David Corn@DavidCornDC
2h
At the Trump rally in MSG, David Rem shouts that Kamala Harris “is the Antichrist.”
Yes, he said this. This is the extremism Trump and the GOP inspires and embraces.
I stand corrected. I thought this year’s October surprise was the reality that Trump’s mental state had slipped so badly he could not campaign in any coherent way.
It turns out that the 2024 October surprise was the Trump campaign’s fascist rally at Madison Square Garden, a rally so extreme that Republicans running for office have been denouncing it all over social media tonight.
There was never any question that this rally was going to be anything but an attempt to inflame Trump’s base. The plan for a rally at Madison Square Garden itself deliberately evoked its predecessor: a Nazi rally at the old Madison Square Garden on February 20, 1939. About 18,000 people showed up for that “true Americanism” event, held on a stage that featured a huge portrait of George Washington in his Continental Army uniform flanked by swastikas.
Like that earlier event, Trump’s rally was supposed to demonstrate power and inspire his base to violence.
Apparently in anticipation of the rally, Trump on Friday night replaced his signature blue suit and red tie with the black and gold of the neofascist Proud Boys. That extremist group was central to the January 6, 2021, attack on the U.S. Capitol and has been rebuilding to support Trump again in 2024.
On Saturday the Trump campaign released a list of 29 people set to be on the stage at the rally. Notably, the list was all MAGA Republicans, including vice presidential nominee Ohio senator J.D. Vance, House speaker Mike Johnson (LA), Representative Elise Stefanik (NY), Representative Byron Donalds (FL), Trump backer Elon Musk, Trump ally Rudy Giuliani, Robert F. Kennedy Jr., right-wing host Tucker Carlson, Trump sons Don Jr. and Eric, and Eric’s wife, Republican National Committee co-chair Lara Trump.
Libbey Dean of NewsNation noted that none of the seven Republicans running in New York’s competitive House races were on the list. When asked why not, according to Dean, Trump senior advisor Jason Miller said: “The demand, the request for people to speak, is quite extensive.” Asked if the campaign had turned down anyone who asked to speak, Miller said no.
Meanwhile, the decision of the owners of the Los Angeles Times and the Washington Post not to endorse Democratic presidential candidate Vice President Kamala Harris seems to have sparked a backlash. As Will Bunch of the Philadelphia Inquirer noted, “in a strange way the papers did perform a public service: showing American voters what life under a dictator would feel like.”
Early on October 26, the Washington Post itself went after Trump backer billionaire Elon Musk with a major story highlighting the information that Musk, an immigrant from South Africa, had worked illegally when he started his career in the U.S. Musk “did not have the legal right to work” in the U.S. when he started his first successful company. As part of the Trump campaign, Musk has emphasized his opposition to undocumented immigrants.
The New York Times has tended to downplay Trump’s outrageous statements, but on Saturday it ran a round-up of Trump’s threats in the center of the front page, above the fold. It noted that Trump has vowed to expand presidential power, prosecute his political opponents, and crack down on immigration with mass deportations and detention camps. It went on to list his determination to undermine the North Atlantic Treaty Organization (NATO), use the U.S. military against Mexican drug cartels “in potential violation of international law,” and use federal troops against U.S. citizens. It added that he plans to “upend trade” with sweeping new tariffs that will raise consumer prices, and to rein in regulatory agencies.
“To help achieve these and other goals,” the paper concluded, “his advisers are vetting lawyers seen as more likely to embrace aggressive legal theories about the scope of his power.”
On Sunday the front page of the New York Times opinion section read, in giant capital letters: “DONALD TRUMP/ SAYS HE WILL PROSECUTE HIS ENEMIES/ ORDER MASS DEPORTATIONS/ USE SOLDIERS AGAINST CITIZENS/ ABANDON ALLIES/ PLAY POLITICS WITH DISASTERS/ BELIEVE HIM.” And then, inside the section, the paper provided the receipts: Trump’s own words outlining his fascist plans. “BELIEVE HIM,” the paper said.
