Small towns would like to be excluded from the rural narrative

Plus: Ohio smackdown, RFK the Republican, Britain vs. Mississippi, LLMs explained

No. 280 | August 11, 2023

First… some personal news! The Intersection’s weekly roundup returns after a brief hiatus following the arrival of our baby boy two weeks ago. We’re beyond blessed that he’s here and healthy. -Patrick

🗳️ Elections

Kati Perry, Tim Meko and Kevin Uhrmacher: Small towns don’t vote like other rural areas (The Washington Post)

Every four years, presidential election maps offer a familiar visual: The sea of Republican red across rural America dotted with blue population centers that overwhelmingly vote for Democrats. Election maps are notoriously bad at conveying the outcome of an election because of the uneven distribution of people across the land. Even county-level maps mask voting patterns in small-town America.

‘When you get out into rural America, it’s actually a lot more heterogeneous than people imagine it to be,’; said Jonathan Rodden, political scientist and author of the book ‘Why Cities Lose: The Deep Roots of the Urban-Rural Political Divide.’ A Washington Post analysis of detailed election results shows that more complicated reality. Yes, voters in America’s small towns favored President Donald Trump in 2020, but they gave Trump roughly 61 percent of their votes, compared with voters in the most rural areas who backed him with 73 percent.”

Kyle Kondik: How the Other Half Votes: The United States, Part One (Sabato’s Crystal Ball)

“Earlier this year, we analyzed several key states by dividing them in half, with a state’s most vote-rich counties adding up to half the statewide vote making up the “top half” of a state, and the rest of the state’s counties making up the ‘bottom half.’ The general though not universal trend is that the top halves are getting bluer and the bottom halves are getting redder or, at the very least, the gap between the two halves is widening.

Both of those observations apply when splitting the nation as a whole into two halves. The nation’s most vote-rich counties, collectively, got bluer from 2012 to 2020 — the two elections we have been comparing as part of this series — while the remaining bottom half counties got collectively redder. That means that the gap between the two halves is increasing.”

Kyle Kondik and J. Miles Coleman: Ohio’s Issue 1 Smackdown (Sabuto’s Crystal Ball)

“There is an old saying that ‘pigs get fat, but hogs get slaughtered.’ It is an apt description for what happened in Ohio’s Issue 1 vote on Tuesday evening.

Ohio Republicans, who already dominate state government, asked voters to essentially take away their own power by raising the threshold for voters to approve statewide constitutional amendment ballot measures from a bare 50% majority to a 60% supermajority. The proposal also would have made the signature-gathering process much more difficult in order to place such amendments in front of voters. The whole point of this process was to erect an impassable barrier in front of a looming constitutional amendment on the ballot in November that would enshrine abortion rights protections into the state constitution.”

Nate Cohn: Why Trump Is So Hard to Beat (The New York Times 🔒)

“In the half century of modern presidential primaries, no candidate who led his or her nearest rival by at least 20 points at this stage has ever lost a party nomination. Today, Donald J. Trump’s lead over Ron DeSantis is nearly twice as large: 37 points, according to a New York Times/Siena College poll of the likely Republican primary electorate released Monday morning.

But even if it might be a mistake to call Mr. Trump “inevitable,” the Times/Siena data suggests that he commands a seemingly unshakable base of loyal supporters, representing more than one-third of the Republican electorate. Alone, their support is not enough for Mr. Trump to win the primary. But it is large enough to make him extremely hard to defeat — perhaps every bit as hard as the historical record suggests.”

Nathaniel Rakich: If RFK Jr. Wants To Be President, He's Running In The Wrong Primary (FiveThirtyEight)

“A certain presidential candidate has been very popular lately. He appeared on Joe Rogan’s podcast. House Republicans invited him to testify before Congress on censorship. Florida Gov. Ron DeSantis, also a Republican, has suggested that if he becomes president, he might nominate him to lead the Food and Drug Administration or Centers for Disease Control. GOP presidential candidate Vivek Ramaswamy said he’d consider him to be his running mate. 

The only problem? This candidate is running in the Democratic primary.”

Nate Cohn: How Did We Do? A Review of 2022 Before Our First Poll of 2023. (The New York Times 🔒)

“Here’s a list of survey results of the 2022 midterm elections, all from the same pollster. As you read them, think about whether you think this pollster’s results were good or bad or whatever adjective you’d like.

