CODE RED-Computerized Election Theft

CODE RED-Computerized Election Theft and The New American Century

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Notes on Election Forensics, Exit Polls, and Baseline Validation

August 8, 2018 By Jonathan Simon

As an election forensics analyst, I have frequently been called upon to explain and defend pattern evidence indicating the targeted mistabulation of votes as a probable cause of pervasive anomalies and disparities. While far more detailed explanations can be found in a number of studies my colleagues and I have conducted, I think it may be useful to set out the fundamental bases for reliance on the approaches we have taken and the conclusions we have reached.

First a word about the need to rely on such “indirect” methods of election verification. It is not something that has been thought about or talked about much, but the vote counting process in the United States is designed for concealment. Most absurdly, the code that counts or miscounts votes has been ruled a corporate trade secret that cannot be divulged or examined under any circumstances.

Nor does the concealment stop with the code. All the “hard” evidence—memory cards, programming code, server logs, and actual cast ballots—is strictly off-limits to the public and, in most cases, to election administrators as well. Given that two corporations supply nearly 80 percent of the hardware and software used to count votes in the U.S., and given that the handful of equipment suppliers and their handful of programming/distributing satellite contractors actually constitute a consolidated and easily targeted closed (indeed virtually hermetic) system, no comfort should be taken from erroneous reassurances that the process is somehow too “decentralized” to be vulnerable to either hacking or insider manipulation.

It is precisely because of the secretive nature of the American vote counting process and because all the hard evidence is inaccessible, that the forensic investigation of election security and authenticity perforce has come down primarily to numerical, statistical, and pattern analysis. Following along after the election circus with a forensic pooper-scooper may not strike you as the best way to try to insure democracy; but until the public reclaims its right of access to voted-on ballots and the counting process, it just happens to be the only way we’ve got.

That said, such numerical, statistical, and pattern analysis is relied upon routinely in fields ranging from aerospace to economics, climate study, epidemiology and disease control. It is also routinely applied, often with the sanction of the government of the United States, to elections pretty much everywhere on Earth other than in the United States, periodically leading to official calls for electoral investigations and indeed electoral re-dos. Exit poll disparities have factored in the overturning of elections from the Ukraine to Peru and are relied upon for validation of votecounts in Western democracies such as Germany.

Disparities, whether in a bank audit or in an election, require explanation. Which is to say, when measurements of what is ostensibly the same phenomenon fail to agree, there exists some cause: one or both of the measurements are inaccurate. In the case of elections, it has generally been assumed that the votecounts are accurate and any other incongruent measure is therefore erroneous. There is, however, given the known vulnerabilities of the vote counting process to manipulation, little or no basis for that assumption of accuracy. As for the other, incongruent measures, there is also no reason to assume their accuracy. If they are to serve as baselines for assessing the accuracy of vote counts, these other measures must themselves be validated. Much of our work as forensic analysts goes into that process—and it is that work that is often ignored or misunderstood in the rush to dismiss red flags and “protect the shield” of our elections.

When official votecounts come out to the right of other measures of voters’ intent—such as exit polls, pre-election polls, post-election polls, and handcounts—forensic analysts refer to it as a “red shift.”1 Since 2002, when the computers took over the counting, the red shift has been pervasive: election after election, in competitive contests bearing national significance,2 the official votecount has been to the right of every baseline measure. We very rarely see the reverse, which we would call a “blue shift.” There is a tremendous amount of data and it all points in the same direction.3 It is critical to grasp the enormous difference in probative value between a single statistical red flag and this years-long parade of unidirectional red flags. The latter rules out chance, glitches, flukes as cause, leaving only systemic inaccuracies and distortions of either the votecount or the baseline measures as possible explanations for the pattern.

From a forensic standpoint, as noted above, much of our work goes into determining whether those baselines from which the official votecounts keep diverging are themselves valid. Naturally, if you simply assume all votecounts are valid, you would then look for reasons to dismiss any data that disagrees with them. You could, for example, disparage all the incongruent exit polls as “off again” because they “oversampled Democrats.” However, we have examined exit poll samples and other baselines closely and found that such is not the case—the problem is definitely not that all these other measures of voter intent are chronically incompetent or corrupted.

