Over the past couple decades, something has happened in elections that’s left people scratching their heads. The person, or party, receiving the most votes doesn’t win. Some examples:
· In Wisconsin, where the population is majority democrat, the state legislature is majority republican.
· In 2012, Democratic Party candidates managed to win only 201 of 435 US House of Representatives elections despite receiving an overall majority of the total combined votes in nationwide House election races.
· Hillary Clinton won the popular vote in 2016 but lost the election.
Why is this happening? For the most part, gerrymandering. Gerrymandering is the dividing of election districts to give one political party a majority in many districts while concentrating the voting strength of the other party into as few districts as possible. Analysts attribute the Republican majorities in the house and senate to highly successful Republican gerrymandering over the last two decades.
There have been many court challenges but few have succeeded because most of the evidence presented has been subjective, hypothetical, or not supported by hard data. Courts don’t make favorable rulings based on subjective, hypothetical, or lack of hard data.
Enter science. After the 2012 election, several academic research groups (mathematicians and statisticians) studied the complexities of gerrymandering and its effect on election outcomes. They identified a very clear and solid relationship between them. Solid enough that it’s now being used as evidence in court cases.
In the last two years, 28 cases have been filed in federal courts, and in 24 of those cases, the district, county, or state has been ordered to abandon their voting district boundaries and redo them from scratch using non-partisan and non-racial guidelines.
So, in the end, mathematics exposed the unfairness of gerrymandering. A reason Republicans don’t like science.