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.

• 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

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.

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

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)

• 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 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.

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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Global merger and acquisition deals hit $1.5tn in the first half of 2024 as a surge in US takeovers and an uptick in megamergers offset a declining number of acquisitions.

The value of deals struck was 22 per cent higher than a year earlier, according to mid-year data compiled by the London Stock Exchange Group, driven by a 70 per cent rise in big deals worth more than $10bn.

But the total number of deals fell 25 per cent to a four-year low, with acquisitions worth $500mn or less — the smaller takeovers that make up the backbone of the deal market — falling 13 per cent by value.

“This year for M&A is much better than last year,” said Anu Aiyengar, global head of mergers and acquisitions at JPMorgan. “But that’s a low bar, because last year was a tough year.”

The tentative recovery comes after M&A activity slid to a 10-year low in 2023 as interest rates rose from the ultra-low levels that stoked a pandemic-era deals boom. But it remains fragile.

One senior European banker said: “There’s concerns about the consumer, there’s concerns about elections, rates haven’t come down as fast as people had hoped. All of that introduces more volatility.”

The US was an engine of activity in the first half of this year, with the value of deals up 43 per cent to $796bn, more than half the global total and the country’s largest share of the global market since 2019.

European dealmaking kept pace to rise 43 per cent by value, while the Asia-Pacific region declined 21 per cent.

Top deals that advanced in the second quarter included US oil and gas producer ConocoPhillips’s move to buy its smaller rival Marathon Oil for $22.5bn, the latest in a series of tie-ups in the Permian Basin sparked by ExxonMobil’s acquisition of rival Hess.

Meanwhile, the Abu Dhabi National Oil Company is nearing a €14.4bn agreement to take over the German chemicals group Covestro after boosting its proposed offer this month.

Deals in energy rose 27 per cent this year to $254bn, according to the report, the best sector behind technology.

Still, an uptick in big deals has not been enough to completely shake M&A from its post Covid-19 doldrums, with deal volumes in the three months to the end of June on track to stay below $1tn for the eighth consecutive quarter.

While middle-market deals continued at a slower pace, financial services proved a bright spot for transactions, with deal volumes in the sector up 60 per cent on the same period last year, bolstered by Capital One’s February agreement to acquire rival Discover Financial for $35.3bn.

Investment bankers and lawyers advising on deals said large companies had been increasingly willing to approach potential targets now the macroeconomic environment had begun to stabilise and as they grew impatient to pursue their long-term plans.

Not every approach has been successful — Australian miner BHP’s £39bn effort to take over Anglo American, for example, collapsed in May after a frenzied six-week pursuit.

“Large strategics have been waiting to forge ahead with a long-term plan,” said Ben Wilson, a senior managing director in Guggenheim Securities’ mergers and acquisitions group. “And there are fewer trapdoors.”

Private equity-backed M&A, a focus for dealmakers, rose 40 per cent in the first half of the year as buyout investors sit on a record number of assets that they must sell down to generate returns for their backers.

Larger banks such as Goldman Sachs, JPMorgan and Morgan Stanley increased their share of the M&A advisory fee market to about 35 per cent of the global total, although this remained slightly less than boutique banks led by New York’s Centerview Partners.

Goldman Sachs was the top financial adviser on mergers in the first half of the year, leading in the US and Europe.

Lena Waithe shares why her least favorite thing is being wrong.

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Lena Waithe shares why her least favorite thing is being wrong.

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A note from Wild Card host Rachel Martin:

Lena Waithe knows what she wants. She wants people to look outside of their own lives to try to understand other people and the choices they make. Her TV shows and films are these powerful little empathy engines.

Waithe became the first Black woman ever to win an Emmy for comedy writing on the show Master of None. She’s also the creator of the comedy series Boomerang and Twenties. She wrote the film Queen & Slim and was a producer on the movie Dear White People.

But for me, Waithe’s real triumph is The Chi. The show takes place where she grew up on the south side of Chicago. It’s about Black people living at the margins of society with little to no room for error. It is also about family and loyalty and joy. I love this show because every character is given their full humanity. You cannot put anyone in a tidy column of good or bad or say, “This person is worthy of respect and this person’s not.” People are complicated, beautiful and broken, and Waithe doesn’t want you to look away because if you do, you’re going to miss the truth that she’s putting out into the world – which is that judging people is harder when you start to understand them.

This Wild Card interview has been edited for length and clarity. Host Rachel Martin asks guests randomly-selected questions from a deck of cards. Tap play above to listen to the full podcast, or read an excerpt below.

Question 1: When did you feel like you found your people?