Poll: D+6; result: D+2.4

Poll: R+4; result R+1.5

Poll: D+5, result D+4.9

Poll: R+5; result R+7.5

Poll: EVEN; result D+0.8

Poll: D+3, result D+1

All right, what did you think?”

Jessica Piper: ‘Whistling past the graveyard’: Dem fear grows over massive grassroots fundraising hit (Politico) 

“One of the best online fundraising days for Democrats this year was the day of Joe Biden’s campaign launch — but even that day’s haul was meager compared to his campaign kickoff four years ago.

That’s among the findings of an analysis of fundraising for the first half of the year through ActBlue, the party’s primary donation processor. Small-dollar giving at the federal level totaled $312 million in the first half of 2023 — a drop-off of more than $30 million compared to this point in the 2020 cycle. The platform also had 32 percent fewer donors in the second quarter this year compared to four years prior, although its total fundraising increased slightly due to several factors, including more recurring donors and greater giving to non-federal groups.”

Michael Podhorzer: All Politics Are Local; All Political Data Is National (Weekend Reading)

“A foundational flaw with contemporary political analysis is the presumption that what is true generally in the United States is also true in whichever state or jurisdiction matters at the moment. Much of what ‘everyone knows’ about politics depends on taking for granted that what is characteristic of a group is also characteristic of the individuals in the group. Formally, these are known as ecological fallacies. Informally, many ecological fallacies – once they are sufficiently discredited – come to be known as stereotypes or prejudices. 

I’ll begin with illustrations of a few of the most common ecological fallacies in circulation. Along the way, we’ll see that Pew’s “gold standard” validated voter study of the 2022 midterms offered easy offramps from believing some of the silliest ecological fallacies about demographics – but the media sped past those offramps, insisting on continuing to go in the wrong direction in spite of the evidence.”

🗺️ Data Visualization

Aatish Bhatia, Claire Cain Miller and Josh Katz: Study of Elite College Admissions Data Suggests Being Very Rich Is Its Own Qualification (The New York Times)

“Elite colleges have long been filled with the children of the richest families: At Ivy League schools, one in six students has parents in the top 1 percent.

A large new study, released Monday, shows that it has not been because these children had more impressive grades on average or took harder classes. They tended to have higher SAT scores and finely honed résumés, and applied at a higher rate — but they were overrepresented even after accounting for those things. For applicants with the same SAT or ACT score, children from families in the top 1 percent were 34 percent more likely to be admitted than the average applicant, and those from the top 0.1 percent were more than twice as likely to get in.”

John Burn-Murdoch: Is Britain really as poor as Mississippi? (Financial Times)

“It was almost nine years ago to the day when the question of where Britain would rank among the US states for economic heft first became ‘a thing’. In an article for the Spectator, Fraser Nelson calculated that on a gross domestic product per capita basis, and after adjusting for price differences, the UK would sit in 49th place out of the 50 US states, narrowly squeezing in ahead of Mississippi. 

As Britain’s economy has half slumbered, half stumbled its way through the nine years since, pausing to commit occasional acts of egregious self-sabotage, the Mississippi Question has only grown more popular. Could this be the year the UK economy is surpassed by that of the US state with America’s highest poverty rate and a life expectancy almost 10 years shorter than Britain’s?”

📊  Public Opinion

Juliana Menasce Horowitz: Martin Luther King Jr.’s Legacy 60 Years After the March on Washington (Pew Research Center)

“On Aug. 28, 1963, about 250,000 people gathered at the Lincoln Memorial in Washington, D.C., for the March on Washington for Jobs and Freedom, where Martin Luther King Jr. gave his historic ‘I Have a Dream’ speech advocating for economic and civil rights for Black Americans.

As the 60th anniversary of the March on Washington approaches, we asked Americans about their views on King’s legacy, the country’s progress on racial equality, and what needs to change in order to achieve racial equality.”

🤖 Artificial Intelligence 

Timothy B. Lee and Sean Trott: Large language models, explained with a minimum of math and jargon (Understanding AI)

“When ChatGPT was introduced last fall, it sent shockwaves through the technology industry and the larger world. Machine learning researchers had been experimenting with large language models (LLMs) for a few years by that point, but the general public had not been paying close attention and didn’t realize how powerful they had become.

Today almost everyone has heard about LLMs, and tens of millions of people have tried them out. But, still, not very many people understand how they work.

If you know anything about this subject, you’ve probably heard that LLMs are trained to “predict the next word,” and that they require huge amounts of text to do this. But that tends to be where the explanation stops. The details of how they predict the next word is often treated as a deep mystery.”