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.

The mother of the 14-year-old who has been charged with murder over the fatal shooting of four people at his Georgia high school called the school before the killings, warning staff of an “extreme emergency” involving her son, a relative said.

Annie Brown told the Washington Post that her sister, Colt Gray’s mother, texted her saying she spoke with a school counselor and urged them to “immediately” find her son to check on him.

Brown provided screen shots of the text exchange to the newspaper, which also reported that a call log from the family’s shared phone plan showed a call was made to the school about 30 minutes before gunfire is believed to have erupted.

Brown confirmed the reporting to The Associated Press on Saturday in text messages but declined to provide further comment.

Colt Gray, 14, has been charged with murder over the killing of two students and two teachers at Apalachee High School in Barrow County, outside Atlanta, on Wednesday. His father, Colin Gray, is accused of second-degree murder for providing his son with a semiautomatic AR 15-style rifle.

Their attorneys declined to immediately seek bail during their first court appearance on Friday.

Investigators previously interviewed the suspects

The Georgia teenager had struggled with his parents’ separation and taunting by classmates, his father told a sheriff’s investigator last year when asked whether his son posted an online threat.

“I don’t know anything about him saying (expletive) like that,” Gray told Jackson County sheriff’s investigator Daniel Miller, according to a transcript of their interview obtained by the AP. “I’m going to be mad as hell if he did, and then all the guns will go away.”

Jackson County authorities ended their inquiry into Colt Gray a year ago, concluding that there wasn’t clear evidence to link him to a threat posted on Discord, a social media site popular with video gamers. The records from that investigation provide at least a narrow glimpse into a boy who struggled with his parents’ breakup and at the middle school he attended at the time, where his father said others frequently taunted him.

Father says his son was bullied at school

“He gets flustered and under pressure. He doesn’t really think straight,” Colin Gray told the investigator on May 21, 2023, recalling a discussion he’d had with the boy’s principal.

Middle school had also been rough for Colt Gray. He had just finished the seventh grade when Miller interviewed the father and son. Colin Gray said the boy had just a few friends and frequently got picked on. Some students “just ridiculed him day after day after day.”

“I don’t want him to fight anybody, but they just keep like pinching him and touching him,” Gray said. “Words are one thing, but you start touching him and that’s a whole different deal. And it’s just escalated to the point where like his finals were last week and that was the last thing on his mind.”

Shooting guns and hunting, he said, were frequent pastimes for father and son. Gray said he was encouraging the boy to be more active outdoors and spend less time playing video games on his Xbox. When Colt Gray killed a deer months earlier, his father swelled with pride. He showed the investigator a photo on his cellphone, saying: “You see him with blood on his cheeks from shooting his first deer.”

“It was just the greatest day ever,” Colin Gray said.

There’s no mention in the investigator’s report and interview transcript of either Gray owning an assault-style rifle. Asked if his son had access to firearms, the father said yes. But he said the guns weren’t kept loaded and insisted he had emphasized safety when teaching the boy to shoot.

“He knows the seriousness of weapons and what they can do,” Gray said, “and how to use them and not use them.”

Family evicted in 2022

An eviction upended the Grays’ family in summer 2022. On July 25 of that year, a sheriff’s deputy was dispatched to the rental home on a suburban cul-de-sac where Colin Gray, his wife, Colt and the boy’s two younger siblings lived. A moving crew was piling their belongings in the yard.

The Jackson County deputy said in a report that the movers found guns and hunting bows in a closet in the master bedroom. They turned the weapons and ammunition over to the deputy for safekeeping, rather than leave them outside with the family’s other possessions outside.

The deputy wrote that he left copies of receipt forms for the weapons on the front door so that Gray could pick them up later at the sheriff’s office. The reason for eviction is not mentioned in the report. Colin Gray told the investigator in 2023 that he had paid his rent.

It was following the eviction, he said, that his wife left him, taking the two younger siblings with her. Colt Gray “struggled at first with the separation and all,” said the father, who worked a construction job.

“I’m the sole provider, doing high rises downtown,” he told the investigator. Two days later, there was a follow-up interview with Colin Gray while he was at work. He said by phone: “I’m hanging off the top of a building. … I’ve got a big crane lift going, so it’s kind of noisy up here.”

Boy described as quiet

The investigator also interviewed the boy, then 13, who was described in a report as quiet, calm and reserved.

He denied making any threats and said that months earlier he’d stopped using the Discord platform, where the school threat was posted. He later told his father his account had been hacked.

“The only thing I have is TikTok, but I just go on there and watch videos,” the teen said.

A year before they would both end up charged in the high school shooting, Colin Gray insisted to the sheriff’s investigator that his son wasn’t the type to threaten violence.

“He’s not a loner, Officer Miller. Don’t get that,” the father said, adding: “He just wants to go to school, do his own thing and he doesn’t want any trouble.”

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Insurers and reinsurers must ditch “arbitrary” exclusions that cut Ukraine from policies and resume cover to support the war-torn country’s economic recovery, the world’s two biggest insurance brokers have said.

New York-listed rivals Aon and Marsh McLennan said blanket exclusions of Ukraine from policies covering everything from soured loans to property damage, which were put in place after Russia’s full-scale invasion in February 2022, “ignore the diversity of risk throughout the country”.

In a rare joint call, they pushed for a reversal of the insurance and reinsurance industry’s moves to lump Ukraine alongside Belarus and Russia in exclusions from broad reinsurance contracts, limiting the supply of primary insurance and “impeding” Kyiv’s economic recovery. 

The exclusions were part of a market pullback as insurers and reinsurers braced for billions of dollars of losses from destroyed buildings, stranded planes and other damage caused by Russia’s invasion. But Kyiv’s leaders and western allies have repeatedly highlighted the importance of the insurance sector to underpin its economy and enable the huge investment that will be needed for its post-war reconstruction.  

John Doyle, chief executive at Marsh McLennan, said the groups were calling on the global insurance sector — which is gathering in Monaco for its annual Rendez-Vous conference — to “end blanket exclusions for Ukraine” and support the country to attract global investment.

Aon chief executive Greg Case said insurers must “work to strengthen” insurance initiatives already being developed, adding: “Insurance capital is essential for the reconstruction of Ukraine’s healthcare, energy and agricultural sectors.” 

Insurance brokers negotiate with insurers to cover their clients’ assets, from supertankers to credit facilities, against potential losses, with a group of individual insurers typically providing a slice of the cover. Aon and Marsh also have big reinsurance broking operations that help primary insurers share their risks with reinsurers.

With almost all of Ukraine’s revenue allocated to its armed forces and its deficit continuing to rise, its leaders have sought insurance schemes as a way to increase trade and investment.

Both firms have been involved in projects seeking to draw some global insurers back into certain areas of Ukraine’s economy.

Last year, Marsh McLennan reached agreement with Kyiv to provide affordable cover to ships carrying grain from its Black Sea ports. This year, Aon unveiled a scheme with a US development agency that was intended to cover Ukrainian businesses against war risks. 

Broader appetite among insurers to underwrite Ukraine risks remains minimal, however.

Ukraine’s economy recovered from a 29 per cent drop in its GDP in 2022, to grow just under 5 per cent in 2023. But GDP growth is expected to slow to 3.2 per cent this year, according to the World Bank.

In the joint statement, Aon and Marsh said that “arbitrary exclusions for Ukraine contribute to confusion about the vastly different levels of risk in the country”, highlighting central and western areas where there is much less war damage.

Additional reporting by Isobel Koshiw in Kyiv