(The following was previously reported at The Gateway Pundit and is included in the upcoming book, The Steal: Volume II – The Impossible Occurs by Joe Hoft)

Less than a week after the 2020 Election, a ‘Dr. Shiva’ from Massachusetts uncovered some startling patterns in the 2020 Election results in Michigan.

…a presentation was released by Dr. V.A. Shiva Ayyadurai (Dr. Shiva), about the 2020 Election.  Dr. Shiva highlights his resume on his website as follows:

Dr. V.A. Shiva Ayyadurai, the inventor of email and polymath, holds four degrees from MIT, is a world-renowned systems scientist, inventor and entrepreneur. He is a Fulbright Scholar, Lemelson-MIT Awards Finalist, India’s First Outstanding Scientist and Technologist of Indian Origin, Westinghouse Science Talent Honors Award recipient, and a nominee for the U.S. National Medal of Technology and Innovation.

Dr. Shiva ran for US Senate in Massachusetts in the Republican primaries of 2020.  He was ahead in all of his polling hoping to be the Republican candidate to run against Elizabeth Warren.  His slogan was “Only the real Indian can beat the fake Indian”.

But Dr. Shiva didn’t make it out of the primary.  Something didn’t look right.  It didn’t pass the smell test.  Because he was convinced that he was going to win the primary election, he decided to investigate the data and systems used in his primary election to see if there were any clues for what happened.

(This is exactly what is done when auditing large data sets. I did this hundreds of times in multiple engagements in many countries.  An auditor will obtain data, gain a good understanding of the data and then perform queries looking for expected patterns that weren’t there or patterns of data that were present that were highly unlikely.

If data has a pattern to it that is not expected, there may be a reason, but if not, there is an issue.  If data doesn’t have a pattern and it is expected, there may be a reason, but if not, there is an issue.  In election data, these outliers or exceptions identify weaknesses in controls and/or fraud and can result in stolen elections.)

Dr. Shiva performed his analysis and then produced a presentation where he discussed what he discovered from looking into elections systems. In his video, Dr. Shiva noted that in our current election systems, we don’t have great input or output features – for example, we don’t receive a record of our votes and outputs can be manipulated.

One of Dr. Shiva’s first observations is that voting machines or systems don’t count ballots, they count results from images of ballots.  These images are supposedly created from real ballots and then put through the system and counted.  These images should be kept by the states but in many states the images are not maintained. Federal statutes claim that all records related to an election must be maintained for 22 months after the election, yet many states do not do this and are not being held accountable for not doing so.

In the current system, there is a feature called the “weighted race” feature.  This allows the system to weight votes.  For example, the system allows for some candidates’ votes to be weighted at a ratio of two to one.  Other candidates’ votes can be halved, where that candidate’s votes are awarded a half a vote to each vote received.  This functionality is built into the software used in voting machines.

Dr. Shiva also explained that our votes are stored in decimals in the election system.  The system doesn’t show one vote equals 1 vote.  In the system one vote can equal a portion expressed by a decimal.  For example, one vote can equal 1.1 or 0.9 depending on the system set up.  Votes are not stored as whole numbers in the election system but they are stored as decimals.

Dr. Shiva then used what he learned from his primary election in Massachusetts and applied this knowledge to the election results in Michigan.  He looked at the top four counties: Oakland, Macomb, Kent and Wayne counties. Per his analysis, in three major counties analyzed, President Trump’s margin of victory was reduced by a margin of 138,000 ballots minimum.  President Trump’s total votes were reduced by a minimum of 69,000 ballots while Biden’s totals were increased by a minimum of 69,000 ballots.  

Dr Shiva shared that this transfer of votes happened in a computer algorithm that linearly transferred more votes from President Trump to Joe Biden the more “red” or Republican a particular precinct was.  

Here is Dr. Shiva’s presentation from the first week after the election steal.

This analysis was performed less than a week after the 2020 Election.  

The post REMINDER: Voting Machine Systems Include a ‘Weighted Race’ Feature that Allows for Vote Transfers Between Candidates appeared first on The Gateway Pundit.