Case Study 2: The "Big Lie" in Contemporary Electoral Politics — The Post-2020 U.S. Electoral Fraud Claims

Chapter 8 | Part 2: Techniques

Introduction: A Contemporary Test Case

On November 7, 2020, major U.S. news organizations called the presidential election for Joe Biden. Within hours, President Donald Trump's campaign and allies began circulating claims that the election had been stolen through widespread fraud. Over the following weeks and months, these claims were amplified through presidential social media accounts, conservative media outlets, and a network of political organizations and fundraising appeals. They persisted despite an extraordinary volume of institutional refutation: over sixty court cases, multiple state-level audits, reviews by the Department of Justice under a Trump-appointed attorney general, and the assessment of the Cybersecurity and Infrastructure Security Agency (CISA) under a Trump-appointed director.

By the time of the January 6, 2021 Capitol riot — in which a crowd assembled under the claim that Congress could be pressured to overturn the certified election results — the claim had been publicly refuted more comprehensively than any comparable electoral fraud claim in American history.

Yet polling conducted in the years following the election consistently found that a substantial portion of Republican voters continued to believe the election had been stolen. Studies in 2021 found figures ranging from 50 to 70 percent of Republican respondents expressing skepticism about Biden's legitimate election.

This case study uses the post-2020 electoral fraud claims as a contemporary test case for the big lie mechanism introduced in Chapter 8. The purpose is not political advocacy; the case is selected because it is the most extensively documented contemporary instance of the big lie pattern, it has been subjected to more institutional fact-checking than any comparable case, and the gap between the evidential record and the persistent belief is therefore unusually stark and analytically instructive.

Part 1: What Was Claimed

The electoral fraud claims of November 2020 through January 2021 were not a single coherent claim but a family of related claims, each of which underwent revision as specific evidentiary challenges were mounted. The major claim clusters included:

The Dominion Voting Systems claims: Claims circulated that Dominion Voting Systems — a company that manufactured vote-tabulation machines used in multiple states — had software designed to switch votes from Trump to Biden, that the software had been designed in Venezuela for Hugo Chavez, and that the company's machines had been connected to the internet during the count and manipulated remotely. These claims were amplified by Trump attorneys Sidney Powell and Rudy Giuliani in public press conferences.

The Georgia allegations: Claims that Georgia's election had been stolen through specific acts of fraud: bags of illegal ballots brought in the middle of the night, illegal ballot drops by operatives, the same batches of ballots counted multiple times. The claims focused heavily on video footage from a vote-counting facility that was characterized in Trump campaign materials as showing fraudulent ballot-handling.

The Pennsylvania allegations: Claims of fraudulent mail-in ballot processing, illegal late-night ballot arrivals, Republican observers being denied access to the counting process, and statistical impossibilities in the reported vote totals.

The general statistical claim: Claims that Biden's vote totals in major cities showed patterns statistically impossible under normal election conditions — claims that deployed the language of statistical analysis (Benford's Law, vote-counting speed analysis) to imply mathematical proof of fraud.

The "hundreds of sworn affidavits" claim: The claim, made repeatedly by Trump's legal team, that hundreds of sworn witnesses had personally observed fraud — and that the mere existence of sworn affidavits constituted evidence that courts and authorities were ignoring.

Part 2: What the Institutional Record Showed

Each of the major claim clusters was subjected to scrutiny by multiple independent institutional processes, and the results were consistent:

The Courts

Trump's legal team and allied organizations filed lawsuits in Arizona, Georgia, Michigan, Nevada, Pennsylvania, Wisconsin, and other states. Over sixty cases were brought. The consistent result was dismissal or defeat — not on technical or procedural grounds (a claim sometimes made to suggest the substance was never examined) but on the merits, with judges across the political spectrum, including judges appointed by Republican presidents, finding that the claims lacked evidence sufficient to warrant the relief requested.

