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Wisconsin 2014 Governor: Cumulative Ward Voting Indicates Fraud

02 Dec

Wisconsin 2014 Governor: Cumulative Ward Voting Indicates Fraud

Richard Charnin
Dec.2, 2014
Updated: Dec.2, 2015

Look inside the books:
Reclaiming Science:The JFK Conspiracy
Matrix of Deceit: Forcing Pre-election and Exit Polls to Match Fraudulent Vote Counts

Index of Wisconsin Blog Posts

JFK Blog Posts
Probability/ Statistical Analysis Spreadsheets:
JFK Calc: Suspicious Deaths, Source of Shots Surveys;
Election Fraud: True Vote Models, State and National Unadjusted Exit Polls

A total of 2,382,055 votes were recorded:
Burke: 1,112,260 (46.69%)
Walker:1,242,413 (52.16%)
Other: 27,383 (1.15%)

The 2014 Wisconsin Governor Cumulative County vote share analysis for all units/wards is available in a spreadsheet for viewing. Vote shares are sorted by increasing ward size for each county. The graphs look strikingly similar to the equivalents in the 2012 recall (especially Milwaukee and Racine). This indicates that the 2012 vote theft strategy was repeated in 2014. If it worked in the recall, why change it? Cumulative vote graphs for the largest counties are located adjacent to the unit/ward vote counts.
https://docs.google.com/spreadsheet/ccc?key=0AjAk1JUWDMyRdEhqXzdlbUhZT1Vic3RSQmU2cUVkc3c&usp=sharing#gid=9

In Milwaukee County, Walker vote shares increased as a function of Unit/Ward size. The increase can be considered as evidence of fraud. One would expect that the lines would be nearly parallel after 90,000 votes. But even parallel lines could indicate constant fraud throughout the county. See the graph below.

Examination
 of 
precinct 
level 
data
 in 
US
 presidential 
elections 
reveals
 a 
correlation
 of
 large
 precincts 
and 
increased
 fraction
 of
 Republican
 votes.
http://arxiv.org/pdf/1410.8868.pdf

The counties that look the most suspicious by the upward slope of Walker shares in large units and wards are Ashland, Brown, Kenosha, Dane, Eau Claire, Jefferson, Milwaukee, Racine, Sheboygan, Winnebago, Waukesha. Of course, a flat line could indicate that fraud is uniform throughout the county.

The spreadsheet can be used as a reference. It will be be enhanced in the near future. Let me know what features you would like to see. View the voting data and graphics in the sheets: Adams-Menominee and Milwaukee-Wood.

Wisconsin 2014 Governor: Total State Cumulative Vote shares
Note how Walker’s vote share initially declines in the smallest wards and reverses trend as the size of wards increase (at the 1 million mark). This is counter-intuitive: Walker’s share should continue the downward trend since larger wards are generally in Democratic strongholds (Dane, Milwaukee..).

Cumulative Vote Shares
https://docs.google.com/spreadsheet/ccc?key=0AjAk1JUWDMyRdEhqXzdlbUhZT1Vic3RSQmU2cUVkc3c&usp=sheets_web#gid=12

County size
Burke had 55.9% in the TOP 15 counties at the 10% CVS mark. Added to the final recorded shares of the other 57 counties, Burke won the election by 52.0-46.9%.

Burke’s total vote dropped by 61,000  from the 25% mark.
Her share fell by 4.8% in the largest 15 counties , increased by 2.4% in the middle 15 and by 0.8% in the 15 smallest . This is a strong indicator of fraud in the biggest counties.

Democratic strongholds
Burke’s share fell by 6.5% in counties in which she was leading at the 25% cumulative vote mark. This is an indicator of fraud in Democratic strongholds.

Correlation
There was a -0.39 statistical correlation between the change in Burke’s total county shares and county vote size and a  corresponding -0.35 correlation in the Democratic-leaning counties (at least 50% at the 25% mark). The correlation is near zero in the middle 15 and smallest 15 counties. This is another indicator of fraud in the largest counties (primarily Milwaukee).

Democratic Vote Share Trend: 5 elections,  15 counties
Obama had 63% in the unadjusted 2008 WI exit poll and 56% recorded, closely matching his CVS share for 15 counties. The unadjusted exit polls are not available for 2010-2014.


Election........Votes. 25%...50%..100% Change
2008 Obama......1853.. 62.4 60.6 57.1... 5.3
2010 Feingold...1375.. 54.7 52.4 48.7... 6.0
2010 Barrett....1372.. 55.0 51.9 48.2... 6.8
2012 Barrett....1551.. 54.2 52.1 48.1... 6.1
2014 Burke......1511.. 54.0 52.2 48.5... 5.5

Burke.......Vote...25%..50%..75%..100%.....Correl Chg
Total.......2385..49.2 48.6 47.5 46.7.... -0.39 -2.6

Top 15......1573.. 53.5 52.0 50.2 48.6... -0.23 -4.9
Mid 15.......242.. 41.0 41.2 41.6 43.1.... 0.01 2.1
Low 15........73.. 43.5 42.6 42.7 43.7.... 0.11 0.2

Burke >50... 935.. 67.3 65.2 62.7 60.8.... -0.35 -6.5

County....... Vote..25 50 75 100% .................. %chg Votechg
Adams............ 8.. 46 46 47 46....................... 0 0.00
Ashland.......... 7.. 59 61 64 63....................... 4 0.26
Barron.......... 17.. 39 39 40 41....................... 2 0.34
Bayfield......... 8.. 54 57 57 61....................... 7 0.56
Brown.......... 100.. 46 44 42 41...................... -5 -5.01

