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Cross-Tabs: September 2024 Times/Siena Poll of the Likely Electorate
How This Poll Was Conducted
Here are the key things to know about this Times/Siena poll:
• Interviewers spoke with 1,695 registered voters across the country from Sept. 3 to 6, 2024.
• Times/Siena polls are conducted by telephone, using live interviewers, in both English and Spanish. About 96 percent of respondents were contacted on a cellphone for this poll.
• Voters are selected for the survey from a list of registered voters. The list contains information on the demographic characteristics of every registered voter, allowing us to make sure we reach the right number of voters of each party, race and region. For this poll, interviewers placed nearly 194,000 calls to nearly 104,000 voters.
• To further ensure that the results reflect the entire voting population, not just those willing to take a poll, we give more weight to respondents from demographic groups that are underrepresented among survey respondents, like people without a college degree. You can see more information about the characteristics of our respondents and the weighted sample at the bottom of the page, under “Composition of the Sample.”
• The poll’s margin of sampling error among likely voters is plus or minus 2.8 percentage points. In theory, this means that the results should reflect the views of the overall population most of the time, though many other challenges create additional sources of error. When computing the difference between two values — such as a candidate’s lead in a race — the margin of error is twice as large.
If you want to read more about how and why The Times/Siena Poll is conducted, you can see answers to frequently asked questions and submit your own questions here.
Full Methodology
The New York Times/Siena College poll of 1,695 registered voters nationwide, including 1,374 who completed the full survey, was conducted in English and Spanish on cellular and landline telephones from Sept. 3 to 6, 2024. The margin of sampling error is plus or minus 2.8 percentage points for the likely electorate and plus or minus 2.6 percentage points for registered voters. Among those who completed the full survey, the margin of sampling error is plus or minus 3.2 percentage points for the likely electorate and plus or minus 3.0 percentage points for registered voters.
Sample
The survey is a response rate-adjusted stratified sample of registered voters on the L2 voter file. The sample was selected by The New York Times in multiple steps to account for differential telephone coverage, nonresponse and significant variation in the productivity of telephone numbers by state.
First, records were selected by state. To adjust for noncoverage bias, the L2 voter file was stratified by statehouse district, party, race, gender, marital status, household size, turnout history, age and home ownership. The proportion of registrants with a telephone number and the mean expected response rate were calculated for each stratum. The mean expected response rate was based on a model of unit nonresponse in prior Times/Siena surveys. The initial selection weight was equal to the reciprocal of a stratum’s mean telephone coverage and modeled response rate. For respondents with multiple telephone numbers on the L2 file, the number with the highest modeled response rate was selected.
Second, state records were selected for the national sample. The number of records selected by state was based on a model of unit nonresponse in prior Times/Siena national surveys as a function of state, telephone number quality and other demographic and political characteristics. The state’s share of records was equal to the reciprocal of the mean response rate of the state’s records, divided by the national sum of the weights.
Fielding
The sample was stratified according to political party, race and region and fielded by the Siena College Research Institute, with additional field work by ReconMR and the Center for Public Opinion and Policy Research at Winthrop University in South Carolina. Interviewers asked for the person named on the voter file and ended the interview if the intended respondent was not available. Overall, 96 percent of respondents were reached on a cellular telephone.
The instrument was translated into Spanish by ReconMR. Bilingual interviewers began the interview in English and were instructed to follow the lead of the respondent in determining whether to conduct the survey in English or Spanish. Monolingual Spanish-speaking respondents who were initially contacted by English-speaking interviewers were recontacted by Spanish-speaking interviewers. Overall, 15 percent of interviews among self-reported Hispanics were conducted in Spanish, including 23 percent of weighted interviews.
An interview was determined to be complete for the purposes of inclusion in the ballot test question if the respondent did not drop out of the survey by the end of the two self-reported variables used in weighting — age and education — and answered at least one of the age, education or presidential election ballot test questions.
