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Toplines: June 2024 Times/Siena Poll of Registered Voters Nationwide

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Toplines: June 2024 Times/Siena Poll of Registered Voters Nationwide

How This Poll Was Conducted

Here are the key things to know about this Times/Siena poll:

• We spoke with 1,226 registered voters from June 20 to 25, 2024.

• Our polls are conducted by telephone, using live interviewers, in both English and Spanish. More than 90 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, we placed nearly 150,000 calls to more than 100,000 voters.

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• 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 registered voters is plus or minus three 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 we conduct our polls, you can see answers to frequently asked questions and submit your own questions here.

Full Methodology

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The New York Times/Siena College poll of 1,226 registered voters nationwide, including 991 who completed the full survey, was conducted in English and Spanish on cellular and landline telephones from June 20 to 25, 2024. The margin of sampling error is plus or minus three percentage points for registered voters and plus or minus 3.2 percentage points for the likely electorate. Among those who completed the full survey, the margin of sampling error is plus or minus 3.5 percentage points for registered voters and plus or minus 3.6 percentage points for the likely electorate.

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.

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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, the Public Opinion Research Laboratory at the University of North Florida, the Institute of Policy and Opinion Research at Roanoke College, 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, 91 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, 13 percent of interviews among self-reported Hispanics were conducted in Spanish, including 17 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, race or presidential election ballot test questions.

Weighting — registered voters

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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, or 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)

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• 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)

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• 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)

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• 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.

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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 intention. The final probability that a registrant would vote in the 2024 election was four-fifths 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 1.21 for registered voters and 1.33 for the likely electorate. The design effect for the sample of completed interviews is 1.24 for registered voters and 1.33 for the likely electorate.

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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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Tornadoes hit Illinois, Indiana and Texas as severe storms sweep US

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Tornadoes hit Illinois, Indiana and Texas as severe storms sweep US

A series of tornadoes hit parts of Texas, Illinois, and Indiana late Tuesday and overnight, as forecasters warn that the threat of severe weather, including flooding, will continue on Wednesday for tens of millions of people from Texas to Michigan.

At least four tornado touchdowns were reported in eastern Illinois, the National Weather Service (NWS) said, leaving a trail of damage stretching into Indiana, where at least two people were killed.

Video of a separate tornado in Taylor county, central Texas, on Tuesday was posted to weather.com. Officials there reported 60mph wind gusts and “baseball-sized” hail.

A search continued on Wednesday for possible victims of a supercell of storms that followed a path from Kankakee county, Illinois, into Indiana late on Tuesday. Rob Churchill, chief of the Lake Township fire department in Indiana, said in a video on Facebook that the small town of Lake Village had taken “a direct hit”.

“We have multiple homes destroyed, please stay away from the area,” he said.

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Fire department officials said at an early morning Wednesday press conference that there were two fatalities, WTHR News, an NBC affiliate, reported. Details were not immediately available.

Shannon Cothran, sheriff of Newton county in Indiana, said in a separate Facebook video that the immediate threat of dangerous weather had passed, but first responders were faced with challenging circumstances as they dealt with the storm’s aftermath.

“[There’s] a lot of damage. Please do not come here. Do not try to help right now. We’ve got a lot of first responders out here doing their job, just give us some room,” he said.

The tornadoes in parts of Illinois and Indiana downed trees and power lines in an area south of Chicago, and overwhelmed 911 operators, officials said. The Kankakee county sheriff’s office said one tornado touched down near the Kankakee fairgrounds before moving north-east into Aroma park, where it caused extensive damage.

JB Pritzker, the Democratic Illinois governor, said in a post on X early Wednesday that he was briefed on the storm and tornado damage and that the state’s emergency management agency was in contact with local officials.

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“Keeping in our thoughts all Illinoisans impacted by the severe weather – we’ll be here to help them recover,” he said.

Severe storms dumping rain and hail in parts of the midwest were threatening to bring intense tornadoes, damaging winds and very large hail from the southern plains to the southern Great Lakes, according to the NWS. States from Oklahoma to Michigan were under tornado watches.

Andrew Lyons, a meteorologist with the weather service’s storm prediction center, told the Associated Press that the exact number of tornado touchdowns would not be known until after officials conducted damage assessments.

