Redistricting reformers have proposed many solutions to the problem of partisan gerrymandering, but they all require either bipartisan consensus or the agreement of both parties on the legitimacy of a neutral third party to resolve disputes. In this paper, we propose a new method for drawing district maps, the Define–Combine Procedure, that substantially reduces partisan gerrymandering without requiring a neutral third party or bipartisan agreement. One party defines a map of $2N$ equal-population contiguous districts. Then the second party combines pairs of contiguous districts to create the final map of N districts. Using real-world geographic and electoral data, we employ simulations and map-drawing algorithms to show that this procedure dramatically reduces the advantage conferred to the party controlling the redistricting process and leads to less-biased maps without requiring cooperation or non-partisan actors.

Computers hold the potential to draw legislative districts in a neutral way. Existing approaches to automated redistricting may introduce bias and encounter difficulties when drawing districts of large and even medium-sized jurisdictions. We present a new algorithm that can neutrally generate legislative districts without indications of bias that are contiguous, balanced and relatively compact. The algorithm does not show the kinds of bias found in prior algorithms and is an advance over previously published algorithms for redistricting because it is computationally more efficient. We use the new algorithm to draw 10,000 maps of congressional districts in Mississippi, Virginia, and Texas. We find that it is unlikely that the number of majority-minority districts we observe in the Mississippi, Virginia, and Texas congressional maps of these states would happen through a neutral redistricting process.

We compare quantitatively six simulation strategies for mortality projection with the Poisson Lee–Carter model. We test these strategies on New Zealand mortality data and discuss the simulated results of the mortality index, death rates, and life expectancy.