On CNN’s State of the Union this morning, host Jake Tapper refused to permit Trump’s running mate, Ohio senator J.D. Vance, to gaslight viewers. Vance angrily denied that Trump has repeatedly called for using the U.S. military against Americans, but Tapper came with receipts that proved the very things Vance denied.
Trump’s rally at Madison Square Garden began in the early afternoon. The hateful performances of the early participants set the tone for the rally. Early on, comedian Tony Hinchcliffe, who goes by Kill Tony, delivered a steamingly racist set. He said, for example: “There’s literally a floating island of garbage in the middle of the ocean right now. I think it’s called Puerto Rico.” He went on: “And these Latinos, they love making babies too. Just know that. They do. They do. There’s no pulling out. They don’t do that. They come inside. Just like they did to our country.” Hinchcliffe also talked about Black people carving watermelons instead of pumpkins.
The speakers who followed Hinchcliffe called Vice President Kamala Harris “the Antichrist” and “the devil.” They called former secretary of state Hillary Clinton “a sick son of a b*tch,” and they railed against “f*cking illegals.” They insulted Latinos generally, Black Americans, Palestinians and Jews. Trump advisor Stephen Miller’s claim that “America is for Americans and Americans only” directly echoed the statement of Adolf Hitler that "Germany is for Germans and Germans only.”
Trump took the stage about two hours late, prompting people to stream toward the exits before he finished speaking. He hit his usual highlights, notably undermining Vance’s argument from earlier in the day by saying that, indeed, he believes fellow Americans are “the enemy within.”
But Trump perhaps gave away the game with his inflammatory language and with an aside, seemingly aimed at House speaker Johnson. “I think with our little secret we are gonna do really well with the House, right? Our little secret is having a big impact, he and I have a secret, we will tell you what it is when the race is over,” Trump said.
It seems possible—probable, even—that Trump was alluding to putting in play the plan his people tried in 2020. That plan was to create enough chaos over the certification of electoral votes in the states to throw the election into the House of Representatives. There, each state delegation gets a single vote, so if the Republicans have control of more states than the Democrats, Trump could pull out a victory even if he had dramatically lost the popular vote.
Since he has made virtually no effort to win votes in 2024, this seems his likely plan.
But to do that, he needs at least a plausibly close election, or at least to convince his supporters that the election has been stolen from him. Tonight’s rally badly hurt that plan.
As Hinchcliffe was talking about Puerto Rico as a floating island of garbage, Democratic presidential nominee Vice President Kamala Harris was at a Puerto Rican restaurant in Philadelphia talking about her plan to spread her opportunity economy to Puerto Rico. She has called for strengthening Puerto Rico’s energy grid and making it easier to get permits to build there.
After the “floating island of garbage” comment, Puerto Rican superstar musician Bad Bunny, who has more than 45 million followers on Instagram, posted Harris’s plan for Puerto Rico, and his spokesperson said he is endorsing Harris.
Puerto Rican singer and actor Ricky Martin shared a clip from Hinchcliffe’s set with his 16 million followers. His caption read: “This is what they think of us.” Singer and actress Jennifer Lopez, who has 250 million Instagram followers, posted Harris’s plan. Later, singer-songwriter and actress Ariana Grande posted that she had voted for Harris. Grande has 376 million followers on Instagram. Singer Luis Fonsi, who has 16 million followers, also called out the “constant hate.”
The headlines were brutal. “MAGA speakers unleash ugly rhetoric at Trump's MSG rally,” read Axios. Politico wrote: “Trump’s New York homecoming sparks backlash over racist and vulgar remarks.” “Racist Remarks and Insults Mark Trump’s Madison Square Garden Rally,” the New York Times announced. “Speakers at Trump rally make racist comments, hurl insults,” read CNN.