He described it as a fairly typical early spring strong storm system that was expected to continue to move east and northeast towards the Atlantic coast on Wednesday, likely bringing more severe weather, he said.

Brandon Buckingham, an AccuWeather meteorologist, said at least 10 tornadoes were spotted in Illinois, Indiana and Texas.

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“There were nearly 200 filtered reports of severe weather spanning more than 2,500 miles from Texas to Michigan,” he said in a post on the weather service’s website.

The forecaster said the chain of storms would peak midweek and “could become the most widespread and impactful severe weather outbreak so far this year”.

The severe weather could reach Washington DC by Wednesday afternoon, CBS News reported, bringing new threats of damaging winds and tornadoes. A line of storms was forecast to sweep east and move into Ohio and Tennessee, including the cities of Cincinnati, Memphis and Nashville, it said.

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Wheelchair curler Steve Emt’s path from drunk driver to three-time Paralympian

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Wheelchair curler Steve Emt’s path from drunk driver to three-time Paralympian

American Steve Emt competes in Sunday’s mixed doubles match against Italy, which the U.S. won.

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Anyone watching the Winter Paralympics has probably taken note of Steve Emt, who — along with Laura Dwyer — is representing Team USA in the Games’ first-ever mixed doubles event.

Their performance is one thing: The pair notched three dramatic, back-to-back wins in the round-robin tournament to reach the semifinals, marking the first time the U.S. has qualified for a medal round in wheelchair curling since the 2010 Paralympics.

After losing to Korea in the semifinals, Emt and Dwyer will face Latvia in the bronze medal match on Tuesday, in the hopes of winning the U.S. its first Paralympic medal in wheelchair curling.

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But it’s their teamwork and attitude on ice that really set them apart. Emt, in particular, has charmed the internet, with his booming baritone delivering a steady stream of encouragement to his doubles partner and demands to the granite stones they’re sliding (“curl!” “sit!”).

“I have three older siblings. I was always on the basketball court getting beat up by them, so I had to assert myself on the court, around the kitchen table, everything,” he said when asked about his deep voice this week.

Steve Emt and Laura Dwyer celebrate during a match this week.

Steve Emt and Laura Dwyer have made sure to celebrate their wins, of which there have been many throughout this wheelchair curling mixed doubles round-robin tournament.

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While Emt, 56, is competing in a new event, he’s no stranger to the sport: The 10-time national champion and three-time Paralympian is the most decorated Paralympic curler in U.S. history.

But he didn’t know what curling was until he got recruited off the street just over a decade ago.

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Emt, who is 6 feet, 5 inches tall, was enjoying a day in Cape Cod, Mass., in 2013 when a stranger with slicked-back hair approached and asked if he was local. Emt replied that he lived in Connecticut and suspiciously asked why.

“He said, ‘Well, I train with the Paralympic rowing team here in the Cape. I saw you pushing up the hill back there. With your build, I could make you an Olympian in a year,’” Emt recalled, referring to his wheelchair. “And I heard ‘Olympics,’ I’m like: Let’s go. What the hell is curling?”

After their conversation, Emt drove home and did some research, confirming that curling was not related to weightlifting, as he originally suspected.

“I went back two weeks later and I threw my first stone, and it just bit me,” he said.

Before long, Emt was making the two-and-a-half-hour drive to Massachusetts to spend the weekend training with that stranger-turned-coach, Tony Colacchio. He made the U.S. wheelchair curling team in 2014 and competed at his first world championship in 2015. Emt made his Paralympic debut in Pyeongchang in 2018, five years after that fateful encounter.

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Emt, speaking to reporters in October, said the sport of curling has changed him as a person, mellowing him out. But the existence of the sport as a competitive outlet for athletes with disabilities changed his life.

Emt had been an all-star high school athlete, an Army West Point cadet and a UConn basketball walk-on before a drunk driving incident paralyzed him from the waist down at 25 years old.

“I’m a jock … I need to compete, and I didn’t have anything going on in my life,” Emt said. “Seventeen years after my crash, I had a hole, and then [Colacchio] came along and stalked me into the sport.”

