Tom Tiffany’s Wisconsin governor campaign cleared a major hurdle on Tuesday as the Republican congressman won his party’s nomination and moved closer to a fall showdown in one of the nation’s most closely watched battlegrounds. The Wisconsin gubernatorial race now appears set to pit Tiffany, a Trump-backed House Freedom Caucus member, against Democratic state Rep. Francesca Hong in a contest that could decide control of the governor’s office in November.
Tiffany defeated medical service technician Andy Manske in the Republican primary, according to the Associated Press. He is expected to face Hong, who is likely to win the Democratic nomination, in a race to replace Democratic Gov. Tony Evers, who opted not to run for a third term. Republicans see the state as one of their best chances to flip a governorship, and Tiffany has leaned hard into that message, calling Wisconsin a place that can stop what he describes as socialism.
Hong’s path to the general election has drawn attention well beyond Wisconsin because of her ties to the Democratic Socialists of America and the agenda she is running on. Her platform includes guaranteed paid leave, a move to raise the state minimum wage from $7.25 to $20 an hour, and a one-year pause on building AI data centers in Wisconsin. That mix has made her a focal point for Republicans looking to frame the race around taxes, regulation, labor policy, and the future direction of the state economy.
Hong has also faced scrutiny over older social media posts that called for defunding and abolishing the police. She now says she no longer supports cutting police budgets or ending police departments. At a voter event on Saturday, she said, “I’m not defunding the police, not abolishing police. I am serious about public safety.” She also had to answer for a resurfaced 2020 post in which she said the country should “cancel Thanksgiving” to “stop celebrating colonialism.” After the backlash, Hong said Thanksgiving is now her “favorite holiday,” and told reporters on Saturday that she has “evolved” and “learned.”