But the biggest sign of the damage the rally did was the frantic backpedaling from Republicans in tight elections, who distanced themselves as fast as they could from the insults against Puerto Ricans, especially. The Trump campaign itself tried to distance itself from the “floating island of garbage” quotation, only to be met with comments pointing out that Hinchcliffe’s set had been vetted and uploaded to the teleprompters.
As the clips spread like wildfire, political writer Charlotte Clymer pointed out that almost 6 million Puerto Ricans live in the states—about a million in Florida, half a million in Pennsylvania, 100,000 in Georgia, 100,000 in Michigan, 100,000 in North Carolina, 45,000 in Arizona, and 40,000 in Nevada—and that over half of them voted in 2020.
In 1939, as about 18,000 American Nazis rallied inside Madison Square Garden, newspapers reported that a crowd of about 100,000 anti-Nazis gathered outside to protest. It took 1,700 police officers, the largest number of officers ever before detailed for a single event, to hold them back from storming the venue.
Hungary PM’s visit prompts anger in EU amid widespread concerns about voter intimidation and coercion
...]
Orbán “does not represent the European Union” on his visit, the bloc’s top diplomat Josep Borrell told Spanish public radio on Monday. “The union’s rotating president has no authority in foreign policy,” he added.
In a statement released on Sunday, co-signed with the European Commission, Borrell flagged concerns about reported pressure and intimidation of voters during Saturday’s elections. “We call on the Central Election Commission of Georgia and other relevant authorities to fulfil their duty to swiftly, transparently and independently investigate and adjudicate electoral irregularities and allegations thereof.”
The Hungarian prime minister issued his congratulations to Kobakhidze and the Georgian Dream party for “their overwhelming victory” on Saturday, before the election results had even been published.
A team from the European parliament sent to observe the elections said it found one case of ballot box stuffing, as well as “physical assault on observers attempting to report on violations, observer and media removal from polling stations, tearing up of observer complaints, intimidation of voters inside and outside of polling stations, presence of multiple party-affiliated observers posing as citizen observers”.
The Spanish centre-right MEP Antonio López-Istúriz White, who led the delegation, also said there had been efforts “to undermine and manipulate the vote”, such as pressure on state employees to take part in campaign events and vote, as well as misuse of state resources to benefit the ruling party. “We express deep concern about the democratic backsliding in Georgia,” he said.
The Dutch MEP Thijs Reuten, who was not part of the delegation, called on the EU’s 26 other member states and the commission to push back against the Hungarian leader. “Orbán legitimising these elections undermines the EU itself,” he wrote on X.
The former Belgian prime minister Guy Verhofstadt tweeted: “As Georgia is channelled towards Moscow with Kremlin interference, Viktor Orbán flies to Tbilisi to endorse a corrupted election. An EU leader now openly working for Moscow & Europe’s democrats sit idle! First step..finally remove Orbán’s EU voting rights.”
The European parliament launched a sanctions procedure against Orbán’s government in 2018 that could ultimately strip Hungary of EU voting rights, but the process has languished.
Orbán’s spokesperson said he had been invited by Kobakhidze and would be accompanied by Hungary’s foreign minister, Péter Szijjártó, economy minister, Márton Nagy, and finance minister, Mihály Varga.
It echoes a furore over the Hungarian leader’s freelance diplomacy in the summer, when he visited Kyiv, Moscow, Beijing and Donald Trump’s Mar-a-Lago home on a so-called peace mission.
Well, it’s that time again: Millions of Americans are stress-eating while clicking “Refresh” on 538’s presidential forecast, hoping beyond hope that the little red or blue line will have made a tiny tick upward. Some may be clutching themselves in the fetal position, chanting under their breath: “There’s a good new poll out of Pennsylvania.”
The stakes of this election are sky-high, and its outcome is not knowable in advance—a combination that most of us find deeply discomfiting. People crave certainty, and there’s just one place to look for it: in the data. Earlier humans might have turned to oracles or soothsayers; we have Nate Silver. But the truth is that polling—and the models that rely primarily on polling to forecast the election result—cannot confidently predict what will happen on November 5.