By that point, Emt had spent years working as a middle school math teacher, a high school basketball coach and a motivational speaker. The latter has been his full-time job for almost a decade, taking him to over 100 schools across the country each year. He tells those teenagers about the chance Colacchio took on him, encouraging them to “be a Tony.”

“Go sit with that kid at lunch that’s sitting alone … smile [at] somebody in a hallway, get your heads out of your phones, get your heads out of the sand,” he continued. “We’re all going through something … and a simple ‘hello’ or ‘good morning,’ it could change their day. It could change somebody’s life.”

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Why Emt now shares his story 

This is the third Paralympics for Emt, who is already eyeing Salt Lake City 20

This is the third Paralympics for Emt, who is already eyeing Salt Lake City 2034.

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Emt wasn’t always so willing to open up. For the first half a year after his 1995 crash, he told everyone a deer had run in front of his car rather than admit he had gotten behind the wheel drunk.

“I was lying to myself, I was lying to everybody around me,” he said. “I didn’t want kids to look at me in my hometown, in the state, and everyone around the country, as a drunk driver. I wanted them to look at me as a stud athlete and a great person.”

Emt had been a “stud athlete”: His talents in high school basketball, soccer and baseball made him a star in his hometown of Hebron, Conn., and earned him a spot on the basketball team at West Point.

But he dropped out two years later, after his father’s sudden death from a heart attack. He went home to Connecticut and eventually enrolled at UConn, where he walked on to its storied basketball team, joining future NBA greats like Donyell Marshall. Emt says, with a chuckle, that he had 38.7 seconds of playing time in his two years.

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Emt was wearing his Big East championship jacket the night of his 1995 accident, which he says left him for dead on the side of the highway. When he woke up from a coma a few days later, he learned he would never walk again.

And he didn’t want to tell people why, until a newspaper reporter approached him six months later wanting to tell his story — and encouraged him to be honest. He said the opportunity to “come clean” helped him accept what he’d done and forgive himself.

“That’s my label: Yeah I’m a curler, yeah I’m a speaker, yeah I’m a drunk driver,” he said. “I’m in a wheelchair because of a drunk driving crash, and I want you to know it and I want you to learn from me.”

Emt first got into motivational speaking about eight months after his accident, and has been doing it ever since. He calls it his therapy.

He says that and curling — which is about shaking hands with competitors instead of smack-talking them — has helped him slow down and appreciate the little things. Relocating to Wisconsin and the chiller pace of Midwest life has also helped. And he says he cherishes the platform that curling has given him.

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“I want people to know: ‘Hey, when you’re ready to talk, I’m here for you.’ This is what I do, from my speaking to my curling, whatever it is, there are so many opportunities to be successful again,” he said. “When you wake up and you’re told you’re never going to walk again, it’s like, what do I do now? … And I just want people to know that there are so many avenues out there, so many things to do.”

Emt, the oldest Paralympian on Team USA, originally aimed to make it to three Games. But he’s now eyeing even more, as he’d like to compete on home turf in Salt Lake City in 2034 (two Games away).

“I’m going to be like 90 years old competing at the Paralympics,” he laughed.

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Map: 2.3-Magnitude Earthquake Reported North of New York City

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Map: 2.3-Magnitude Earthquake Reported North of New York City

Note: Map shows the area with a shake intensity of 3 or greater, which U.S.G.S. defines as “weak,” though the earthquake may be felt outside the areas shown.  All times on the map are Eastern. The New York Times

A minor, 2.3-magnitude earthquake struck about 12 miles north of New York City on Tuesday, according to the United States Geological Survey.

The temblor happened at 10:17 a.m. Eastern in Sleepy Hollow, N.Y., data from the agency shows.

The Westchester County emergency services department said in a statement that it had not received any reports of damage.

As seismologists review available data, they may revise the earthquake’s reported magnitude. Additional information collected about the earthquake may also prompt U.S.G.S. scientists to update the shake-severity map.

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Source: United States Geological Survey | Notes: Shaking categories are based on the Modified Mercalli Intensity scale. When aftershock data is available, the corresponding maps and charts include earthquakes within 100 miles and seven days of the initial quake. All times above are Eastern. Shake data is as of Tuesday, March 10 at 10:30 a.m. Eastern. Aftershocks data is as of Tuesday, March 10 at 2:18 p.m. Eastern.

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