Lena Waithe: Michael Svoboda – who was a writer’s PA on The Game when I was an assistant at Girlfriends – he and I just really vibed. And he was just like, “Yo, I got a writer’s group that I do where we sit and write original pilots that we’re working on to kind of help us get some stuff done.” And I walked into that writer’s group and I just like found all these amazing people that I’m still tight with today.

Rachel Martin: Tell me how that jibes with your hometown Chicago and your experience there, because it sounds like your people were writers. Did you not have that in some way in Chicago?

Waithe: I was a bit of an oddball in Chicago because I was obsessed with TV, obsessed with movies. Like, people go to the movies and watch TV shows – it’s a pastime. And I think my family could tell it was more than that for me – I would be just enthralled by it and be thinking about it.

Like, I have like a Wizard of Oz tattoo. I have Judy Garland. I have the lion. I have the scarecrow. I have all of it, because that movie was more than a movie for me. It was almost like a Bible to life.

It’s like – you always think there’s something out there that’s better than where you’re at right now. But the truth is, when you go out there and get to the Emerald City and meet the wizard, you realize it’s not really what you thought it was. And then all you long for when you’re in the Emerald City is to go where?

Martin: Home.

Waithe: Exactly. And it’s a lesson none of us really learn, still. You know, we still are trying to go, like, “I gotta get to the Wizard – if I could just get to the Emerald City, everything will be fine.”

And then you get there, you’re just like, “I’m still not fine.” And so I think the big reason why Wizard of Oz is such a religion and a reminder for me is that there is no Emerald City that will feel like home.

Martin: Was that sad for you? Was there a grief attached to that?

Waithe: No, it helped me to slow down. Because the truth is, there’s always something you want. And that’s fine, you know, you need that thing to make you want to go. But you got to remember that it’ll be nice if it happens. It’ll be cool. But you don’t want it to be a thing that, if you don’t get it, you can’t find happiness.

Question 2: What makes you irrationally defensive?

Waithe: Irrationally defensive? (laughs) Oh my gosh.

I don’t like to be wrong. My least favorite thing is getting something wrong. And that can be in many ways, you know, it’d be a relationship, you know, some trivia, you know what I mean?

Martin: I love that those were in the same breath..

Waithe: I know it’s like relationship, like Taboo, you know what I mean? I’m not good at not being good at things. So I can get defensive when I’m not like succeeding at something.

Martin: When’s the last time you were wrong about something?

Waithe: Oh, recently. I thought a particular actress was in Game of Thrones. And she wasn’t, and I was so ticked because I was like, “Are you sure that’s not her?” And I looked it up too. I was like, “Let me see, let me see!”

Martin: Right, of course! Because you believed with every fiber of your being that she was in Game of Thrones.

Waithe: I really did. That’s what I’m saying. Like, I was so not happy about that in that moment because I never get that stuff wrong, but it’s okay.

Martin: We’re going to forget you were wrong about that one. No one has to know.

Waithe: Now everybody knows.

Question 3: What’s your best defense against despair?

Waithe: Ooooooh. I love this Baldwin quote. He says to Nikki Giovanni in a beautiful conversation that they’re having where she thinks she’s a pessimist. And he says, “No, you’re a realist. You’re cool, but you’re not a pessimist.” He’s like, “Because you’re alive.” And I think my biggest defense against despair is the fact that I’m alive. Is that I’m here. And even though it can feel like a curse, it is the greatest gift to be Earthside at this time.

And you can’t run away from despair. You can try. I love that Solange song, “Cranes in the Sky,” because it’s all about ways in which we try to run away. So you can try to shop it away, smoke it away, you know, like sex away. You can’t.

Martin: So in the particular, when it has come for you, do you just sit there and like say an affirmation? Like, “I’m alive?” You look in the mirror, you pinch yourself like…

Waithe: No, I’m a sleeper. I’ll try to sleep it away. I try to watch The Comeback, you know, which is my favorite go-to.

Martin: Really? That brings you back from the brinks of despair?

Waithe: No, it just reminds me of a character that is so flawed. But yet, I love and root for so much. Like, Valerie Cherish is a game changing character for me. When I watch that show, I can’t help but look at Valerie Cherish and go, “Alright. I’m alright, I’m okay, I’ll be alright,” You know – that character and that show, The Comeback, ladies and gentlemen, go find it.

Martin: Despair beware!

Waithe: When you are in despair, go watch the first season of The Comeback, okay? And you will be like, “What am I experiencing? And I feel better now cause I’m laughing and also like completely have secondhand embarrassment.”