The widespread perception that polls and models are raw snapshots of public opinion is simply false. In fact, the data are significantly massaged based on possibly reasonable, but unavoidably idiosyncratic, judgments made by pollsters and forecasting sages, who interpret and adjust the numbers before presenting them to the public. They do this because random sampling has become very difficult in the digital age, for reasons I’ll get into; the numbers would not be representative without these corrections, but every one of them also introduces a margin for human error.
Most citizens see only the end product: a preposterously precise statistic, such as the notion that Donald Trump has a 50.2 percent—not 50.3 percent, mind you—chance of winning the presidency. (Why stop there? Why not go to three decimal points?) Such numerical precision gives the false impression of certainty where there is none.
Early American political polls were unscientific but seemingly effective. In the early 20th century, The Literary Digest, a popular magazine in its day, sent sample ballots to millions of its readers. By this method, the magazine correctly predicted the winner of every presidential election from 1916 until 1936. In that year, for the contest between Franklin D. Roosevelt and Alf Landon, the Digest sent out roughly 10 million sample ballots and received an astonishing 2.4 million back (a response rate of 24 percent would be off the charts by modern standards). Based on those responses, the Digest predicted that FDR would receive a drubbing, winning just 41 percent of the vote. Instead, he won 61 percent, carrying all but two states. Readers lost faith in the Digest (it went out of business two years later).
The conventional wisdom was that the poll failed because in addition to its readers, the Digest selected people from directories of automobile and telephone ownership, which skewed the sample toward the wealthy—particularly during the Great Depression, when cars and phones were luxuries. That is likely part of the explanation, but more recent analysis has pointed to a different problem: who responded to the poll and who didn’t. For whatever reason, Landon supporters were far more likely than FDR supporters to send back their sample ballots, making the poll not just useless, but wildly misleading. This high-profile error cleared the way for more “scientific” methods, such as those pioneered by George Gallup, among others.
The basic logic of the new, more scientific method was straightforward: If you can generate a truly random sample from the broader population you are studying—in which every person has an equally likely chance of being included in the poll—then you can derive astonishingly accurate results from a reasonably small number of people. When those assumptions are correct and the poll is based on a truly random sample, pollsters need only about 1,000 people to produce a result with a margin of error of plus or minus three percentage points.
To produce reasonably unbiased samples, pollsters would randomly select people from the telephone book and call them. But this method became problematic when some people began making their phone numbers unlisted; these people shared certain demographic characteristics, so their absence skewed the samples. Then cellphones began to replace landlines, and more pollsters made use of “random-digit dialing,” which ensured that every active line had an equal chance of being called. For a while, that helped.
But the matter of whom pollsters contacted was not the only difficulty. Another was how those people responded, and why. A distortion known as social-desirability bias is the tendency of respondents to lie to pollsters about their likely voting behavior. In America, that problem was particularly acute around race: If a campaign pitted a minority candidate against a white candidate, some white respondents might lie and say that they’d vote for the minority candidate to avoid being perceived as racist. This phenomenon, contested by some scholars, is known as the Bradley Effect, named after former Los Angeles Mayor Tom Bradley—a Black politician who was widely tipped to become governor of California based on pre-election polling, but narrowly lost instead. To deal with the Bradley Effect, many pollsters switched from live callers to robocalls, hoping that voters would be more honest with a computer than another person.
But representative sampling has continued to become more difficult. In an age of caller ID and smartphones, along with persistent junk and nuisance calls, few people answer when they see unfamiliar numbers. Most Americans spend much of their time online, but there are no reliable methods to get a truly random sample from the internet. (Consider, for example, how subscribers of The Atlantic differ from the overall American population, and it’s obvious why a digital poll on this site would be worthless at making predictions about the overall electorate.)
