Nearly one month later, the Democratic Party and the pundits and other politics experts are continuing to study the wreckage of the 2024 election. They are asking themselves how this could have possibly happened. How could we have been so wrong in assessing the country’s mood? They need to quickly come up with the correct answer because they are running out of time. Trump has promised a campaign of revenge and retribution against his perceived enemies. He is not kidding.

The public opinion polls suggested that the election between Kamala Harris and Donald Trump would be very close — and more specifically that Harris would be much more competitive, if not the victor. Of course, this did not happen. The fabled Democratic blue wall was easily smashed by Trump and his MAGA movement. Trump also made in-roads as he won support from key parts of the Democratic Party’s base across the country. This hinted at a larger trend as Kamala Harris and the Democrats experienced a collapse of support among a wide range of voters. The result: Trump would increase his support by more than two million votes as compared to the 2020 election. By comparison, Harris received seven million fewer votes than President Biden did in 2020.

In a recent essay at The Conversation, historian and media critic W. Joseph Campbell offers this assessment:

So it went for pollsters in the 2024 presidential election. Their collective performance, while not stellar, was improved from that of four years earlier. Overall, polls signaled a close outcome in the race between former President Donald Trump and Vice President Kamala Harris.

That is what the election produced: a modest win for Trump….

Campbell continues:

A significant question facing pollsters this year – their great known unknown – was whether modifications made to sampling techniques would allow them to avoid underestimating Trump’s support, as they had in 2016 and 2020.

Misjudging Trump’s backing is a nagging problem for pollsters. The results of the 2024 election indicate that the shortcoming persists. By margins ranging from 0.9 points to 2.7 points, polls overall understated Trump’s support in the seven swing states, for example.

Some polls misjudged Trump’s backing by even greater margins. CNN, for example, underestimated Trump’s vote by 4.3 points in North Carolina, by more than 6 points in Michigan and Wisconsin as well as Arizona.

Results that misfire in the same direction suggest that adjustments to sampling methodologies were inadequate or ineffective for pollsters in seeking to reach Trump backers of all stripes.

At the Columbia Journalism Review, Meghnad Bose makes this intervention about how the news media chooses to present the polls in the context of other information:

Now that the smoke has cleared from Election Day, it appears that the polls and statistical models mostly got the story right. But if it doesn’t quite feel that way — the race seemed to be a nail-biter, then Donald Trump won decisively — that may have been a result of how the numbers were presented, and the conclusions that journalists (and news consumers) drew from the data. “If we want to minimise the risk of nasty shocks,” John Burn-Murdoch, a chief data reporter for the Financial Times, wrote last week, “and we want pollsters to get a fair hearing when the results are in, both sides need to accept that polls deal in fuzzy ranges, not hard numbers.”

That tension — between editorial desire for a straightforward narrative and blurry reality — is made more complicated by herding, when polling firms toss results that don’t align with a dominant plotline.

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Here is one of the main challenges of public opinion polls, even high-quality........

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