914232025/http://gardow.com/davebradlee/default.html |archive-date=14 September 2018 |access-date=3 September 2018 |website=Gardow.com}}</ref><ref>{{cite news |last1=Wang |first1=Sam |date=2 February 2013 |title=The Great Gerrymander of 2012 |url=https://www.nytimes.com/2013/02/03/opinion/sunday/the-great-gerrymander-of-2012.html |access-date=3 September 2018 |website=The New York Times}}</ref> According to Bradlee, the software was designed to "put power in people's hands," and so that they "can see how the process works, so it's a little less mysterious than it was 10 years ago."<ref>{{cite web |last1=Korte |first1=Gregory |title=Technology allows citizens to be part of redistricting process |url=https://usatoday30.usatoday.com/news/washington/2011-03-21-redistricting21_ST_N.htm |access-date=3 September 2018 |website=USA Today}}</ref>

[[Markov chain Monte Carlo|Markov chain Monte Carlo (MCMC)]] can measure the extent to which redistricting plans favor a particular party or group in election, and can support automated redistricting simulators.<ref name="B Fifield, M Higgins, K Imai, A Tarr, 2015">{{cite web |last1=Fifield |first1=B. |last2=Higgins |first2=M. |last3=Imai |first3=K. |last4=Tarr |first4=A. |date=2015 |title=A new automated redistricting simulator using markov chain monte carlo |url=https://imai.fas.harvard.edu/research/files/redist |archive-url=https://web.archive.org/web/20200801022433/https://imai.fas.harvard.edu/research/files/redist |archive-date=1 August 2020 |access-date=9 March 2019 |type=Working Paper}}</ref>