These shifts in technology and social behavior have created an enormous problem known as nonresponse bias. Some pollsters release not just findings but total numbers of attempted contacts. Take, for example, this 2018 New York Times poll within Michigan’s Eighth Congressional District. The Times reports that it called 53,590 people in order to get 501 responses. That’s a response rate lower than 1 percent, meaning that the Times pollsters had to call roughly 107 people just to get one person to answer their questions. What are the odds that those rare few who answered the phone are an unskewed, representative sample of likely voters? Zilch. As I often ask my undergraduate students: How often do you answer when you see an unknown number? Now, how often do you think a lonely elderly person in rural America answers their landline? If there’s any systematic difference in behavior, that creates a potential polling bias.
To cope, pollsters have adopted new methodologies. As the Pew Research Center notes, 61 percent of major national pollsters used different approaches in 2022 than they did in 2016. This means that when Americans talk about “the polls” being off in past years, we’re not comparing apples with apples. One new polling method is to send text messages with links to digital surveys. (Consider how often you’d click a link from an unknown number to understand just how problematic that method is.) Many pollsters rely on a mix of approaches. Some have started using online “opt-in” methods, in which respondents choose to take a survey and are typically paid a small amount for participating. This technique, too, has raised reasonable questions about accuracy: One of my colleagues at University College London, Thomas Gift, tested opt-in methods and found that nearly 82 percent of participants in his survey likely lied about themselves in order to qualify for the poll and get paid. Pew further found that online opt-in polls do a poor job of capturing the attitudes of young people and Hispanic Americans.
No matter the method, a pure, random sample is now an unattainable ideal—even the aspiration is a relic of the past. To compensate, some pollsters try to design samples representative of known demographics. One common approach, stratification, is to divide the electorate into subgroups by gender, race, age, etc., and ensure that the sample includes enough of each “type” of voter. Another involves weighting some categories of respondents differently from others, to match presumptions about the broader electorate. For example, if a polling sample had 56 percent women, but the pollster believed that the eventual electorate would be 52 percent women, they might weigh male respondents slightly more heavily in the adjusted results.
The problem, of course, is that nobody knows who will actually show up to vote on November 5. So these adjustments may be justified, but they are inherently subjective, introducing another possible source of human bias. If women come out to vote in historically high numbers in the aftermath of the Supreme Court’s Dobbs decision, for example, the weighting could be badly off, causing a major polling error.
The bottom line is that modern pollsters are trying to correct for known forms of possible bias in their samples by making subjective adjustments to the data. If their judgments are correct, then their polls might be accurate. But there’s no way to know beforehand whether their assumptions about, say, turnout by demographic group are wise or not.
Forecasters then take that massaged polling data and feed it into a model that’s curated by a person—or team of people—who makes further subjective assessments. For example, the 538 model adjusts its forecasts based on polls plus what some in the field call “the fundamentals,” such as historical trends around convention polling bounces, or underlying economic data. Most forecasters also weight data based on how particular pollsters performed in earlier elections. Each adjustment is an educated guess based on past patterns. But nobody knows for sure whether past patterns are predictive of future results. Enough is extraordinary about this race to suspect that they may not be.
More bad news: Modern polling often misses the mark even when trying to convey uncertainty, because pollsters grossly underestimate their margins of error. Most polls report a plus or minus margin of, say, 3 percent, with a 95 percent confidence interval. This means that if a poll reports that Trump has the support of 47 percent of the electorate, then the reported margin of error suggests that the “real” number likely lies between 44 percent (minus three) and 50 percent (plus three). If the confidence interval is correct, that spread of 44 to 50 should capture the actual result of the election about 95 percent of the time. But the reality is less reassuring.