In 2006, for instance, we examined the national exit poll sample and found that it was to the right of every other independent measure of the national electorate. We knew, therefore, that the massive red shift we found in the 2006 election could not have been a function of a faulty (i.e., left-skewed) exit poll baseline, leaving mistabulation of the votes as the only explanation for the shift that could not be discounted.4 We went further in 2006 (and again in 2008) and, recognizing that competitive races are natural targets for rigging (the outcome can be altered with a modest manipulation, yielding a high reward/risk ratio) while noncompetitive races are not (much higher risk factor: to alter the outcome you have to shift too high a percentage of votes to pass the smell test), we compared competitive with noncompetitive races relative to an identical baseline. We found that the more competitive a race the more likely it was to be red shifted—the correlation was dramatic.5

In 20106 we were able to compare hand-counted to computer-counted ballots in a critical U.S. Senate race (Massachusetts: Coakley vs. Brown) and again found an outcome-altering red shift of the computer-counted votes, one that we were unable to explain by any factor other than strategically mistabulated votecounts.7

More recently, in 2016, our analysis of the respective party primaries found that, while the exit poll results were consistently accurate throughout nearly all the Republican primaries, they were wildly and broadly inaccurate in the Democratic primaries, exhibiting a pervasive intra-party “red shift” to the detriment of Bernie Sanders. It seems very unlikely that the same pollsters, employing the same methodological techniques and interviewing voters at the same precincts on the same days, would be competent and consistently successful with Republicans but somehow incompetent and consistently unsuccessful with Democrats.

In the 2016 general election, the critical “swing” states that provided Trump’s electoral college majority—including Wisconsin, Pennsylvania, Ohio, and North Carolina—were among the most egregiously red-shifted of all the states, with poll-votecount disparities far outside the margins of error.8 As in the election of 2004 and the 2016 primaries, it was the overall contrasting pattern that was most remarkable—as the National Exit Poll, which impounded the many “safe” states where manipulation was not suspected, was not red-shifted outside the margin of error. That is, the pollsters “got it right,” except in those states with close Trump victories that produced his Electoral College majority. We can of course choose, at our peril, to believe that, election after election, such things “just keep happening.”

E2016 in fact offered up a quintessence of what is wrong with whatever debate there is over indicators of electoral foul play, and the general under-appreciation of the subtlety of forensic analysis. Much was made of the apparently egregious over-representation of college graduates in the National Exit Poll sample. With an “Aha!” that could be heard on Mars, the poll was declared “garbage” and tossed hastily and permanently in the shredder because 50 percent of its respondents had declared themselves to be college grads. The impact of education level on candidate choice was modest (about the equivalent of gender and far below race), but this did not stop the critics from fastening on the 50 percent figure (which it must be said would not even have been available to fasten on were the exit polls as opaque in their revelations as are the votecounts), which they calculated implied an unrealistic rate of turnout among college grads.

What the scoffing and whewing herd apparently failed to notice was that the exit poll they had just trashed—along, it soon became clear, with every other exit poll ever conducted or to be conducted in the United States—was accurate! That’s right, accurate. The unadjusted National Exit Poll approximated Clinton’s popular vote victory margin within 1.1 percent. It was accurate enough as to require hardly any adjustment—and, if it hadn’t been for the major disparities in the Trump table-run battleground states, would not have required any adjustment at all.

How, then, to read this riddle? How could a poll with such an apparent demographic goof wind up so close to the mark? What no critic apparently understood, or wanted to understand, is something very basic and essential to exit poll methodology: multiple stratification (weighting). Exit pollsters know enough not to expect equivalent response rates across race, age, gender, income, education, and partisanship groups. They use data-rich models, as in many other sciences, to weight their samples accordingly. It has been my observation that the aggregate impact of these multiple weightings—because they are grounded at least in part on demographic data derived from prior elections’ exit polls that have been adjusted rightward to congruence with red-shifted votecounts—tends to be rightward. That is, there are factors in the exit pollsters’ weighting algorithm that tend to chronically push the sample a few points to the right. The over-representation of college grads pushed the sample a point or two to the left. Such weightings tug against one another—so, for example, the sample might wind up over-representing the college-educated but under-representing non-white voters. The art and science of exit polling lies in getting those balances right, and they’ve sure enough had a lot of practice (in fact, prior to the computerized voting era, the main problem with exit polls was that they were so accurate that the pollsters had to agree to withhold their results until polls had closed in order not to discourage late-day turnout).

It’s a complex process and you could say, I suppose, “the secret’s in the sauce” (although, again, this sauce is far less secret than the votecounts themselves—the numbers are there to inspect and compare, at https://www.cnn.com/election/2016/results/exit-polls/national/president for the adjusted National poll and on this website for the unadjusted screencaptures, along with a more complete analysis of the polling methodology).

