- Nov 29, 2014
Aguirre ran his black SUV into the back of the technician’s truck to get the man to stop and get out, according to a court document describing probable cause for the charge of aggravated assault with a deadly weapon. He pointed a handgun at the technician and forced him to the ground, according to the affidavit. One of the other people Aguirre was with allegedly stole the technician’s vehicle after searching it; police later found the abandoned truck a few blocks away.
Mark Aguirre was working on behalf of a powerful Republican megadonor’s group to investigate unsubstantiated claims of widespread voter fraud when, in October, he allegedly pulled a gun on a man described by the Harris County district attorney’s office as an “innocent and ordinary” air conditioner repairman.
fake newsPeople of alleged credibility are in the game now, former CIA workers, data scientists, etc. Encourage everyone to watch and see if you can call the bullshit.
There are basically two points:
- There are counties that went to Biden by a margin that is a statistical outlier. Additionally, 100% of the outliers are for Biden.
- Vote switching happens at a bizarrely high rate, over 90% of votes were alleged adjudicated in some areas. The adjudication process repeatedly switched large groups of votes from Trump to Biden. This is in the openly reported data, but has not yet been discussed.
I would actually be a little worried about this claim because I'm so out of my depth in election data reporting that I don't understand why #2 happens at scale (i.e. 100k votes), except they get #1 so wrong, it's hard to take them seriously in #2.
#1 is assuming the hypothesis. They're basically saying "if all the data look like the ones without the outliers, then the outliers are really unlikely." But the first half of the sentence (really: if the non-outlier data are from the sampling distribution, and we assume the outliers are too) is a fucking wish. High population counties are known to swing heavily left, i.e. the non-outlier data are NOT representative of a sample of the overall population, making the "outlier" just the rest of the story. It would be like sampling suburban home sizes in Ohio, finding the distribution, and then when you see the sizes of apartments in NYC, declaring they are fraudulent because they aren't the same as the ones in Ohio. Complete nonsense.
#2 is something I saw election night. CNN claimed that these changes in numbers were due to updates (I don't remember if they used the term adjudication or not). But I actually do agree that it sounds, on the surface, weird that so many are adjudicated and that so many of the adjudications led to vote switches (i.e. from Trump to Biden). I'm looking forward to learning why this happened but, given the quality of #1, I am not expecting much from it.