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Nov 9, 2020 24 tweets 5 min read Read on X
@WontMarch4Soros @bedivere_knight @ColdPotatoSpud After thinking about the data / analyses I've been doing on the raw data vs website and other reports, I believe I have an explanation for why Rashid has so many more votes than Wittman. This will be a long explanation :
1. This explanation may bounce around a bit, but touches on different aspects of the pics I've posted across different threads. Ask questions if things don't seem to follow, since they are related.
If we think about how elections work, different precincts will have diff ballots
2. The ballots are different because downstream the (house reps) are different in the various districts. There are only two races that will be on every ballot across every district precinct. Senate and President. This is important.
3. The reason we are seeing so many ballots cast for Prez / Senate but not down ballot is because it is necessary not to fill them out in order to distribute these headline votes across different districts. How does this tie into Rashid's high vote total?
4. There was a large number of ballots where he was selected over Wittman, but this was a mistake (not the plan). In order to tie to the ballots themselves, it's necessary to leave the votes for Rashid as is, but to "reduce" the number when reporting his race.
5. This also means that many of the suspect ballots came from CD-1, because Rashid's name was on the ballot, but should not have been filled in. Stafford County seems like the source for these ballots. By filling in CD-1, those involved threw a wrench in the plan
6. Based on the Edison data, a large chunk (80%/20%) Biden votes was added and removed from the totals (around 400K ballots). Since about half of these (200K), had Rashid filled in, it caused problems because the systems would assign these votes to Rashid.
7. The raw data shows these 200K assigned to Rashid via Stafford County Absentee Ballots. For audit purposes, these can't be shifted to CD-10 or CD-11, because the house rep race is different, and it would violate the data integrity of the system.
8. Only alternative is change reporting of the figures to chop off 200K votes from him or else it would be obvious there is something wrong in the district. For the Senate and Prez votes on these ballots, those votes can be distributed because they appear in all districts.
9. Hence why down ballot races show a big disconnect when compared to Prez and Senate figures. Assuming this was a small group of people, it would be necessary to inject these ballots into the process at a central point (CD-1), but rely on others upstream to distribute them.
10. This distribution was complicated by these Rashid ballots which should not have been filled in. But this leaves a crumb trail of what the plan was. Couldn't delete these votes or else it wouldn't match the ballots if an audit was conducted.
11. Where does this leave us? My suggestion would be to have Wittman "concede" to Rashid, and highlight this discrepancy. "The elections board has ignored 200K ballots that their own systems show were cast for Rashid". If Rashid isn't in on this, he may even want to pursue this.
12. Since these are "valid" votes, sure he would support have the elections board report the votes properly. This would be an opening to scrutinize the system and why Rashid has 383K of the ~570K active votes in the district. That's unbelievably high, and would invite questions
13. This raises another question. Within the voting system (where the raw data comes from), are people able to "split" ballots. This is a bit technical but think it through. Assuming a ballot is tied (at a minimum) a district, can the down ballot votes be segregated form the top?
14. Does the voting system tie individual votes to specific ballot barcodes in VA? If it does, a forensic review would show votes from CD-1 ballots, being accounted for in CD1-10 and CD-11 districts. Since 1 ballot = many votes (prez, senate, house rep), we would see
15. Senate and Prez votes, tied to a CD-1 in the system, but reported in CD-10 / CD-11. This would prove that meddling was done at the elections board to smooth out the lumps of these large injects of ballots. It is very difficult to hide all the signs of manipulation.
16. Again, this is contingent on the voting system tracking votes from a ballot, and a ballot from a source (county). More importantly, this may give us the clues we need to follow the ballots upstream to the counting process. This is critical to get them thrown out.
17. If there are audit trails of batches of votes / ballots being uploaded into the election system, then it would be possible to identify which batches contained the ballots / votes that were shifted to CD-10 / CD-11. From the upload point, can we trace this back further?
18. Depending on the rules for reporting vote totals / ballots, it may be possible to isolate where the 400K batch swings originated from (e.g Edison data going up and down). If that trial exists, from the voting system, down to where the votes came from, we have a chance to
19. Identify the specific ballots that were fraudulent. This gives investigators a head start on where to focus, without the fuss of looking for dead votes and trying to figure out which ballot that might relate to. This approach would start with the results and track backwards
20. to the batch of votes / ballots that were uploaded. I don't know much about how ballots / votes are stored / retained after tabulation, but assuming there is a link backwards. We could identify the ballots related to highly suspect swings in Edison data.
21. Perhaps it varies by State, but if possible, this approach could be replicated for each state with a suspicious dump of ballots / votes. It would be much more efficient, and it's targeted nature would be more palatable to a judge rather than tearing through all the ballots
22. I realize such an approach is not a guarantee, but large processes usually have links between the steps. Some are obvious and clear, others need to be derived and synthesized. But without more knowledge of the systems involved, I can only say this is a possibility.
23. Anyone with deep knowledge about vote / ballot counting knowledge, the tabulation process, and how totals are centralized in VA would help shed light on the feasibility of this approach. What other options are there to expose what has taken place?