But you can also say “the proof’s in the pudding.” The fact is that the National Exit Poll—the one torn apart by a posse of critics sorely lacking in understanding of exit poll methodology, many of whom have been hell-bent on discrediting exit polls as a verification tool since 2004—got it right, while the exit polls by the same firm, using the same methodological “sauce,” in the critical battleground states table-run by Trump, were way off, all in the same direction. That is a damning second-order comparative, and the best evidence we can get from a system determined to withhold all its “hard” evidence, a process designed for concealment. So far, to my knowledge, no one has established a benign explanation for this, or numerous other, telling patterns of disparity.9

I hope that any reader troubled by the evidence summarized here, and/or by its facile dismissal by those who would prefer not to grapple with its implications, will take the time to examine the studies included in the “Evidence and Analysis” chapter of CODE RED, all of which are fully accessible to the non-statistician. In conclusion, the key point is that it is not just a few instances or an equivocal pattern, nor can it be attributed to skewed baselines—it is pervasive. It is difficult to look at all this data gathered together and not emerge gravely concerned that elections have been systematically manipulated and strongly moved to further investigate that possibility.

Careful! The Danger of Tuesday’s Democratic Sweep . . . To Elections and To Democrats

November 9, 2017 By Jonathan Simon Leave a Comment

With no apologies for being the turd in the punchbowl, I want to share my reading of yesterday’s election. There’s a lot of undisguised celebrating going on – even among the nominally and professionally impartial – and I have already had to respond to a fair number of “See I told you there was nothing to worry about!” pokes. However . . .

Lest anyone for a minute believe that yesterday’s results – the Democratic sweep and thump of #Trump – provide assurance that our elections are now secure and that no one is targeting 2018 or 2020 for votecount manipulation, please understand that that is seriously wishful thinking. There are very good reasons that entities with capacity to interfere with the counting process in these particular contests would have taken a pass, which it appears they did.

1) The actual victory margins in key contests were large – altering outcomes would have brought the smell test very much into play.

2) The prizes, significant as they may be, were a drop in the bucket compared to what is on the table in 2018. Given the now-heightened scrutiny of our election processes (and of course concerns about “the Russians”), it would make little strategic sense to trigger red flags now – thereby putting urgency into the effort to button-up election security before 2018. Indeed it would have been a gross strategic blunder.

3) Virginia had decertified its paperless machines (DREs), so that, unlike GA-6 this summer, voting was entirely on paper and recounts/audits would have been in play in the event of “issues” with the count (anomalous results, exit poll-votecount disparities, etc.). In fact, five state legislative elections are being recounted, with control of the Virginia House of Delegates in the balance. Election administration at the state level was, crucially, under Democratic control. New Jersey, although using DREs, was simply too big a margin – a Guadagno win would have failed the smell test spectacularly.

Even for those contests within smell-test range, the overarching analogy here is to the pool shark: missing makeable shots is part of the hustle, indeed essential to the hustle. Same for a poker cheat. If you win every hand, either no one will play or they will start making you play in short sleeves. You save those up-sleeve aces for the big pots.

We’ve been around this block many times. People can’t wait to say “There! You see, it’s all good now!” When Democrats win, whether it’s Obama in 2008 and 2012 (the mechanisms for which are explained in detail in CODE RED or in E2017 this Tuesday, the reflex assumption is that it proves U.S. elections are safe and secure. This is, ironically, because virtually every piece of evidence collected over the 15 years of the computerized vote-counting era points to distortions or manipulations favoring the more right-wing candidate or position. If some champion of the Right is so good at rigging, goes the thinking, and if elections could still be rigged, why would he/she/it ever, in a competitive election, allow the Democrat or left-winger to win? Ipso facto, Tuesday’s result prove rigging is not possible, so the thinking goes.

Strategically, rigging Tuesday night would have been idiotic, but we will have to spell this out over and over again, so strong is the desire to seize upon any apparent evidence that things are on the up and up.

Yesterday’s results should do nothing to reassure anyone about the security of our elections or diminish by a hair the urgency of our efforts to restore public and observable vote counting. We have seen way too many aces drop out of sleeves to think for a minute that this game is being played straight. If we do, we’re the perfect mark.

To me, ironically, the takeaway from yesterday is that this is more or less what elections in an observably counted United States would look like: Unadjusted Exit Polls, for the first time in 15 years, spot-on wherever conducted; no “red shift;” no head-scratching, against-interest, right-wing victories.

But anyone who draws the conclusion, based on yesterday’s results, that 2018 won’t be rigged is someone I’d love to play poker with.

Yesterday’s results speak volumes about the truth of our country and are worth real celebration. Then . . . back to the task at hand.

Donald Trump Warned of a “Rigged” Election: Was He Right?

June 27, 2017 By Jonathan Simon

With Donald Trump formally installed in the Oval Office, election integrity activist Jonathan Simon crunches the numbers and reflects on Election 2016, the death of electoral transparency and the thwarting of public will.

