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Cross-Tabs: July 2024 Times/Siena Poll of the Likely Electorate

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Cross-Tabs: July 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:

• We spoke with 1,142 registered voters across the country from July 22 to 24, 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, we placed more than 140,000 calls to nearly 54,000 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 3.3 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 1,142 registered voters nationwide, including 1,004 who completed the full survey, was conducted in English and Spanish on cellular and landline telephones from July 22 to 24, 2024. The margin of sampling error is plus or minus 3.3 percentage points for registered voters and plus or minus 3.4 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 3.7 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, 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, 13 percent of interviews among self-reported Hispanics were conducted in Spanish, including 20 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 Biden job approval question — 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 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)

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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. 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 1.27 for registered voters and 1.40 for the likely electorate. The design effect for the sample of completed interviews is 1.29 for registered voters and 1.43 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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Kamala Harris memes resonate with Gen Z voters

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Kamala Harris memes resonate with Gen Z voters

In an unofficial video doing the rounds on TikTok, a beaming Kamala Harris jives through the street with school children decked out in a glittery LGBT pride jacket while holding an umbrella. The clip then cuts to images of Donald Trump with notorious sex offender Jeffrey Epstein — all set to a diss track by rapper Kendrick Lamar.

In the four days since Harris became the lead candidate to replace Joe Biden as Democratic presidential nominee, the internet has exploded with memes of the US vice-president giggling, dancing and telling zany stories.

On platforms such as TikTok and X, Gen Z users are creating and sharing content featuring the vice-president, with added colours and electro beats, and spliced with other niche pop culture references.

Democratic strategists say the positive memes are part of a new, youth-led wave of enthusiasm for the party, which Biden, the oldest main party candidate in America’s history, failed to muster.

Although Biden won 59 per cent of voters aged 18-29 in 2020, a YouGov/Yahoo news poll taken before he withdrew from November’s election showed his support had dropped to 43 per cent. Trump’s rating in the same age group was 31 per cent.

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“Young voters will be one of the arteries needed to make sure this campaign is alive and well,” said Antjuan Seawright, a Democratic strategist. “I certainly think we’re seeing energy, interest and participation that we had not seen before.”

Some of the most popular memes describe Harris as a “brat” — a reference to pop singer Charli XCX’s hit summer album that Gen Zers across the US and Europe are having to explain to their elders.

Far from being an insult, the singer said it refers to “that girl who is a little messy and likes to party and maybe says some dumb things sometimes”.

After Charli XCX’s post about Harris went viral, the vice-president’s campaign adopted Brat trappings, changing the colour and font of its X account to those of the singer’s album, an in-joke that has resonated with Gen Zers.

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An analysis of Harris’s popularity on TikTok shows a recent leap in the use of #kamalaharris on the video platform, with mentions going up 455 per cent in the past 30 days.

Her campaign has been quick to lean into the online buzz, by making memes referencing XCX and other artists popular with Gen Z, like Chappell Roan.

You are seeing a snapshot of an interactive graphic. This is most likely due to being offline or JavaScript being disabled in your browser.

Part of Harris’s appeal is her relative youth and historic status as the first main party Black and Asian-American female presidential candidate. But she has also tapped into Gen Z’s irreverent and obscure brand of online humour.

In another viral clip Harris shares an anecdote about her mother admonishing young people: “You think you just fell out of a coconut tree? You exist in the context of all in which you live and what came before you.”

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“In an alternative universe we would see the coconut tree clip and think it’s sort of an incoherent phrase — like I don’t exactly know what she’s talking about, but because of that it’s funny,” said Haley Ellant, a 20-year-old junior at Bernard College.

“We don’t know if she can beat Trump but Gen Z is kind of rallying behind her, because there’s not much else we can do and her personality fits our humour.”

There is already some evidence that the online enthusiasm could translate into tangible support.

In the 48 hours after Biden withdrew from the race, Vote.org, a voter registration non-profit, said it registered 40,000 new voters, 83 per cent of whom were aged 18-34.

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Gen Z political advocacy group Voters of Tomorrow said that it had seen more chapter sign-ups since Harris kicked off her campaign than in the previous two months combined, and its political action committee had its best fundraising day in its history on Sunday, raising nearly $125,000 from grassroots donors.

“That money rolling in the door is a big deal. It costs us about $4.77 to register one voter, so that’s a whole lot of new young voters that we can register,” said Marianna Pecora, Voters of Tomorrow’s director of communications.

