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Judge Dismisses Bullshit Lawsuit Claiming Pollster Committed Fraud By Being Wrong

from the frivolous-slapp-nonsense dept

Last year, we wrote about Donald Trump’s bullshit lawsuit against Iowa pollster Ann Selzer for releasing surprising polls right before the 2024 election suggesting that Kamala Harris might actually beat Donald Trump in Iowa. The polls turned out to be wrong—as polls sometimes are—and Trump decided this was grounds for a lawsuit. That case continues with a bunch of nonsense legal gamesmanship.

But Trump’s lawsuit wasn’t the only one. A separate “class action” lawsuit was filed against Selzer and the Des Moines Register by Dennis Donnelly, a random Des Moines Register subscriber who claimed the poll constituted “fraud,” “professional malpractice,” and—even more ridiculously—”interference with the right to vote.” It was basically a copycat lawsuit of Trump’s to try to put more pressure on Selzer and the Des Moines Register.

Last week, a judge rightly dismissed the case as complete nonsense.

Polls, like nearly all speech, are protected by the First Amendment. To get past that rather large hurdle, a plaintiff would need to show the poll was somehow both false and made with “actual malice”—not that it was mean-spirited, but that Selzer basically knew it was “false” when she published it.

That’s a problem when the “expression” in question is a poll based on data Selzer actually collected. It’s an opinion derived from methodology, not a factual claim that can be “false.”

Finding actual malice requires Donnelly to plausibly allege Defendants sacrificed decades of work in cultivating this reputation for accuracy by “knowingly or recklessly” manufacturing a poll they knew was incorrect in pursuit of an unclear goal. See ECF No. 36 at 33. With no factual allegations to support such an assertion and mere conclusory statements, Donnelly asserts only a bare legal conclusion accompanied by actual malice buzzwords that Defendants acted knowingly or recklessly. This is insufficient to meet the plausibility standard….

The court’s response to the “fraudulent misrepresentation” claim is even more brutal:

No false representation was made. Defendants conducted a poll using a particular methodology which yielded results that later turned out to be different from the event the poll sought to measure. The results of an opinion poll are not an actionable false representation merely because the anticipated results differ from what eventually occurred…. Donnelly, and all other readers, knew how the poll was conducted because the poll results were accompanied by a thorough discussion of methodology…. Donnelly does not claim the disclosed methodology was not followed, that results were falsified, or that Defendants altered the poll in some other way which did not reflect the publicly disclosed methodology. Defendants told readers exactly what they did and how they did it. Therefore, no false representation was made.

The court then highlights the absurdity of Donnelly’s position by applying his own logic to the polls he cited favorably:

Donnelly cites to several other polls which had then-candidate Trump ahead by between seven and nine points…. The actual margin of the election was thirteen points…. Donnelly cites these other polls favorably, yet, by his definition of misrepresentation, every single one of these polls cited also “was all wrong.” … These polls were not fraudulently misrepresenting the state of the race, they merely used different methodologies in an attempt to best capture a snapshot of a dynamic race. … Donnelly fails to cite to any authority finding an opinion poll of a future event constitutes a false factual assertion.

The “professional malpractice” claim fares no better. The court compares it to suing a weather forecaster for an incorrect prediction and walks through the parade of absurdities that would follow:

Donnelly’s claim also fails because political opinion polls are predictive and inherently uncertain. Defendants here carried out a randomized survey and published the results along with a full explanation of the poll methodology. Donnelly’s novel attempt to impose liability for news prediction is similar to Brandt v. Weather Channel, Inc. in which a plaintiff sought to hold a news channel liable for an inaccurate weather forecast…. That court noted “to impose such a duty would be to chill the well established first amendment rights of the broadcasters.” Id. at 1346. The court in Brandt further observed the litany of absurd suits which could follow from imposing such a duty, such as construction workers suing when they pour concrete in reliance on a weather report forecasting no rain or commuters suing when they are stuck in traffic and late to work because the news reported there would be light traffic. Id. Finding for Donnelly here would permit similar absurdity. The Court declines to permit such absurdity and finds Defendants owed no such duty to Donnelly.

This ruling doesn’t just dismiss Donnelly’s lawsuit—it preemptively demolishes every argument Trump is using in his own case. As Jacob Sullum at Reason points out, Trump’s lawsuit is even weaker than Donnelly’s already pathetically weak case:

If anything, Trump’s fraud claims are even less plausible than Donnelly’s. Donnelly, who sued on behalf of all Des Moines Register subscribers, actually has a commercial relationship with the newspaper. Trump, by contrast, does not seem to have any such connection with the Register or Selzer. But both lawsuits suffer from the same basic problem: Because they treat misleading journalism as actionable fraud, they amount to thinly veiled assaults on freedom of the press.

Of course, these lawsuits were never really about having plausible claims. These lawsuits exist to send a message: publish anything that favors a political opponent of Donald Trump, and he and his MAGA allies will bury you in litigation. It doesn’t matter if the cases are frivolous. The process is the punishment, and the threat of more lawsuits is the deterrent. That’s not a legal strategy—it’s a censorship campaign dressed up in legal paperwork.

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