Weighting — registered voters
The survey was weighted by The Times using the R survey package in multiple steps.
First, the sample was adjusted for unequal probability of selection by stratum.
Second, the sample was weighted to match voter file-based parameters for the characteristics of registered voters.
The following targets were used:
• Party (party registration if available in the state, else classification based on participation in partisan primaries if available in the state, else classification based on a model of vote choice in prior Times/Siena polls) by whether the respondent’s race is modeled as white or nonwhite (L2 model)
• Age (Self-reported age, or voter file age if the respondent refuses) by gender (L2)
• Race or ethnicity (L2 model)
• Education (four categories of self-reported education level, weighted to match NYT-based targets derived from Times/Siena polls, census data and the L2 voter file)
• White/non-white race by college or non-college educational attainment (L2 model of race weighted to match NYT-based targets for self-reported education)
• Marital status (L2 model)
• Home ownership (L2 model)
• National region (NYT classifications by state)
• Turnout history (NYT classifications based on L2 data)
• Method of voting in the 2020 elections (NYT classifications based on L2 data)
• Metropolitan status (2013 NCHS Urban-Rural Classification Scheme for Counties)
• Census tract educational attainment
Finally, the sample of respondents who completed all questions in the survey was weighted identically, as well as to the result for the general election horse race question (including leaners) on the full sample.
Weighting — likely electorate
The survey was weighted by The Times using the R survey package in multiple steps.
First, the samples were adjusted for unequal probability of selection by stratum.
Second, the first-stage weight was adjusted to account for the probability that a registrant would vote in the 2024 election, based on a model of turnout in the 2020 election.
Third, the sample was weighted to match targets for the composition of the likely electorate. The targets for the composition of the likely electorate were derived by aggregating the individual-level turnout estimates described in the previous step for registrants on the L2 voter file. The categories used in weighting were the same as those previously mentioned for registered voters.
Fourth, the initial likely electorate weight was adjusted to incorporate self-reported intention to vote. Four-fifths of the final probability that a registrant would vote in the 2024 election was based on their ex ante modeled turnout score and one-fifth based on their self-reported intentions, based on prior Times/Siena polls, including a penalty to account for the tendency of survey respondents to turn out at higher rates than nonrespondents. The final likely electorate weight was equal to the modeled electorate rake weight, multiplied by the final turnout probability and divided by the ex ante modeled turnout probability.
Finally, the sample of respondents who completed all questions in the survey was weighted identically, as well as to the result for the general election horse race question (including leaners) on the full sample.
The margin of error accounts for the survey’s design effect, a measure of the loss of statistical power due to survey design and weighting. The design effect for the full sample is 1.38 for the likely electorate and 1.21 for registered voters. The design effect for the sample of completed interviews is 1.43 for the likely electorate and 1.26 for registered voters.
Historically, The Times/Siena Poll’s error at the 95th percentile has been plus or minus 5.1 percentage points in surveys taken over the final three weeks before an election. Real-world error includes sources of error beyond sampling error, such as nonresponse bias, coverage error, late shifts among undecided voters and error in estimating the composition of the electorate.
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Waymo called the cops on teen riders, raising privacy concerns
A Waymo robotaxi drives in San Francisco’s North Beach neighborhood this week.
Heather Diehl/Getty Images
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Police in San Mateo, Calif., posted Monday on social media that they had apprehended a pair of teenagers from a Waymo driverless robotaxi after the company alerted authorities to suspected criminal activity. It’s the latest incident involving video surveillance of passengers and others by autonomous vehicles — raising questions about the limits of privacy in such vehicles.

The Facebook post by the San Mateo County Police said: “Parents do you know where your teens are? @waymo does!”
The 15-year-olds were allegedly drinking alcohol and shooting toy guns from the car, according to the police. They said Waymo’s systems detected behavior that then triggered a safety response, after which the company disabled the vehicle and contacted police.