Harris is also seen as being to Biden’s left on some crucial policy issues that appeal to young voters, such as climate change, student debt forgiveness and the war in Gaza, as well as having being the administration’s standard bearer on reproductive rights.

“I think she should obviously claim credit for the foundation Joe Biden laid,” said Joseph Geevarghese, executive director of Our Revolution, a progressive advocacy group. “But she would do well to take it a step further and get to the root causes of some of these issues.”

But while Harris is enjoying a newfound popularity on social media platforms, engagement data shows that Trump’s numbers still dwarf those of the Democratic vice-president. 

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Despite Trump posting only five TikToks to date, their viewership ranges from 3mn-164mn, far above the Democrat’s average of 330,000 views per post.

You are seeing a snapshot of an interactive graphic. This is most likely due to being offline or JavaScript being disabled in your browser.

Similarly, on Instagram Harris posts more often across her three accounts but Trump receives more engagement.

The internet has also been flooded by racist posts about Harris. One, which harks back to birther conspiracies about Barack Obama, says that because her parents were immigrants, she is not a “natural born citizen” and ineligible to hold the office of president.

Another depicts a T-shirt with a sexually explicit edited photo of the Harris, reading “Cumala”.

There are also signs that Harris’s ‘memeability’ appeal to Gen Z may be off-putting to older voters.

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“On the one hand they now have a candidate who can walk across the stage and complete a sentence,” said Terry Nelson, a Republican strategist. “On the other side she has a reputation for a word-salad speech pattern.

“Right now you have a rush of excitement about her candidacy — that may last for three months, it may not.”

Data visualisation by Peter Andringa and Sam Learner

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The U.S. men's soccer team opens the Paris Olympics with a tough loss against France

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The U.S. men's soccer team opens the Paris Olympics with a tough loss against France

France’s Kiliann Sildillia (left) is challenged by the USA’s Paxten Aaronson in the opening game of group play at the 2024 Summer Olympics on Wednesday in Marseille, France.

Alex Livesey/Getty Images


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Alex Livesey/Getty Images

NPR is in Paris for the 2024 Summer Olympics. For more of our coverage from the games head to our latest updates.

PARIS — It was a tale of two halves.

The United States men’s soccer team returned to the Olympics after a 16-year absence and opened with a 3-0 loss to host France in group play in Marseille.

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France controlled possession for the first half and outshot the Americans 8-3. But the U.S. looked calm, cool and composed, beating back a physical French team that was whistled for seven fouls. At halftime, it was 0-0.

In Olympic men’s soccer, roster restrictions require nearly all players to be under 23 years old. Most of the U.S. squad, coached by Marko Mitrovic, has previously played in Major League Soccer or an MLS academy club. Walker Zimmerman, age 31, is one of a trio of “overage” players. At the 2022 World Cup in Qatar, he started three times and appeared in all four U.S. matches.

Both the U.S. and France started the second half much how they ended the first: trading spirited passes and attacking deep into their own halves of play. The overwhelmingly French crowd cheered and yelled to will on their squad that finished 13th at the Tokyo Olympics in 2021.

The U.S. missed a golden opportunity to get on the scoreboard first. In the 59th minute, Djordje Mihailovic fired a blistering right-footer that smashed off the crossbar.

The American excitement didn’t last long.

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Two minutes later, French captain Alexandre Lacazette powered a long-range shot from outside the penalty area. It scooted past the outstretched arms of the diving American goalkeeper Patrick Schulte. The score was 1-0 and the crowd came alive.

Lacazette continued his brilliant play in the 69th minute with an assist. He scooted around the American defense and passed to Michael Olise who doubled the French lead to 2-0.

France added another goal off a picture-perfect header from Loïc Badé from a corner kick in the 85th minute.

That was all the host country would need to open play in Group A with an easy 3-0 victory over the U.S.

The U.S. next takes on New Zealand on Saturday in Marseille, France.

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Who Can Achieve the American Dream? Race Matters Less Than It Used To.

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Who Can Achieve the American Dream? Race Matters Less Than It Used To.

Lawrence Cain Jr., a Black millennial in Cincinnati, did not have a comfortable upbringing. His family didn’t have much money. They took few vacations. But Mr. Cain did have a strong community — which he said taught him entrepreneurship and showed him he could dream big. His mom took double shifts at nursing homes. She and her father ran their own businesses. Mr. Cain worked at his grandfather’s deli starting at 11 years old.