Key rulings included findings that: - The Dominion Voting Systems claims were "not substantiated" and that plaintiffs had "not demonstrated that they are justified in their claims" (U.S. District Court, Eastern District of Michigan) - The "bags of ballots" footage in Georgia showed legitimate ballot handling by authorized election workers, as confirmed by Georgia Secretary of State Brad Raffensperger — a Republican - Statistical claims based on Benford's Law were methodologically inappropriate for the type of data being analyzed

The Supreme Court declined to hear cases on the merits. The claim that courts were refusing to examine the evidence was directly contradicted by the rulings themselves, which in multiple cases extensively addressed the specific evidence presented.

The Cybersecurity and Infrastructure Security Agency

On November 12, 2020, CISA — the federal agency responsible for election security, whose director Christopher Krebs had been appointed by President Trump — issued a joint statement with the National Association of State Election Directors describing the 2020 election as "the most secure in American history." The statement specifically addressed the Dominion claims, noting that voting machines used paper ballots that provided a verifiable audit trail and had not been connected to the internet.

Krebs was fired by Trump on November 17, 2020, two days after the statement's release. His firing confirmed, for critics, the pattern of the big lie mechanism: institutional counter-speech is met not with engagement but with institutional retaliation against its sources.

The Department of Justice

Attorney General William Barr — Trump's attorney general, who had been a consistent political ally — stated in a December 2020 Associated Press interview that the Department of Justice had found no evidence of widespread fraud that would have changed the election outcome. Barr subsequently resigned. His assessment was subsequently confirmed by multiple DOJ investigations.

State-Level Audits

Multiple states conducted post-election audits specifically in response to fraud claims:

In Georgia, Secretary of State Raffensperger ordered a hand recount of all ballots statewide. The hand recount confirmed Biden's victory with a difference of less than 400 votes from the machine count. A subsequent audit of absentee ballots found no systemic fraud.

In Arizona, a Republican-led state legislature commissioned a private company (Cyber Ninjas, whose principals had publicly supported the fraud claims) to conduct a full audit. The audit, released in September 2021, found that Biden had won by a slightly larger margin than the certified results.

In Michigan, a bipartisan Senate Oversight Committee spent months investigating fraud claims and released a report finding "no evidence of widespread or systematic fraud in Michigan's prosecution of the 2020 election."

Part 3: The Big Lie Mechanism — Analysis

Why Institutional Refutation Failed

The post-2020 electoral fraud claims represent a test case for the big lie mechanism because the institutional refutation was unusually comprehensive, came from sources with strong bipartisan credibility (Republican election officials, Trump-appointed judges and agency heads), and was publicly documented in extraordinary detail. Yet the claims persisted in a substantial portion of the population. Understanding why requires applying the analytical frameworks from Chapter 8.

Scale and the incredulity mechanism. The claim that a presidential election was stolen through widespread fraud coordinated across multiple states, involving thousands of election workers across partisan lines, successful suppression of all physical evidence, and the complicity of multiple Trump-appointed officials in the cover-up — is a claim of extraordinary scale. The incredulity mechanism that the big lie exploits operated in both directions: some portion of the audience found it easier to accept the claim's scale than to accept that the former president would make a claim so enormous if it were false. The sheer audacity of the claim, and the institutional authority of the person making it, generated its own credibility.

The conspiracy expansion requirement. As institutional refutations accumulated, the big lie required an expanding conspiracy theory to sustain itself. Each refutation from a Republican official was absorbed by attributing that official's finding to corruption, intimidation, or complicity. Brad Raffensperger's confirmation of Biden's Georgia victory was interpreted as evidence that Raffensperger had been compromised. The CISA statement was explained by Krebs's subsequent firing — which was itself evidence of the conspiracy, not a refutation of it. The DOJ finding was explained by Barr's subsequent resignation. Each institutional counter-statement was incorporated into the conspiracy rather than allowed to falsify the claim.

This is the structural characteristic that the chapter identifies as distinguishing the big lie from ordinary political spin: the big lie is unfalsifiable by design, because any institutional source capable of refuting it is incorporated into the conspiracy it posits.

The repetition infrastructure. The claim was sustained by a significant media infrastructure — cable news outlets, social media amplification, political fundraising emails, and political speeches — that repeated it with sufficient frequency to activate the illusory truth effect. Audiences who encountered the phrase "stolen election" or "massive fraud" hundreds of times across these channels were subject to the normalization-through-repetition effect described in Chapter 11.

