Yes it's hard to take the cheating, voter suppression, and coup-ing into account statistically. I wasn't really advocating for the author or prediction. Just wanted those elements of the article when I saw the post.
Yeah, but his last prediction was 100% wrong, or his current one is...
In the run-up to the 2024 presidential election in the United States, amidst widening calls by Democratic Party representatives, members, voters, and supporters for incumbent president Joe Biden to withdraw from the race in favor of another candidate with "better chances,"[36][37] Lichtman denounced that demand as a "foolish, destructive escapade," accusing "pundits and the media" of "pushing" the Dems into a losing choice. He added that "all" those calling for Biden's resignation have "zero track record" of predicting election outcomes.[38] By July 21, 2024, Biden announced he was withdrawing from the race, adding that he will serve out the remainder of his term.[39]
Or, we could just accept the simple fact that if the candidates change, so too does the prediction. He made his predictions based on the options available at the time.
Also, his keys aren't supposed to need frequent reevaluation based on fine-grade events, so if they predict she'd win now, they should have predicted she'd win last month. The only information that's been revealed is there wasn't a "primary" challenge for the eventual nominee.
"Lichtman has correctly predicted the outcome of almost every election over the last half-century, except for the race in 2000, in which Republican George W. Bush defeated Democrat Al Gore."
Lichtman argues he was right in 2000 because his system predicted the popular vote winner, but that means in 2016 he was wrong because Trump didn't win the popular vote. He then tried to say the keys are now about predicting the electoral college winner, but there wasn't any change in the keys. He's just trying to redefine his targets to say he was right after the fact.
Coincidentally the odds are that almost exactly one will guess 9 out of 10 correctly, and about four people will guess 8 out of 10 correctly. Odds drop to about 1 in 1000 for guessing all 10 correctly.
If you try to forget who the picture on the right is, and just look at him as a random person, he looks so fucking strange with that makeup and that skin texture.
I don't want to diminish the talent of the historian in vain but past performance is not always an indicator of being good at predictions, he might just have been lucky in a completely random guess 9 times out of 10. Given the amount of historians making such predictions it is not unlikely that such an historian exists and it would be fairly easy to mistake their success for talent.
I don't know where I found this but I found a scheme somewhere to scam some investors:
Find a large list of potential victims. Tell one part of it that you predict that market will do A, and the other part that the market will do B. Repeat the process several times, selecting only the investors to whom you've always told the correct prediction. Eventually you will have a handfull of people who have "solid proof" that you are a visionnary and you can scam them.
Again, I absolutely do not mean to say that this particular historian is bad. This story just reminded me of these ideas and I wanted to share.
I'm curious if at this point it would be possible to train an LLM on this type of estimation. But I don't understand Ai really well or if they are even good at predictive work. Im going off of research that involved predicting disease (I think it was diabetes)
Had to run this through ChatGPT and funny enough it sites this article in the first paragraph. It also has no idea about Kennedy dropping out and endorsing Trump.
As of now, predictions for the 2024 U.S. presidential election suggest a tight race. Kamala Harris, the Democratic nominee, has been forecasted by election expert Allan Lichtman to win, based on his "13 Keys to the White House" model. Lichtman has a strong track record, having correctly predicted most U.S. presidential elections since 1984. He argues that Harris holds more favorable indicators than her main rival, Donald Trump, who is seeking a second non-consecutive term.
On the other hand, some models, like those from Race to the WH, show a more competitive scenario, with polling and swing state dynamics still evolving. Trump's ongoing legal issues and the emergence of strong third-party candidates like Robert F. Kennedy Jr. add complexity to the race.
Ultimately, the final outcome will depend heavily on how these factors unfold in the coming months, as both candidates continue their campaigns
LLMs don't handle booleans, and the 13 keys is an open statement, so the best you could do is train 13 neural networks to determine each of the keys, but you'd need a lot of data for that I suspect we simply don't have.
It'd probably be better to train a neural network to just output probabilities of each candidate winning based on specific information, like polling data.
well given the odds of a know-nothing correct pick being 50% then at best one would expect a coin flip to do on average is 5/10 though there were maybe a couple easy calls in there