Duke University Team Dabbles with Its Own Algorithm for Measuring Partisan Gerrymandering

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duke-u-gerrymandering-teamNorth Carolina – It isn’t Efficiency Gap Analysis, but a team of mathematicians at Duke University’s Sanford School of Public Policy have applied its own model (Markov Chain Monte Carlo method) to measuring the extent of partisan gerrymanders.  The algorithm produces maps with districts that have proven to be comparably more competitive than the actual districts established by states.  This does not appear to be anything new however, since computer modeled redistricting has been around for quite sometime.  The groups methodology explanation does not indicate how its model is superior to other algorithms. Read the article in

  • The group applied its model to 8 state congressional maps: AZ, IA, MD, NC, NY, TN, TX and WI.
  • The algorithm took into account population, county splits, compactness and minority districts.
  • The team hopes to explore state legislative redistricting in the future.

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Categorised in: featured, Gerrymanders, Redistricting

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