Waymo’s cars, equipped with an array of cameras, microphones and other sensors to monitor passengers and other nearby vehicles, are becoming more common in cities across the United States. Experts say the detention of the two teens in San Mateo highlights a potential — but not inevitable — trade-off between privacy and convenience. It also questions the extent to which companies similar to Waymo are required to hand over private data, including audio and video of passengers, in situations where a crime is suspected.
NPR reached out to Waymo, which is owned by Alphabet, the parent company of Google, for comment on the details of the San Mateo incident and how the company responded, but did not hear back. But on its website, the company says that as many as 29 cameras in its autonomous cars provide an all-around view and “are designed with high dynamic range and thermal stability, to see in both daylight and low-light conditions, and tackle more complex environments.”
“There already exist laws that govern duty to report or even duty to protect” for carriers such as Waymo, according to Alessandro Acquisti, a professor of information technology at the MIT Sloan School of Management. “The privacy problems arise when and if driverless carrier companies used such laws or ethical obligations as a pretext for blanket, indiscriminate accumulation of identifiable data for unspecified future purposes.”
That includes not just monitoring people inside the cars, but outside too. Take, for example, a hit-and-run investigation last year in Los Angeles. Media reported that the police inquiry was aided by video captured by a Waymo taxi that had a clear view of the crime. Critics suggested at the time that authorities were using the company’s vehicles as a mobile surveillance platform. And during 2025 protests in Los Angeles against Immigration and Customs Enforcement crackdowns, demonstrators vandalized Waymos, apparently angry that video recorded by the vehicles could be used by police, although there is no evidence that happened.
In a transparency report, Google says it received nearly 290,000 requests from governments worldwide in the first six months of 2025 for disclosure of user information across all its platforms, including Waymo. The company says that in more than 80% of the requests in those six months, some information was disclosed. “Google carefully reviews each request to make sure it satisfies applicable laws. If a request asks for too much information, we try to narrow it, and in some cases we object to producing any information at all,” the company says.
In an email to NPR, San Mateo Police Department spokesperson Jeanine Luna said that detaining the teens in the Waymo on Monday was “wholly appropriate” under the circumstances. “We received the call of a ‘firearm’ being shot from a moving vehicle,” she said. “Furthermore, the occupants were described as being possibly ‘intoxicated.’” she said.
“Being that the vehicle was disabled (the occupants had every right to exit the vehicle before police arrival, but they did not), a high-risk traffic stop was conducted to ensure the safety of all involved,” Luna added. “They were not arrested and were released to their parents, however, potential charges are still pending dependent on what the video from inside the vehicle shows.”
Autonomous taxis represent an ethical gray area
Robotaxis began to roll out across the U.S. in December 2018, when Waymo launched in Phoenix. These services have been used for less than a decade — so the norms surrounding them aren’t settled, experts agree.
The Facebook post may make Waymo passengers wonder what triggers a police intervention, says Irina Raicu, director of the Internet Ethics program at Santa Clara University. She has used Waymo’s driverless taxis and says ethically, the privacy issues surrounding them sit in a gray area. “There’s something about being in a car without another person that makes you think it’s private.”
“With all these recording devices, we don’t see them, [and] they’re not these obvious things being stuck in our faces,” Raicu adds.
That brings up a key issue: informed consent, Acquisti says.
“It is not clear the extent to which passengers … are reminded that when they step into the car, that they are being monitored, and most likely they are not told in its entirety how the data will be used,” he says.
Bruce Schneier, a cybersecurity and privacy expert and professor at the Munk School at the University of Toronto, believes that Waymo does have a compelling interest in protecting its vehicles. He compares monitoring a robotaxi via cameras to a human taxi driver keeping an eye on passengers in the rearview mirror.
“Maybe the driverless car comes back … and it has all of its cushions slashed, and it’s like, ‘Who the hell did that? Let’s go and look at the tape,’” Schneier suggests. “You can’t have sex in the back of a taxi, right? Someone would say, ‘Stop it.’”
