Freedom of Information Act open record orders were filed by citizens in most Wisconsin Counties to hold the ballots of the June 5 Recall Election
Two different groups of volunteer citizens are spot checking the machine count of the vote to compare it to a hand count audit. One group is holding any information until the audit is complete while the other is releasing comparative audit totals as they are completed. Below is one of the tallies from Ward 16 in Dane County that deserves attention.
I followed the election returns on the night of June 5 with the county newspaper editor who had been through the election return process many times, and he noticed something unusual – that many voters who cast their vote for Walker also picked Mitchel as their choice for Lieutenant Governor. It was later learned when looking at other areas of the state how this tendency of shift from Walker to Mitchel was observed throughout the state. Is this another one of “hinky” or questionable anomalies that left people unsettled on June 5? It sure is, but what makes the result of the hand count in Ward 16 even more interesting is that it fits the description of a classic flip.
The totals of the hand count audit are shown in the boxes below with a description of the vote gain/loss by candidate.
Interesting +12/-12 Flip
The +12 number in column 4 Barrett suggests that 12 votes were found for Barrett that the machine did not count.
The -10 in column 10 suggests that 10 votes were given to Mitchel that the machine over counted.
The -1 in columns 6 and 7 suggest the 1 vote for Trivedi was uncounted and 1 under vote (when someone does not vote in all the choices) was uncounted by the machine.
The total of these miscounts indicate 12 votes were gained by Barrett and a total of 12 votes were lost in the columns for Mitchel 10, Trivedi 1, and undervote 1.
Citizen Audit Finding
Vote Machines are Programmable Computers
The computers that tabulate your vote (voting machines) have been proven to be highly susceptible to hacking, usually by being programed to “flip”votes. The programming is run to take away every 10th, 20th, or xth vote from one candidate and give it to another. Any programmer will tell you this procedure is not difficult to write or initiate. So, in the example above we have a case that supports the immediate reaction of the newspaper editor on election night and the observation of the cross over vote where people voted Walker then switched to vote for Mitchell.
The problem with flipping is that regardless of how or for whom the flip occurs the machine total must match the number of people who voted as recorded in the poll books, or the flip shows up as an obvious mismatch of totals. So, the flipping in favor of a candidate must not subtract from the total people generated, poll book number of voters. So, the programming is written to take away a vote from, lets just say Barrett. Did the 12 votes taken away from Barrett get moved to Walker, Triveli, or under votes, while leaving the Mitchel votes unchanged? This way the final totals of the hand count would be 12 votes greater than the machine count with an exact flip of 12 votes.
If the audit shows flipping with Scans what about the touch screens?
Dane County uses an optical scan machine, where the ballot is marked and then read by scanning it through the machine, which is slightly more reliable then the touch screen machines where no paper is ever hand marked in the voting process. This makes the touch screen machines even more susceptible to hacking then the scans. In fact, an analysis by Richard Charnin shows how Walker did consistently better on touch screen as opposed to scan machines as demonstrated in the scatter chart below.
The scatter chart shows the vote in Winnebago County. The left axis of the chart shows the percent of the Walker vote share. Two types of machines are used in the county and the bottom line shows the percentage of votes that were cast on Touch Screen machines as opposed to scan machines. You can clearly see how the percentage of votes received by Walker increases as the percent of voters using the touch screen machines increases.
Notice the second block of the top row and see all of the dots and notice how Walker’s share of the vote increased dramatically when the percentage of voters using the touch screen machines increased.
Richard Charnin has done more statistical analysis of Wisconsin elections than anyone in the state – and he lives in Florida! Visit his blog for more stunning information regarding the prevalent fraud in our elections. Richard Charnin (pictured right) who predicted what the fraud factor would look like ten days before the June 5 election. Now he is creating a model which will boil it down to the Municipality:
“I just created a Muni Recall True Vote model based on the elections.xlsx data. It uses the 2008 Presidential and 2012 Recall recorded votes. This is just a quick, first-cut. I will be adding improvements over the next day or two.” Richard Charnin’s latest Municipal Recall True Vote Model