Election Night Confirmed the Polls Were Lies
We spent the last several months in a fog of coordinated propaganda posing as polling.
Via American Greatness, Harvard Crimson
As the old saw goes, “There are three kinds of lies: lies, damned lies, and statistics.” As of this writing, the 2020 election outcome for the two candidates hangs in the balance. But whatever happens, the American people now know that the polls were a deception.
In an era during which more than 90 percent of voters committed to a decision weeks before election day, we were asked to believe Biden was up 47 percent to 42 percent in Florida. He was up six points in North Carolina, 12 points in Michigan, and eight points in Wisconsin. Days ago, the president supposedly was underwater in Ohio by four points. Did people change their minds? No, of course not.
It’s hard to know exactly when the polling process became contaminated. Were these shy voters who refused to talk to pollsters? Trump supporters seemed increasingly less “shy” as thousands thronged to impromptu public parades and rallies. But we can suspect that the polls consistently erred on the side of a President Biden for the same reason that the legacy media so clearly abuses its readers with misinformation: They’re liars. The polls are lies and the reporting on the polling is lies.
The signs have been there for months. Trump supporters knew they were being lied to. But some Biden voters suspected it. A few true liberal holdouts began nervously grumbling about the Big Tech censorship of the Hunter Biden financial scandals. African Americans, Hispanics, LGBTQ, and blue-collar workers increasingly have resisted their typecasting. Famous rappers began giving cultural permission to vote for Trump.
Like kamikaze planes splashing harmlessly in the sea adjacent to their targets, the legacy media either lied to America or themselves as they squandered the last shreds of illusionary credibility. The polls were never meant to reflect public opinion. They were always about shaping the opinion. And as the day of reckoning approached and the real opinion failed to follow the pollster’s wishful thinking, many tried to pull out of their dives, reporting a “tightening” race.
Balderdash. The opinions have not changed that much in just a few days. Full Story By Adam Mill @ American Greatness
Harvard Researchers Warn 2016 Polling Mistakes Serve as a 'Cautionary Tale' in 2020
Harvard Government Ph.D. candidate Shiro Kuriwaki and Michael G. Isakov ’22 cautioned against “overconfidence” in polling data in a paper published Tuesday on their analysis of pollsters’ incorrect predictions 2016 Democratic presidential nominee Hillary R. Clinton would win the previous election.
👉 Understanding Public Opinion Polls
Kuriwaki and Isakov’s paper, published in the Harvard Data Science Review last week, identifies mistakes in 2016 polling and posits ways to correct these mistakes.
The paper explains that sampling biases were partly to blame for polling mistakes in the 2016 presidential election.
Shortly after the election, some analysts attributed errors in polling to the so-called “shy Trump” effect, in which voters would purportedly lie to pollsters as they were embarrassed to express support for Trump. Kuriwaki and Isakov, however, wrote that analysis of the 2016 polls reveals that mistakes were more likely due to a “sampling problem,” rather than the “shy Trump” effect.
“There was very little evidence of that, partly because there were similar errors for other Republican candidates,” Kuriwaki said in an interview. “So if people were just lying about Trump, you won't see that pattern.”
Kuriwaki and Isakov wrote that polls are most reliable when the sampling pool is representative of the general population, but noted that polls often fall victim to selection bias and disproportionately sample certain demographics.
Pollsters improperly corrected these biases in 2016, which caused the polls’ distorted results, according to the authors.
Poll aggregators also contributed to polling error in 2016, according to Kuriwaki and Isakov.
“When aggregators say there's a 93 percent chance of Hillary Clinton winning, some people think like, ‘Oh, she'll get 93 percent of the votes,’ which is not true,” Kuriwaki said. “But if you say the model tells you that Hillary Clinton will get 53 percent of the popular vote, which is one of the predictions, then people might have the right level of uncertainty.”
“2016 headlines made people more overconfident about the actual results,” he added.
They wrote their research describes a “cautionary tale” they urged pollsters to be responsible in the way they present results. . . Full Article By Raquel Coronell Uribe @ Harcard Crimson