Episode Details

The aware understand that free speech is required for freedom to reign. Our Framers understood it well, and that’s why it is enshrined in the First Amendment to the US Constitution in the Bill of Rights. But how does a free society protect free speech from nefarious charlatans who abuse that right for personal and ideological gain?

Such is the question we face today when we examine the partisan politics that have metastasized like cancer throughout the mainstream media complex and, to drill down into one aspect of that niche, the pollsters.

In an era of high political polarization, trust in polls has waned, particularly among certain voter groups. This distrust manifests in lower response rates and sometimes (and this is growing) dishonest responses, further skewing poll results. There has also been a trend where polls “herd” their respondents towards an expected result to avoid being an outlier, which can lead to a uniform but inaccurate picture.

The American Association of Public Opinion Research published a white paper on herding that read:

“Herding” specifically refers to the possibility that pollsters use existing poll results to help adjust the presentation of their own poll results. "Herding” strategies can range from making statistical adjustments to ensure that the released results appear similar to existing polls to deciding whether or not to release the poll depending on how the results compare to existing polls. By drawing upon information from previous polls, herding may appear to increase the perceived accuracy of an individual survey estimate…”

The white paper said that one troublesome consequence of herding is that pollsters who engage in the practice will produce artificially consistent results that don’t accurately reflect public attitudes. This perceived polling consistency instills false confidence about who will win an election, thereby artificially impacting how the media covers the race. The white paper’s author goes on to say that the faux consistency becomes a major factor in whether political campaigns and parties “devote resources to a campaign, and even if voters think it is worthwhile to turn out to vote. “

So, by the conscious decisions made by the polling companies and, most of the time, by the individual pollsters themselves, even the associations that champion their “science” admit that industry practices artificially affect elections.

In 2020, Maddy Weinberg, writing from the University of California at Berkeley, noted that data analyzing over 1,400 polls from 11 election cycles revealed that only 60 percent of polls conducted the week before an election included the actual outcome. This doesn't sound too bad to those defending the “science” of polling, but to the consumer, that result is a failing grade.

The defenders of this failure spin it this way:

“It’s really important to remember that these polls are not forecasting who’s going to win. They are an estimate of likely vote share. So this is about whether the truth falls inside the confidence interval, not whether the poll calls the eventual winner.”

And pollsters often use statistical models manufactured to adjust or “weight” their data to—as they see it—to better reflect the broader population. However, these adjustments often introduce errors if the assumptions or methods used are ideologically tainted, dishonest, or flawed. For instance, weighting by “recalled vote” or education level has been criticized for possibly skewing results. The 2020 election highlighted that national polling errors were among the highest in 40 years despite these adjustments.

So, it goes without saying (although it must be said) that the “science” of polling is inaccurate, to say the very least. Yet, the mainstream media complex and the political opportunists of all political parties routinely cite polling results as intently sincere and an accurate harbinger of the coming