The motivated reasoning substrate. The claim was not deployed in a vacuum; it was deployed into an information ecosystem in which a significant portion of the audience had deep partisan motivations to find the claim credible. Motivated reasoning — the tendency to subject challenging information to more rigorous scrutiny than confirming information — provided the psychological substrate. Partisan audiences who wanted to believe the election was stolen subjected the institutional refutations to standards of skepticism that they did not apply to the fraud claims themselves.

The "where there's smoke" heuristic. Even audiences who did not fully accept the specific fraud claims were sometimes left with a vague sense that something must be wrong — that a former president would not make claims of this magnitude without some basis. This residual doubt is precisely the goal of the big lie in democratic contexts: not universal belief in the specific claim, but sufficient doubt about institutional legitimacy to reduce confidence in democratic processes.

The Institutional Target

The chapter argues that the big lie is specifically corrosive to democracy because it specifically targets institutional trust. This analysis is confirmed by the post-2020 case with unusual clarity.

The claim was not merely that Biden won through fraud; it was that the institutions designed to adjudicate electoral disputes — courts, election offices, auditors, federal agencies — were themselves part of the fraud. This institutional targeting was explicit and consistent: when courts ruled against the claims, the courts were corrupt or intimidated; when election officials certified results, they were compromised; when the Justice Department found no evidence, the DOJ was protecting the conspiracy.

The practical consequence was documented in subsequent research: the fraud claims were associated with significant declines in confidence in American electoral institutions among Republican voters — not just in the 2020 election specifically, but in the integrity of elections as such. This broader institutional confidence erosion is the most lasting damage inflicted by the big lie, because it affects the audience's capacity to accept the legitimacy of future electoral outcomes.

Part 4: The Anatomy of the Claim's Propagation

The Role of Media Infrastructure

The post-2020 fraud claims were amplified through a media ecosystem that gave them reach and repetition that no individual or organization could have achieved alone. Key components:

Presidential social media: Trump's Twitter account, with approximately 89 million followers, provided the primary amplification channel for fraud claims in the immediate post-election period. The claims moved from Trump's Twitter account to mainstream news coverage (correcting them) to conservative social media channels (amplifying them) in recursive cycles that provided both reach and the repetition paradox described in section 8.5.

Conservative cable news: Coverage on Fox News, Newsmax, and One America News provided sustained amplification of fraud claims. Fox News's subsequent legal exposure — Dominion Voting Systems' defamation lawsuit, which resulted in a $787.5 million settlement in 2023 — produced internal communications (released in discovery) that documented Fox News hosts privately expressing disbelief in the claims they were publicly amplifying, a factual record of unusual frankness about the big lie mechanism in operation.

Fundraising email campaigns: The Trump campaign and allied organizations sent thousands of email solicitations that repeated fraud claims while soliciting donations to "stop the steal." Federal Election Commission filings documented that the fundraising operation raised approximately $250 million in the seven weeks after Election Day. The economic incentives to sustain the claim were therefore structural, not merely political.

Social media networks: The hashtag #StopTheSteal and related phrases generated hundreds of millions of impressions across platforms. The virality dynamics described in Chapter 8 — simple claims traveling faster than complex corrections — operated at scale.

The January 6, 2021 Event

The convergence of the big lie with the mechanics of social mobilization produced the January 6, 2021 assault on the U.S. Capitol, in which a crowd assembled under the explicit claim that Congress could be pressured to refuse certification of the electoral results. The event was directly downstream of the fraud claims: participants in subsequent trials and hearings testified to their belief that they were acting to prevent the fraudulent outcome of a stolen election.

The January 6 Committee investigation — whose findings were released in December 2022 — documented the specific pathways through which the fraud claims had been communicated, the evidence that the architects of the claims knew they were false or had not established evidentiary support, and the operational planning that translated the claims into the mobilization of a crowd.

