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The algorithm that could help end partisan gerrymandering

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We are living in the age of the algorithm. So why not apply data science to a decades old issue?
A full copy of Professor Cho's paper is available here:
The Supreme Court has long recognized the potential for abuse in the redistricting system. But the Justices have had trouble establishing an objective measure to rule on the fairness of a political map.
Professor Wendy Tam Cho of the University of Illinois set out to fix this problem. Her goal? To create a “Computational Method for Identifying Extreme Redistricting Plans,” as she put it in the subtitle of one research paper. The video above gives an overview of the process Cho proposed.
If you would like to know more about your state’s redistricting law, I recommend checking out this website from Justin Levitt, a professor of constitutional law at Loyola University Law School.
A full copy of Professor Cho's paper is available here:
The Supreme Court has long recognized the potential for abuse in the redistricting system. But the Justices have had trouble establishing an objective measure to rule on the fairness of a political map.
Professor Wendy Tam Cho of the University of Illinois set out to fix this problem. Her goal? To create a “Computational Method for Identifying Extreme Redistricting Plans,” as she put it in the subtitle of one research paper. The video above gives an overview of the process Cho proposed.
If you would like to know more about your state’s redistricting law, I recommend checking out this website from Justin Levitt, a professor of constitutional law at Loyola University Law School.
The algorithm that could help end partisan gerrymandering
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