Mr. Cain, 35, got a two-year degree in business management and first worked as a bank teller and financial adviser. In 2015, he was ready to forge his own path. He started a financial coaching business, Abundance University. Business is booming. Today, Mr. Cain identifies as solidly middle-class. He and his wife, a teacher, can support themselves, their three children and then some. They take holidays around the country. “My kids are spoiled,” he joked.

Mr. Cain in many ways reflects the trends captured by a new Harvard study. It looked at two groups: a Gen X cohort born in 1978 and a millennial cohort born in 1992. The researchers combed through decades of anonymized census and tax records to which the federal government gave them access. The data covered 57 million children, which offered the researchers a more detailed view into recent generations than previous economic studies had. Adjusting for inflation, they then measured these groups’ ability to rise to the middle and upper classes — their economic mobility.

Lawrence Cain Jr. of Cincinnati did not have an easy upbringing, but today identifies as middle-class.

Asa Featherstone, IV for The New York Times

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The researchers found that Black millennials born to low-income parents had an easier time rising than the previous Black generation did. At the same time, white millennials born to poor parents had a harder time than their white Gen X counterparts. Black people still, on average, make less money than white people, and the overall income gap remains large. But it has narrowed for Black and white Americans born poor — by about 30 percent.

The community you come from has a huge effect on your economic mobility. For centuries, this meant a tremendous advantage for white Americans, even those born into low-income families. But in a surprising shift, the study suggests that advantage is not as large as it once was.

On the flip side of Mr. Cain is someone like Derek Brown, a white millennial in Cincinnati. His parents were separated, and he was raised in two worlds, one middle class and one poor. His dad worked at a General Electric factory, a steady job that provided a more middle-class life. His mom worked long hours at gas stations, Mr. Brown said, but she struggled. Sometimes, she couldn’t pay the bills, and their power was cut off at home. “It was never the dream,” he said.

Unlike Mr. Cain, Mr. Brown did not have a strong sense of community, as he bounced between his mother, his father and his grandparents. Watching his mother, he came to believe that hard work does not necessarily lead to a better life. He once hoped to become a journalist when he grew up, but he gave up that dream to pursue what he believed would be a more realistic way to pay the bills.

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The Northside neighborhood in Cincinnati has crime rates that are higher than the national average.

Asa Featherstone, IV for The New York Times

About five miles south of Northside, the Over-the-Rhine district is known for its dining and culture.

Asa Featherstone, IV for The New York Times

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Today, Mr. Brown, 34, feels that he is behind where his father was. He works as a hairstylist at Great Clips. He lives paycheck to paycheck. He currently has a $3,000 medical bill that his insurance didn’t cover, and he doesn’t know how he’ll pay for it. He’s always scared of the next big cost. “I have really bad financial anxiety,” he said. “I don’t even want to drive to places. What if my car breaks down?”

“It’s instilled in your head: Anything is possible if you work hard for it,” Mr. Brown added. “What no one tells you is that for some people there is a glass ceiling, and you just don’t see it until you hit it.”

As the Harvard study shows, the difference in outcomes between Mr. Cain and Mr. Brown is increasingly typical. But the racial differences weren’t the only findings. Over the decade and a half of the study, the opportunity gap between white people born rich and those born poor expanded by roughly 30 percent. One possible interpretation: “Class is becoming more important in America,” while race is becoming less so, Raj Chetty, the study’s lead author, told me.

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Let’s look at how class has dictated outcomes. For white Americans in particular, changes in mobility significantly differed between those born poor and those born rich.

Imagine four white children: a rich one and a poor one born in 1978, and the same pair born in 1992.

At 27 years old, the poor white millennial would make less money on average than the poor white Gen X-er.

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The white Gen X child born rich, unsurprisingly, could expect to make much more.

And while poor white millennials do worse than their predecessors, rich white millennials do better.

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The change has widened class divides in the United States.

The data didn’t just show that people’s lives were guided by immutable facts like class and race. It suggested that a person’s community — the availability of work, schooling, social networks and so on — plays a central role.

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Imagine a thriving American community. What makes it successful? Jobs are an important factor. So are effective schools, nice parks, low crime rates and a general sense that success is achievable. In a thriving place, people not only get good jobs, but they also know that those jobs can lead to better lives, because they see and feel it all the time. “Our fates are intertwined,” said Stefanie A. DeLuca, a sociologist at Johns Hopkins University who was not part of the Harvard study. “The fortunes of those around you in your community also impact what happens to you.”

