Somebody apparently spent more than $21,000 to rig the Hugo Awards, badly

polygon.com:

It’s been a difficult decade for the Hugo Awards, the coveted science-fiction/fantasy awards that emerge every year from the Worldcon convention. A decade of open attempts at ballot manipulation has put a national spotlight on Worldcon’s awards process, once mostly of interest to the relatively small number of fans who buy voting memberships. The latest scandal? An unnamed party secretly bought hundreds of fake memberships to the 2024 convention to pack the ballot box for a single nominee. From what the organizers have said publicly about the attempted fraud, it’s clear this was the most inept, clumsiest Hugo-rigging scheme to date — and also the priciest.

The Hugos have been in the news frequently since the “Sad Puppies” movement made international news in 2015. The group used pre-planned voting blocs to pack the ballot with their own members and chosen nominees — largely straight, white males, as a “corrective” against perceived diversity. The resulting news coverage blew up in the mainstream — not because of widespread obsessive interest in the mechanics behind the Hugos, but because of the way the Puppies represented a rising faction in an ongoing political war against women, queer-identified folks, and people of color in public spaces.

A second, related movement, the “Rabid Puppies” slate, followed the next year, and heightened the controversy. An angry response to George R.R. Martin’s awards-show hosting gig in 2020 got more air than it might have otherwise because of Martin’s Game of Thrones fame. And revelations that the 2023 nominees were heavily censored behind the scenes has brought to light a lot of lingering questions about the awards’ voting and vetting process.

Now the Hugos are dealing with this year’s surprising new problem: incredibly inept ballot-box stuffing. The Hugo Administration Subcommittee for Worldcon 2024, which will be held Aug. 8 to 12 in Glasgow, Scotland, has issued a statement detailing the “unusual data” (to put it mildly) that