Proof That the 2020 Election Wasn’t Stolen, Which No One Will Read – BCB #88
Also: Sweeping statements fuel political polarization, and campuses’ tolerance of controversial speakers varies by topic
Here’s comprehensive evidence that the 2020 election was fair, but it doesn’t matter
Researchers at Stanford conducted a massive study chasing down every election fraud claim and found that there isn’t evidence to support any of them.
All of the claims we evaluate fail to provide evidence of fraud or illegal voting. Trump’s claims of fraud or illegality are riddled with errors, hampered by misunderstandings about how to analyze official voter records, and filled with confusion about basic statistical techniques and concepts. Often, the claims are based on the casual impressions of what happens in a “normal” election based on little more than intuitions.
The problem with this research is that it has no natural audience. Those who already think Biden legitimately won aren’t going to wade through 85 pages just to confirm their beliefs. Conversely, Red folks who believe the election was stolen won’t be interested in reading such studies — in much the same way that Blue is unlikely to read extended criticisms of climate science.
Further, this work is likely to come off as dismissive and disparaging to Red readers. For them to want to read it, it would have to be written with sensitivity to their deep sense of loss. And it would need to include appropriate caveats, such as the fact that there is always some amount of voter fraud. An Associated Press analysis found 475 votes under investigation nationwide — a tiny fraction, too small to tip any state, and about the same low rate seen in previous elections.
Interestingly, eight prominent Red thinkers laid out similar evidence in a 2022 report, “Lost Not Stolen.” That document makes “the Conservative Case that Trump Lost and Biden Won the 2020 Presidential Election.” It’s potentially less biased, or at least has the appearance of being less biased, because it’s in-party criticism (see our issue on surprising validators).
For us, the lesson here is that this attempt at rigorous factuality will have little short-term impact on political discourse. Not that it’s not valuable work! It’s essential to have a comprehensive analysis of claims and evidence. In some cases, perhaps legal cases, this will prove decisive. But for most of us, this has long since ceased to be about the evidence.
How imprecise language amplifies polarization
“Democrats love open borders.” “Republicans think federal income tax is too high.” New research has found that using generic language like this to describe political beliefs may amplify perceived differences between political parties, increasing already incorrectly extreme perceptions of what the other side believes.
In one experiment participants were asked how much each party would agree with a generic statement (e.g. “Democrats believe that we are spending too little on space exploration programs”). For controversial issues there was an overestimation of support within their own party and underestimation in the opposing party, leading to an exaggerated perception gap between parties.
Even small differences in how much Democrats and Republicans supported various policies led people to make broad generalizations. For example, if Democrats slightly more often supported a policy than Republicans, people would conclude “Democrats believe X” and “Republicans do not believe X,” even if the difference in support was small. This highlighted the potent role of generic language in exaggerating perceived differences between political parties, suggesting that such language could be contributing to the polarization observed in the political landscape.
This research also found that people were much better able to recall generic statements attributed to politicians, rather than specific statements. Participants were significantly more likely to remember information in broad, generic terms, regardless of how it was initially presented. This illustrates how the nuances of party positions get drowned out and many people tend to draw polarized conclusions.
Lastly, participants were presented with fictional statements saying that “Democrats” or “Republicans” generically held certain views, or alternatively more specific statements that they were held by “many” or “some” members of a party. Generic statements led to exaggerated guesses of how many people in the named party held a particular view, and underestimates of how many people in the un-named opposing party held that view.
In short, these studies demonstrate that generic statements lead people to misinterpret and misremember a party’s or politician’s positions in ways that make people seem farther apart than they actually are. The implication is clear: speak in specifics, not stereotypes, to avoid making polarized misperceptions worse.
Campus tolerance of speakers depends on the topic
US students' tolerance of controversial campus speakers appears to depend on the topic, with no massive difference in Red or Blue forbearance. A new “campus climate” survey by FIRE asked students from private and public universities whether they would allow speakers who promote various controversial ideas.

When we covered tolerance for campus speakers in our censorship issue, it seemed like Blue was less accepting of controversial speakers. This study asks about a larger number of issues and paints a more symmetrical outcome, mirroring the pattern we wrote about in our issue on conspiracy theories. Conspiracies seem very Red in some studies which ask only about a small number of examples, whereas a more exhaustive survey finds that each side believes in its own theories.
I am, perhaps, the natural audience for this evidence that the 2020 election wasn't stolen. I'm on the left side of the US political chasm, so this is what I want to believe, but unfortunately I've caught a non-negligible number of members of my own side spreading misinformation, including both falsehoods and data-free statements likely to provoke emotional responses. My biases say "of course the election wasn't stolen", but I mistrust both my biases and randos making claims that I want to agree with.