On an individual level, Lawrence Cain Jr. benefited from both his mother’s jobs and his family’s support and entrepreneurship. They helped plant the idea that he could work hard and become a business owner. “If your networks are doing well, you may think that you can do well, too,” said David B. Grusky, a sociologist at Stanford who was also not part of the Harvard study.

The inverse is also true. Derek Brown said that his childhood was too chaotic for him to develop strong social roots. Across a community, bad events can cascade and cause things to fall apart. Consider a neighborhood in which crime rises. Businesses move to safer locations. The tax base shrinks, and infrastructure deteriorates along with schools. People flee, and social networks splinter. A sense of despair takes over among the people who remain.

Real-world effects

A cookout in the Northside neighborhood.

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Asa Featherstone, IV for The New York Times

Why did things get worse for poor white people and their communities, but not for their Black counterparts? One explanation focuses on the availability of jobs. The researchers found that community employment levels are an important predictor of differences in economic mobility.

In the real world, the situation might have played out like this: Over the past few decades, globalization and changes in technology have caused many jobs to go from the United States to China, India and elsewhere. These shifts appear to have pushed white people out of the work force, while Black people found other jobs.

There are several explanations for the racial disparity. White workers might have had more wealth or savings to weather unemployment than their Black counterparts did, but at a cost to their upward mobility. They might also have been less willing to find another job. A steel mill that shut down could have employed not just one worker but his father and grandfather, making it a family occupation. People in that situation might feel that they lost something more than a job — and might not settle for any other work.

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The places where Black workers live were generally less affected by job flight than the places where white workers live. And compared with earlier generations, Black workers today are less likely to face racial prejudice in the labor force, making it easier for them to find work. While a white worker might have a generational connection to a steel mill job, a Black worker often does not, because segregation kept his parents and grandparents out.

These trends add up to decades of lost economic progress for low-income white people and the opposite for Black Americans.

Change in persistence of poverty

Share of children born low-income who are no longer low-income at age 27

Source: Opportunity Insights

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The findings do not show that Black opportunity took away from white opportunity. In fact, the study found that white mobility had deteriorated least in the places where Black mobility had improved most.

In some ways, the research might prove politically controversial. Conservatives have long argued that white working-class Americans fell behind, while liberals have emphasized helping minority groups through policies like affirmative action. The left points out that Black and brown people remain far behind their white counterparts and therefore need more help from social programs. The right believes that’s outdated thinking, if it was ever correct. The study provides fodder for both sides.

“The left and the right have very different views on race and class,” said Ralph Richard Banks, a law professor at Stanford who wasn’t involved in the research. “The value of the study is that it brings some unimpeachable evidence to bear on these questions.” He added, “There’s something in it for everyone.”

For their part, the Harvard researchers feel optimistic about one major finding: Economic mobility can change relatively quickly. It improved in Charlotte, N.C., since 2014, after an earlier study by the Harvard group drove the city to make new investments. Local leaders got nonprofits and businesses, including Bank of America, which is based there, to provide job training, education, housing and other services to poorer residents. The researchers hope the results persuade other policymakers around the country to make similar investments.

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“It actually is possible for opportunity to change in a serious way, even in a relatively short time frame,” said Benjamin Goldman, one of the Harvard researchers.

These trends don’t apply evenly to every part of the country. Some places had bigger or smaller gains for Black Americans and bigger or smaller losses for white Americans, as this map shows:

Expected income at age 27 for children born poor, by county

Source: Opportunity Insights

Note: Maps show expected incomes at age 27 in counties with at least 250 children in each relevant group. Counties shown in gray do not have estimates due to insufficient data.

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Mr. Cain believes his story shows that hard work can make a better life possible. He saw just how much his mother, as a Black woman, needed to do to get by. He faced his own doubts and troubles, including racism and discrimination, growing up. But he always remembered what his mother and grandfather taught him — that he could achieve his version of the American dream.

“I can chase that feeling every day of doing things for me, doing things with people I love and making an impact on the community,” Mr. Cain said. “That’s success for me.”

How common are stories like Mr. Cain’s where you live? You can see how economic mobility has changed in your county through this interactive:

Comparing incomes for Black and white children born poor, by county

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Expected income at age 27

Black

White

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