As Published in MintPressNews
By Jonathan D. Simon @JonathanSimon14 | January 24, 2017

Whether viewed in terms of outcome or of process, the story of the 2016 presidential election is one so grim that it calls for a trigger warning for anyone of ethical sensibilities or faith in the workings of democracy. In a year that will be remembered by many for the number of revered individuals we lost, it is an open question whether our democracy itself should top the list of the dearly departed, or whether rumors of its demise are exaggerated and it is with us still, lingering on in the ICU and facing a long and arduous road to recovery. If one of democracy’s vital organs is acknowledged to be an electoral process that permits the undistorted translation of collective public will into the electoral results that determine leadership, policy, and national direction, then 2016 goes down as the year that this vital organ, long diseased, finally failed. If the patient is to be nursed back to health, our search for a cure begins with a thorough case history and an unblinking examination of our stage-4 electoral pathology.

How did we get here?
An election year is made up of innumerable events and constant flux. If we take an alpha-to-omega overview of the 2016 presidential election, the first thing that jumps out from the thousands of event pixels is the fact that America entered 2016 with the near consensus recognition that something serious needed to be done to deal with runaway economic inequality. The year ended, however, with a president-elect and Cabinet representing not the “1%,” but the “0.1%,” portending not merely a step but a giant leap away from economic equality and toward outright plutocracy. The nation that came into the year coalescing around the need to seriously address climate change and the easy availability of guns, exited it in the hands of a climate change denier and new darling of the NRA. A nation that seemed anxious about the relatively mild pay-to-play concerns raised by the Clinton Foundation, wound up with an all but branded White House, its chief and ancillary occupants boasting more and deeper conflicts of interest than any in our long history.

In reviewing the elections of the year 2016, we will want to ask how we wound up, in virtually every dimension, zigging when we meant to zag. How did such a seemingly fundamental reversal of public will (and taste) come to pass? How did the gears of our electoral process mesh (or slip) to lead us to such a bleak moment in our national journey, as we rang in the New Year in our hospital bed, a forlorn “Get Well Soon” balloon bobbing from the bedpost.

Emergence of the politics of disgust
In the dog days of 2015, the ho-hum assumption was the “inevitability” of a Jeb Bush/Hillary Clinton matchup, or at least some tight variation on that theme. But as the campaigns got started in earnest and the public began to displace the pundits and weigh in with their votes, a very different picture began to emerge. It seemed that “upstarts” like Donald Trump and Bernie Sanders were pulling bigger crowds and generating far more enthusiasm than any of the “establishment” candidates, wherever those candidates attempted to position themselves on the traditional political spectrum. Voters — right, left, and center — registered their distress at the dysfunctionality and unresponsiveness of the political hierarchy by turning to candidates promising some sort of fundamental change.
Trump, who promised change from the right, melted his various, more conventional opponents and became the Republican nominee. Sanders, who promised change from the left (and who consistently far out-polled both Trump straight-up and Clinton when tested in matchups against Trump), was sent packing. Was there any more to that primary season outcome than simply one upstart winning and another upstart losing? The forensic answer to this question was troubling.

Attempting (and failing) to verify computerized vote counting in the primaries
Since votes are counted unobservably in the pitch-dark of cyberspace and our voting equipment and programming (unlike our footballs) are essentially off-limits to inspection, election forensics comes down perforce to indirect measures of patterns and anomalies, from which red flags may emerge to suggest “problems” with the vote counting process. Baselines commonly used for this verification process range from exit polls and pre-election polls, to hand counts (in the very few places where they still exist), to parallel contests too noncompetitive to be likely targets for malfeasance, to vote count patterns correlated with type or brand of counting equipment (e.g., paperless touchscreen vs. optical scanner or Dominion Voting vs. ES&S). In the 2016 primaries, it was primarily the exit polls that waved the red flags, although there were other strongly corroborating indicators.

Unlike previous eras, exit polls — or at least those in competitive elections bearing national significance — in the era of computerized voting have been so habitually “off” in the same direction (to the “left” of the vote counts) that many, having first presumed the accuracy of the vote counts, have come to dismiss the polls as faulty, the pollsters as biased or incompetent. This jaundiced view prevails despite the existence of studies confirming the demographic validity of exit poll samples.

But the pattern of exit poll and vote count results in the 2016 primaries was strange enough that it should have given pause to even the most hardened skeptics. To continue reading, please click HERE.
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Notes on Election Forensics, Exit Polls, and Baseline Validation

Careful! The Danger of Tuesday’s Democratic Sweep . . . To Elections and To Democrats

Donald Trump Warned of a “Rigged” Election: Was He Right?

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