(TargetLiberty.org) – An upcoming study by the Crime Prevention Research Center (CPRC) President John Lott, Jr. is reigniting debate about the role of voter fraud in the 2020 election. Lott’s research paper, which has yet to be published, compares data from various precincts and attempts to identify gaps in absentee ballot numbers across party lines. While the analyst is careful to label his results “inconsistent,” they suggest potential discrepancies in six key swing states.
Methodology
Lott’s study, titled “Simple tests for the extent of vote fraud with absentee and provisional ballots in the 2020 US presidential election,” technically remains incomplete and unpublished. However, what information is available so far is open to the public via the Social Science Research Network (SSRN). Lott says the peer-reviewed economics journal Public Choice recently picked it up and intends to publish it soon.
Lott’s methodology is somewhat unique: he applied three separate tests for voter fraud to data sourced from a number of key regions across the United States, including Arizona, Georgia, Michigan, Nevada, Pennsylvania, and Wisconsin.
First, he compared information from precincts in swing states accused of fraud to close neighbors who faced no such allegations. Some of these locations were so close in distance, they effectively fell on either side of county lines or sat across the road from one another.
Next, Lott compared absentee ballots filed in favor of former President Donald Trump with those filed in favor of Joe Biden. He factored in differences between the aforementioned neighboring precincts, in-person votes for Trump, and overall voter registration demographics.
Lastly, Lott investigated factors that prompted “artificially” larger voter turnouts, such as votes submitted by the deceased, increases in absentee ballot submission, and examples of people being paid to vote along specific party lines.
Strange Results
Lott also separately examined results from Pennsylvania and Georgia. At first, the resulting data produced only weak evidence for voter fraud in either region. He combined information from both areas and reran the same tests.
That’s when the bigger picture began to shift.
Combined results from Allegheny, Pennsylvania, and Fulton, Georgia suggested an excess of 10,000 votes for President Joe Biden. Around 67% of the discrepancy came from Allegheny alone (6,700 votes), where voters were allowed to file provisional ballots to correct problems with absentee ballots on Election Day.
Total results across all precincts came in at an average of 255,000 excess votes in favor of President Joe Biden. That’s statistically significant, but is it really proof of fraud?
A Developing Theory
Lott theorizes that comparing results in bordering precincts should help raise red flags for systemic fraud. He suggests because these locations are often nearly identical demographically, any differences should be considered cause for concern.
However, whether or not the logic is truly sound isn’t as straightforward. For example, in the case of Allegheny County, Lott suggests permissive attitudes toward the absentee ballot process contributed to the “excess” votes for Joe Biden.
Some would call it correlation rather than causation, and the data just plain isn’t sufficient evidence to overturn the 2020 election or get Trump reinstated, anyway. But as Lott points out in a recent article for Real Clear Politics, that isn’t what he was trying to achieve.
Instead, the analyst hopes his data will draw attention to the very real and very provable issue of voter fraud in the United States. Both Democrats and Republicans agree that some measure of fraud occurs during every election.
Lott condemns people like Sidney Powell, who made broad fraud claims but failed to follow through with any actual proof. He hopes that the study will at least draw attention to the matter and show that it represents a clear and present danger to electoral integrity. Moreover, it’s an entirely resolvable, bipartisan issue — so long as leaders don’t turn a blind eye to it.
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