More from the article ...
... There is reason for concern. In addition to high-profile misses " the most prominent among them, the 2016 presidential contest that elected Trump " recent election cycles have witnessed cratering survey response rates, flawed weighting and turnout assumptions, and a rise in bad-faith actors, not to mention the challenge of vanishing landline phones.
This year, a handful of episodes have further undermined confidence. Polls predicted a slam-dunk victory for Abdul El-Sayed in Michigan's Democratic Senate primary -- he won by 1 percentage point. Francesca Hong, the democratic socialist running in Wisconsin's Democratic primary for governor, held a double-digit lead in preelection surveys -- she narrowly lost. And a poll in the Los Angeles mayoral race -- which spread widely after one of the candidates, Mayor Karen Bass, touted it on social media -- turned out to be entirely bogus. The Los Angeles Times later reported that the individual behind the sham poll said it was part of a "short-term social experiment" to examine how polling numbers could "spread through the political information ecosystem without independent verification."
The polling misfires, however, don't reflect the changes in the industry. There are new methods of reaching people, and new ways to account for the most elusive voters.
Those corrections have seemingly paid off; you may not realize it, but the polls largely nailed the results of the past two midterms.
Still, polls aren't meant to be predictive. They represent a snapshot in time, offering insight into public sentiment and voters' most pressing concerns.
"Certainly, given the polling misses in 2016 and, to some extent, 2020, there's an obvious fear factor," says Charles Franklin, director of the Marquette Law School Poll. "We've done a lot over this past decade to try to improve the control we have over those kinds of errors, but ultimately we can't force people to do polls, and so this remains always a background fear factor." ...
[emphasis mine]