Buffalo.......... 6.. 40 38 40 41....................... 1 0.06
Burnett.......... 7.. 39 41 41 40....................... 1 0.07
Calumet......... 21.. 29 34 34 34....................... 5 1.07
Chippewa........ 25.. 37 42 42 42....................... 5 1.23
Clark........... 11.. 36 34 34 34...................... -2 -0.23

Columbia........ 25.. 43 48 50 51....................... 8 1.98
Crawford......... 6.. 55 55 43 51...................... -4 -0.25
Dane........... 240.. 70 71 71 70....................... 0 0.00
Dodge........... 57.. 29 32 34 36....................... 7 3.98
Door............ 15.. 43 44 45 45....................... 2 0.30

Douglas......... 16.. 54 58 61 61....................... 7 1.10
Dunn............ 15.. 41 43 43 46....................... 5 0.76
EauClaire....... 42.. 49 52 52 50....................... 1 0.42
Florence......... 2.. 28 30 30 31....................... 3 0.06
FonduLac........ 43.. 34 37 36 35....................... 1 0.43

Forest........... 4.. 51 47 44 44...................... -7 -0.25
Grant........... 19.. 44 45 46 48....................... 4 0.77
Green........... 15.. 49 48 51 52....................... 3 0.46
GreenLake........ 7.. 30 28 30 31....................... 1  0.07
Iowa............ 11.. 55 54 55 56....................... 1  0.11

Iron............. 3.. 40 37 38 38...................... -2 -0.06
Jackson.......... 8.. 48 47 47 48....................... 0 0.00
Jefferson....... 36.. 43 39 38 39 ..................... -4 -1.43
Juneau........... 9.. 44 43 45 45....................... 1 0.09
Kenosha......... 56.. 60 57 52 48..................... -12 -6.78

Kewaunee......... 9.. 38 35 33 37...................... -1 -0.09
La Crosse....... 48.. 57 55 54 53 ..................... -4 -1.94
Lafayette........ 6.. 44 44 46 48....................... 4 0.25
Langlade......... 8.. 34 36 36 34....................... 0 0.00
Lincoln......... 12.. 42 43 43 42....................... 0 0.00

Manitowoc....... 34.. 30 34 37 37....................... 7 2.38
Marathon........ 57.. 34 37 38 38....................... 4 2.26
Marinette....... 15.. 35 34 36 38....................... 3 0.46
Marquette........ 6.. 44 41 42 42...................... -2 -0.13
Menominee........ 1.. 75 75 75 75....................... 0 0.00

Milwaukee...... 368.. 74 70 66 63 .................... -11 -40.48
Monroe.......... 15.. 38 38 31 42....................... 4 0.60
Oconto.......... 16.. 34 34 34 35....................... 1 0.16
Oneida.......... 17.. 48 43 43 42...................... -6 -1.02
Outagamie....... 74.. 42 42 41 39...................... -3 -2.22

Ozaukee......... 47.. 30 31 29 29...................... -1 -0.47
Pepin............ 3.. 40 39 42 42....................... 2 0.06
Pierce...........15.. 41 43 43 46....................... 5 0.75
Polk.............16.. 41 41 41 41....................... 0 0.00
Portage......... 30.. 45 50 51 50....................... 5 1.50

Price............ 7.. 39 38 40 42....................... 3 0.21
Racine.......... 80.. 62 55 48 45..................... -17 -13.60
Richland......... 7.. 55 51 49 48...................... -7 -0.49
Rock............ 58.. 55 55 56 56....................... 1 0.58
Rusk............. 6.. 40 36 37 39...................... -1 -0.06

Sauk............ 26.. 55 55 56 56....................... 1 0.26
Sawyer........... 7.. 41 41 43 44....................... 3 0.21
Shawano......... 17.. 37 34 35 34...................... -3 -0.51
Sheboygan....... 50.. 42 39 38 36...................... -6 -3.00
St. Croix....... 34.. 39 41 41 39....................... 0 0.00

Taylor........... 8.. 32 28 27 29...................... -3 -0.24
Trempeleau...... 11.. 48 49 48 46...................... -2 -0.22
Vernon.......... 12.. 47 48 48 50....................... 3 0.36
Vilas........... 11.. 34 35 38 37....................... 3 0.33
Walworth........ 40.. 36 36 34 35...................... -1 -0.40

Washburn......... 7.. 42 41 42 43....................... 1 0.07
Washington...... 66.. 26 25 24 23...................... -3 -1.98
Waukesha....... 203.. 30 29 28 27...................... -3 -6.09
Waupaca......... 21.. 32 34 34 36....................... 4 0.84
Waushara........ 10.. 38 35 37 37...................... -1 -0.10

Winnebago....... 69.. 46 46 46 44...................... -2 -1.38
Wood............ 31.. 36 38 40 41....................... 5 1.55

Compare the 2012 recall cumulative county vote trend analysis to 2014. https://richardcharnin.wordpress.com/2012/12/09/walker-recall-county-cumulative-vote-trend-by-ward-group/

https://docs.google.com/spreadsheets/d/1Fkvjx_XW-VuJ89WlTONZoSLiqj-T-8RakeV0_N9iqyQ/pubchart?oid=2140563995&format=interactive

 

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One response to “Wisconsin 2014 Governor: Cumulative Ward Voting Indicates Fraud

  1. Dave

    December 8, 2014 at 2:41 pm

    Very interesting Richard. Now that you have actually released the spreadsheets, I can see how it works and completely agree that something is going on in certain large wards. These large wards are certainly not all predominately Republican so it seems fishy. I started reading your stuff after the Recall and certainly appreciate you getting back into the fray in WI. Keep up the good work. Time will tell if this makes any difference long term.

     

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