“A Partisan Solution to Partisan Gerrymandering: The Define-Combine Procedure”, Maxwell Palmer, Benjamin Schneer, Kevin DeLuca2023-12-13 (mechanism design, politics)⁠:

[supplement; data; simulator; only strategy-resistant?] 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 [fair cake-cutting] 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.

[Keywords: redistricting, partisan gerrymandering, representation, simulation methods]

…Using simulations based on real-world geographic and electoral data, we assess DCP’s performance in all states where congressional redistricting occurs, and we find that DCP produces maps with large reductions in partisan bias, as well as improvements according to several other commonly used redistricting metrics. Compared to adopted plans from the most recent redistricting cycle, our simulations suggest that DCP would likely perform dramatically better than maps originating from state legislatures and politician commissions and at least as well as maps produced by independent commissions and special masters.