Part 5: What This Case Teaches About the Big Lie Mechanism

The Democratic Context

The post-2020 case illustrates how the big lie mechanism operates in a functioning democracy — a context significantly different from the totalitarian context in which the technique was theorized and first deployed at scale.

In the Nazi context, the big lie (the stab in the back myth) was deployed before institutional capture was complete, and institutional capture then insulated it from counter-speech. In the post-2020 case, the big lie was deployed in a context where the institutional counter-speech apparatus remained largely functional: courts ruled, officials certified, agencies investigated, journalists fact-checked. The big lie persisted despite this counter-pressure because:

1. It had sufficient media infrastructure to provide the repetition required for the illusory truth effect.
2. It was deployed by a figure with presidential authority, activating the credibility-of-audacity mechanism.
3. It operated in a partisan media ecosystem that sorted audiences into information environments with very different exposure to the counter-speech.
4. The motivated reasoning of a partisan audience provided additional resistance to correction.

This is the democratic variant of the big lie: it does not require institutional capture to survive; it requires only a media ecosystem sufficiently fragmented that a significant portion of the audience can be insulated from institutional counter-speech.

The Limits of Fact-Checking

The post-2020 case is significant for researchers studying the effectiveness of institutional fact-checking. The claim was subjected to fact-checking of unusual comprehensiveness — not just by media fact-checkers but by government agencies, courts, and political figures of the same party as the claim's promoter. The result was that institutional fact-checking:

• Did not prevent the claim's initial propagation (the speed asymmetry of false versus true claims operated normally)
• Did not prevent the claim's persistence among the partisan audience most predisposed to believe it
• May have contributed to its spread through the repetition paradox (each correction cited the claim)

This does not argue that fact-checking is useless — there is evidence that institutional refutation limits the claim's spread to less-partisan audiences. But it confirms the chapter's analytical point that the big lie, in the democratic context, is sustained not through control of information but through the fragmentation of information environments.

The Ongoing Consequence

The lasting analytical legacy of the post-2020 electoral fraud claims, as of this writing, is not the specific claims themselves but the institutional trust damage they produced. Survey research consistently documents lower confidence in electoral institutions among audiences exposed to sustained fraud claims — not because the specific claims are necessarily believed in detail, but because the campaign of sustained doubt has reduced the baseline assumption of institutional reliability.

This is the big lie's most durable output in democratic contexts: not a specific false belief but a generalized skepticism about institutional truth-telling that makes future big lies easier to propagate. The audience that has been trained to distrust election officials, courts, and federal agencies is an audience that has been partially pre-inoculated against the institutional counter-speech that would otherwise limit the next big lie.

Conclusion: Lessons for Democratic Resilience

The post-2020 electoral fraud claims confirm several of the analytical claims made in Chapter 8 and add several observations specific to the democratic context:

1. The big lie can persist in a democracy without institutional capture — provided it has sufficient media infrastructure, partisan motivation, and authority-halo from a credible political figure.

2. Institutional counter-speech is necessary but not sufficient — the volume and quality of refutation was extraordinary, and it was insufficient to prevent the claim's persistence among the targeted audience. Structural conditions — media fragmentation, partisan sorting, motivated reasoning — limited the effective reach of institutional counter-speech.

3. The fundraising incentive sustains the claim beyond its political utility — the $250 million raised on the "stop the steal" campaign created a financial infrastructure with incentives to sustain the claim independent of any political strategy.

4. The conspiracy expansion requirement is observable in real time — the progressive incorporation of each new source of refutation into the conspiracy is documented and analytically transparent in this case, making it a particularly useful teaching example.

5. Institutional trust damage is the lasting output — the most significant consequence of the fraud claims, as measured by subsequent research, is not the specific beliefs they generated but the generalized institutional skepticism they produced, which will make democratic truth-arbitration harder in future cycles.

Case Study 2 connects to Chapter 24 (Digital Disinformation: The 2016–2020 Campaigns), which addresses the broader information environment in which the post-2020 claims operated. Chapter 35 (Law, Policy, and the Regulation of Propaganda) addresses the First Amendment questions raised by the big lie in democratic contexts.