He concludes that some supervision makes sense. In an Uber rideshare, he notes, “most of the time there’s a camera recording the back seat.” (Uber says on its website that it allows drivers to install such cameras for the purpose of “fulfilling transportation services.”)

Waymo robotaxis, while a fairly common sight in the San Francisco Bay Area, are still a novelty in much of the country. And many people are hesitant to ride in one, according to a Pew Research Center poll published this month. The survey found that only 5% of Americans had ever ridden in a driverless car. Meanwhile, 71% of those polled said they would feel uncomfortable in one, with only 7% saying they would be “extremely or very comfortable” riding in one.
For that reason, experts who spoke with NPR said they were optimistic that it’s not too late to shift gears on privacy norms and policies surrounding these vehicles.
Acquisti doesn’t see why privacy measures can’t be built into driverless vehicles.
“I would immediately challenge the notion that people have to be monitored,” he says, noting that privacy-preserving technologies exist and can be installed.
“Driverless cars are coming, but they don’t have to come in this particular incarnation,” Raicu says. “They’re still being designed and redesigned. It’s early days.”
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Trump fires last members of election commission, inciting fears of midterm ‘chaos’
Donald Trump has terminated the remaining members of the independent, federal commission that assists election administration officials nationwide just a few months before the midterm elections, multiple outlets reported Thursday.
The remaining three commissioners of the four-member bipartisan commission were forced out on Thursday in different ways. The one Republican appointee resigned and the other two, Democratic appointees were notified of their terminations via email from the White House presidential personnel office.
“On behalf of President Donald J Trump, I am writing to inform you that your position as Commissioner of the Election Assistance Commission is terminated, effective immediately. Thank you for your service,” the email, seen by Reuters, said.
The White House did not immediately respond to a request for comment.
The Election Assistance Commission serves as a “national clearinghouse of information on election administration”, accredits testing laboratories and certifies voting systems, and maintains the national mail-voter registration form developed by the National Voter Registration Act of 1993, according to the commission’s website. The terminations follow Trump and top administration officials’ advocacy to change vote-by-mail requirements and investigations into the 2020 election outcome, which Trump lost to Democrat Joe Biden.
“It is irresponsible and dangerous that this Administration remains dead set on causing chaos for our election officials across this country,” Arizona secretary of state Adrian Fontes said in a Thursday statement. “This move undermines the integrity of nonpartisan election administration.”
The 2002 law that established the commission, the Help America Vote Act, states the president can appoint replacements to the commission.
It is unclear how Trump will move ahead with the commission.
Reuters contributed reporting
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Former Olympian pleads not guilty in reflecting pool vandalism charges
Former U.S. Olympian David Hearn (left) walks with his attorney Norman Eisen to speak to reporters and protesters gathered after his arraignment at the Superior Court of the District of Columbia in Washington, D.C. on Thursday.
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Former U.S. Olympic canoeist David Hearn pleaded not guilty to damaging the Lincoln Memorial Reflecting Pool in D.C. Superior Court Thursday morning.
Federal prosecutors charged Hearn with a single count of destruction of property causing more than $1,000 in damage to the pool.

Hearn has previously claimed, which his attorneys repeated during a short press conference outside the court, that he simply touched the water in the pool out of curiosity.
The Trump administration had just completed a $14 million renovation of the pool.
But shortly after the work finished, peeling paint and algae gathered in the water. The remodel has been largely criticized as a massive failure and waste of taxpayer dollars.

Superior Court Judge Carmen McLean released Hearn on his own recognizance. His next hearing is scheduled for Aug. 5.
Norm Eisen, one of Hearn’s attorneys, spoke to reporters outside of court following the hearing. He said the administration is using Hearn as a “scapegoat … for their own failures.”
“It is not a crime to touch the reflecting pool, to touch water in the United States of America,” he said.
Prosecutors say there is a host of evidence against Hearn.
This is a developing story.
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