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More from @FishingForInfo

Dec 13, 2020
Virginia Vote Shifting Pattern - 2016 Edition: A key question raised in the 2020 election was about the large difference in top ballot races vs down ballot races. My analysis takes the votes of the Prez and subtracts the votes of the House candidate for Dems and Reps. Here's 2016
2. These figures come from the VA election results website. In 2016, the "Delta" column shows a surplus for Hillary, and a deficit for Trump in all districts except VA-3, VA-9, and VA-11. The highlighted row is VA-7 which we will examine more closely later in the thread.
3. The sum of the Trump deltas is a -171K votes. If we look at total VA votes for 2016, Hillary has 1,981K and Trump had 1,769K. A difference of 212K votes. So, correcting the shift means a Trump win in 2016.
Read 14 tweets
Dec 9, 2020
Understanding VA-7 Turnout Part 2 : From the last thread on VA-7, we explored two key anomalies :
1. Drop in R turnout in Henrico and Chesterfield Counties
2. Uniform >40% D turnout

This thread will explore a comparison in turnout with VA-4. Why VA-4? Henrico and Chesterfield.
2. For some background, there are 14 counties in VA that cover more than 1 district. See image. Here we see the counties on each row and the districts they cover in the numbered columns. Henrico and Chesterfield cover both district 4 and 7.
3. One more note on Chesterfield and Henrico. These two counties create two halves of a donut that encompass Richmond City county. This provides an interesting option of comparing turnout differences within a county across different districts. Let's see if they are.
Read 21 tweets
Nov 29, 2020
Understanding VA-7 Turnout : As part of digging into the VA data sources, I've gone back to look at 2016 election results to understand the differences between the two. A key house is Virginia's 7th district where Abigail Spanberger(D) was defending her seat from Nick Freitas(R)
2. Spanberger won the seat in the 2018 election against incumbent David Brat. Result : ~176K (D) to ~169K (R). David Brat is famous for defeating Eric Canton in the Republican primary (first time a sitting House Majority leader had lost a primary).
3. Since turnout is generally higher for Presidential races (2016 / 2020), I figured it best to compare those figures in the analysis, but the 2018 results provide some useful context when looking at turnout differences.
Read 14 tweets
Nov 14, 2020
Limitations of High-Level Analyses Part 2 : Some out there are taking Dr Shiva's analysis and replicating it for Democratic votes to compare and see if the pattern is different. From a couple I've seen, there is a similar downward linear pattern that's less steep.
2. This has led some to conclude that this is in fact a natural pattern that has naturally occurred as the result of the local the electorate, and therefore, there's nothing untoward about the pattern. If it's happening for both Ds and Rs, it can't be a problem. Right? No!
3. When you see the same downward linear slope, it doesn't mean the local electorate is uniquely voting in those areas. It means that manipulation is occurring on both sides. The different in the steepness of the pattern allows to understand the severity of the manipulation.
Read 12 tweets
Nov 14, 2020
Limitations of High-level Analyses : After the Dr Shiva presentation, there has been a lot of effort dedicated to to understanding the pattern he showed in his graph. Many tweets speculating about the reason such a pattern might be true / reasonable.
2. Some have compared the graphs across elections (2016 and 2020) to understand how the trends compare and what the differences may mean in terms of the voters. While these analyses are interesting from an academic perspective, we should ask what is actually being compared?
3. Let's take a step back from voting results analyses, and consider what these results are and what they represent. Using a random county as an example, an analysis of this county's precincts will show us the outlines / broad pattern of the votes tabulated for the county.
Read 21 tweets
Nov 13, 2020
Deep Dive Explanation of Approach / Analysis : I want to provide the context of the work I am doing, and the reasoning behind it. I started this with a question : Why did R's do so well down ballot, and not at the top? In order to answer this question, I needed a suitable dataset
2. The ideal dataset would allow us to see, for each batch of ballots, the landscape of the votes (e.g. which candidates received the votes, and by what proportions). And not just any batch would suffice to perform this analysis.
3. Batches of ballots needed to be large (e.g. many ballots), and must include votes for Prez, Senate, and House Rep for both Dems and Reps (3 races x 2 parties). The batch is a self contained example of voting behavior, that would be random within a district.
Read 18 tweets

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