Democrats faked birthdays in Pennsylvania and are caught by statistics
Counties with more suspicious birthdays were more likely to vote for Biden
When people picked fake dates for fake voters they didn’t spread them in a normal pattern through the year. Instead of having more birthdays in the summer months (which is normal in the US) there were more births than expected in December and January. There were also more birthdays on the nice round numbered days like the 10th, 20th and 30th days of the month.
In a layered and detailed study Carl Bell uncovers how wildly unlikely these birthdays are. Not only are the days suspicious, the months are too, and then there is the red hot flag that the counties with the oddest birthday patterns are usually Biden supporters. And furthermore, they are counties that differed the most from their past voting behaviour and also counties with higher votes for third parties too (like the libertarians). It’s almost like fake voters wanted Joe Biden to win, but not win by too much, so they had to add in some votes for “others” as well.
The “birthday” tool could not only to be used to spot suspicious counties in the first place, it was so detailed it could give an estimate of what votes might have been if those outlier counties had had a more normal distribution.
As usual, when they take out the fakes, Trump won.
This looks like something that would be useful in a court of law. “Beyond reasonable doubt”.
It’s a sign of the caliber of the Trump supporters, and another weapon in the game. Studies like this motivate the good guys and must surely make some people more nervous.
Lawyers will be watching.
These suspicious birthdays also matter significantly for election outcomes. While there are suspicious counties that vote Republican overall, in general more suspicious birthdays in a county are strongly associated with a larger Biden vote share, and a higher Biden vote share relative to all Democrat presidential candidates since 2000. More suspicious birthdays are also associated with a higher vote share for Jorgensen relative to Trump (consistent with a fraud scheme aiming to get Biden high but not “too high”, while simultaneously giving as few votes to Trump as possible).
Finally, we quantify the magnitude of how this potential fraud may have impacted the election. Even a small reduction in the amount of suspicious birthdays (to the 98th percentile of the conservative distribution) would be predicted to have resulted in Trump winning the state by 71,500 votes. This suggests that whatever is driving the anomalous patterns in birthdays is sufficiently important to affect the statewide election result.
h/t Scott of the Pacific.
By Carl Bell at Revolver
We construct a new metric of potential voter fraud using suspicious distributions of birthdays in Pennsylvania voter registration data. The basic idea is that people picking fake birthdays will make predictable non-random choices, like picking round numbers for days of the month, and not knowing what true birth month distributions look like.
Under this metric, a number of counties in Pennsylvania have extremely unlikely distributions of voter birthdays. Seven counties representing almost 1.4 million votes total (Northumberland, Delaware, Montgomery, Lawrence, Dauphin, LeHigh, and Luzerne) have suspicious birthdays above the 99.5th percentile of plausible distributions, even when using conservative assumptions about what these distributions should look like.
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