It can be hard to remember all the news since the last New York Times/Siena University poll in April, so here’s a quick list:
President Trump paused many tariffs and enacted others; Elon Musk left his Department of Government Efficiency; Kilmar Abrego Garcia was brought back to the United States; Republicans passed their enormous tax-and-spending bill; National Guard troops were deployed to Los Angeles; the United States bombed Iran; there was an uproar over releasing the Jeffrey Epstein files; the federal government took over Washington, D.C.; Charlie Kirk was assassinated.
Yet despite it all, “unchanged” is probably the best description of the findings from today’s Times/Siena poll.
Mr. Trump’s approval rating is at 43 percent, about the same as the 42 percent who approved in April. His disapproval rating is unchanged at 54 percent.
Similarly, Democrats lead by two percentage points in the race for Congress. That’s about the same as their three-point lead in April.
You can tell the same story about the economy, immigration, trade, Russia and so on. Voters still think Mr. Trump is going “too far,” and they mostly disapprove of his handling of the most important issues, but his political standing hasn’t gotten much worse over the last few months, either.
My colleagues have the story here, along with a separate article on a reversal of support for Israel, with slightly more Americans now saying they sympathize more with Palestinians than Israel.
Why aren’t Democrats doing better?
We didn’t ask how voters viewed the Democratic Party in this poll, but our questions about immigration nonetheless help illustrate why “disapproval” of Mr. Trump does not neatly translate into support for Democrats.
Overall, Mr. Trump’s approval rating on immigration isn’t great, with 46 percent approving and 52 percent disapproving. More specifically, a slim majority, 51 percent, say Mr. Trump is going “too far” on immigration enforcement. Only 44 percent think the deportation process has been fair.
It might look like a great opportunity for Democrats, but there’s a catch:
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54 percent say they “support” deporting illegal immigrants, compared with 44 percent who “oppose.”
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51 percent say that the government is mostly deporting people who “should” be deported, compared with 42 percent who say the government is mostly deporting people who “should not” be deported.
In other words, a majority of voters support Mr. Trump’s core objective, and they think the administration is mostly deporting the right kind of people. To the extent that a majority disapproves, it seems to be mostly about the excesses of the execution of the policy. We didn’t ask specific questions about the Abrego Garcia case, the deportation of people to places that aren’t their home countries, racial profiling, the defying of court rulings, and so on, but voters might object to these sorts of actions even if they support deportation in general.
For someone who was in the majority on each of these questions, you can see why that person might not be inclined to support Democrats. Would you rather have a president who goes too far in pursuit of a goal you support, or would you rather have a president who isn’t as committed to the goal you support or might even oppose it altogether?
Text experiments, continued
In a continuation of a trial that began with our recent New York City poll, we experimented with using text messages in this survey, the first time we’ve done so in a national Times/Siena poll.
We again fielded the poll as two separate surveys. One half of the poll was a usual Times/Siena telephone poll. The other half of respondents received a text message invitation to take an online survey, and those who didn’t take the online poll were then called back by phone.
In the earlier poll, the two approaches yielded fundamentally similar results. This time, the results were very different.
In short, the text sample was much more Democratic than the phone sample. As initially weighted, the text half of the sample was D+4 by party identification. That was much more Democratic than the R+4 phone half of the poll, and it was also more Democratic than any Times/Siena poll in years.
Similarly, the respondents in the text half of the poll were much more likely to report having supported Kamala Harris last year — a kind of measure often called “recalled vote.” As originally weighted, the respondents in the text half of the sample said they backed her by six percentage points in 2024, compared with Mr. Trump’s 1.5-point victory in the popular vote and compared with an even result in the phone poll. As a consequence, we weighted the text sample’s recalled 2024 vote to match the results of the 2024 election. After weighting, the results of the text poll were very similar to the phone survey.
Now, some of you may remember that I’m generally pretty skeptical of looking at how voters “recall” voting in the last election. Historically, weighting on “recall” vote doesn’t work well. But this is an unusual case. The seven-point difference between the recalled vote result and the actual 2020 election result in the text sample would have been larger than in any prior Times/Siena national poll (and possibly any Times/Siena poll). And historically, “recalled vote” tends to overstate the winner, making the overestimation of Ms. Harris even less tolerable. The parallel phone-only sample adds additional confidence that this was simply because the text sample had too many Democratic-leaning voters.
Most of all, the text sample is an experimental design. The point is to evaluate whether the text-plus approach yields a representative sample; unlike the phone poll, it’s not fielded under the assumption that it’s representative without recall vote. Many kinds of polls — perhaps even most polls nowadays — are not. Obviously, this isn’t what we were hoping to find, but this is why we test new approaches. It taught us something important about the best way to design our surveys, even if it is not what we wanted to learn.
Nate Cohn is The Times’s chief political analyst. He covers elections, public opinion, demographics and polling.
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