Michigan: MIT PhD Shows Trump’s Margin Was Reduced by 138,000 Votes in Just Four Counties by a Counting Computer with the “Weighted Race” Feature Turned On, which Transferred Votes from Trump to Biden
In Michigan, in four counties alone, 69,000 votes were transferred from Trump to Biden by a computer counting algorithm.
There are 83 counties in Michigan, though the four selected were the most populous ones. The official vote count in Michigan has Biden ahead by 146,000 votes, with 99% counted. If four of the 83 counties almost reverse the outcome, presumably if all 83 are included the true vote for the whole state would show Trump had won handily. Even before the other shenanigans, such as dead voters.
This analysis, by Dr. Shiva Ayyadurai, seems to be authoritative and correct (but we need someone else to repeat the analysis themselves on the raw data to verify it):
If the video goes missing, look here
See especially from about 14 minutes. This is the strongest statistical evidence of massive fraud to date. Most importantly, it indicates how many votes were switched by this particular fraud, and shows who should have won.
Looks like they have found the big mechanism for the election fraud.
The weighted race feature is verified elsewhere:
Votes are being counted as fractions instead of as whole numbers, by Bev Harris.
This report summarizes the results of our review of the GEMS election management system, which counts approximately 25 percent of all votes in the United States. The results of this study demonstrate that a fractional vote feature is embedded in each GEMS application which can be used to invisibly, yet radically, alter election outcomes by pre-setting desired vote percentages to redistribute votes. This tampering is not visible to election observers, even if they are standing in the room and watching the computer. Use of the decimalized vote feature is unlikely to be detected by auditing or canvass procedures, and can be applied across large jurisdictions in less than 60 seconds. …
Fractionalized votes … allow “weighting” of races. Weighting a race removes the principle of “one person-one vote” to allow some votes to be counted as less than one or more than one. Regardless of what the real votes are, candidates can receive a set percentage of votes. Results can be controlled. For example, Candidate A can be assigned 44% of the votes, Candidate B 51%, and Candidate C the rest. …
According to programmer notes, a weighted race feature was designed which not only gives some votes more weight than others, but does so based on the voter’s identity. Ballots are connected to voters, weights are assigned to each voter per race, stored in an external table not visible in GEMS. Our testing shows that one vote can be counted 25 times, another only one one-thousandth of a time, effectively converting some votes to zero.
The weighted race feature has been in place in the US voting system since 2004. Perhaps Hammer and Scorecard work by fiddling with these weights in the counting machines.
After this election, surely everyone will abandon machines and go back to hand counting paper ballots. In the meantime, if this is true, it looks like Trump really did win, fairly easily.