To defeat gerrymandering, we must go back to the drawing board.

The article focuses on the resurgence of gerrymandering in the United States and explores methods to detect and address it. Gerrymandering involves manipulating electoral district boundaries to favor a political party, with recent mid-decade redistricting efforts in several states aiming to influence the 2026 US House elections. Traditional detection methods like the Polsby–Popper test and efficiency gap have limitations, while advanced mathematical techniques such as Markov chain Monte Carlo (MCMC) sampling offer more reliable identification of gerrymandered maps, though the Supreme Court has ruled partisan gerrymandering nonjusticiable. The article advocates for electoral reform, highlighting proportional ranked choice voting (proportional RCV) as a system that could enhance fair representation by allowing voters to rank candidates and elect multiple representatives per district, thereby reducing wasted votes and improving minority and community representation. [Extracted from the article]