In a 2022 research paper titled “Election Polls Are 95 Percent Confident but Only 60 Percent Accurate,” Aditya Kotak and Don Moore of UC Berkeley analyzed 6,000 polls from 2008 through 2020. They found that even with just one week to go before Election Day, only about six in 10 polls captured the end result within their stated margin of error. Four in 10 times, the polling data fell outside that window. The authors conclude that to justify a 95 percent confidence interval, pollsters should “at least double” their reported margins of error—a move that would be statistically wise but render polling virtually meaningless in close elections. After all, if a margin of error doubled to six percentage points, then a poll finding that Harris had 50 percent support would indicate that the “true” number was somewhere between 44 percent (a Trump landslide) and 56 percent (a Harris landslide).
Alas, the uncertainty doesn’t end there. Unlike many other forms of measurement, polls can change what they’re measuring. Sticking a thermometer outside doesn’t make the weather hotter or colder. But poll numbers can and do shift voting behavior. For example, studies have shown that perceived poll momentum can make people more likely to vote for the surging party or candidate in a “bandwagon” effect. Take the 2012 Republican primaries, when social conservatives sought an alternative to Mitt Romney and were split among candidates. A CNN poll conducted the night before the Iowa caucus showed Rick Santorum in third place. Santorum went on to win the caucus, likely because voters concluded from the poll that he was the most electable challenger.
The truth is that even after election results are announced, we may not really know which forecasters were “correct.” Just as The Literary Digest accurately predicted the winner of presidential races with a deeply flawed methodology, sometimes a bad approach is just lucky, creating the illusion of accuracy. And neither polling nor electoral dynamics are stable over time. Polling methodology has shifted radically since 2008; voting patterns and demographics are ever-changing too. Heck, Barack Obama won Indiana in 2008; recent polls suggest that Harris is losing there by as much as 17 points. National turnout was 55 percent in 2016 and 63 percent in 2020. Polls are trying to hit a moving target with instruments that are themselves constantly changing. For all of these reasons, a pollster who was perfectly accurate in 2008 could be wildly off in 2024.
In other words, presidential elections are rare, contingent, one-off events. Predicting their outcome does not yield enough comparable data points to support any pollster’s claim to exceptional foresight, rather than luck. Trying to evaluate whether a forecasting model is “good” just from judging its performance on the past four presidential elections is a bit like trying to figure out whether a coin is “fair” or “rigged” from just four coin flips. It’s impossible.
The social scientists Justin Grimmer, Dean Knox, and Sean Westwood recently published research supporting this conclusion. They write: “We demonstrate that scientists and voters are decades to millennia away from assessing whether probabilistic forecasting provides reliable insights into election outcomes.” (Their research has sparked fierce debate among scholars about the wisdom of using probabilistic forecasting to measure rare and idiosyncratic events such as presidential elections.)
Probabilistic presidential forecasts are effectively unfalsifiable in close elections, meaning that they can’t be proved wrong. Nate Silver’s model in 2016 suggested that Hillary Clinton had a 71.4 percent chance of victory. That wasn’t necessarily “wrong” when she lost: After all, as Silver pointed out to the Harvard Gazette, events with a 28.6 percent probability routinely happen—more frequently than one in four times. So was his 2016 presidential model “wrong”? Or was it bang-on accurate, but an unusual, lower-probability event took place? There’s no way of knowing for sure.
The pollsters and forecasters who are studying the 2024 election are not fools. They are skilled analysts attempting some nearly impossible wizardry by making subjective adjustments to control for possible bias while forecasting an uncertain future. Their data suggest that the race is a nail-biter—and that may well be the truth. But nobody—not you, not me, not the betting markets, not Nate Silver—knows what’s going to happen on November 5.
Josh Marshall@joshtpm
2h
My biggest worry about the Post at the moment is that Bezos will just say **** this and dump it on some private equity types. Obvs it’s not an attractive business purchase at the moment. And there aren’t that many civic-minded billionaires without a lot of govt reg exposure.
On Monday, October 28, 1929, New York’s Metropolitan Opera Company opened its forty-fifth season.
Four thousand attendees in their finest clothes strolled to the elegant building on foot or traveled in one of a thousand limousines to see Puccini’s Manon Lescaut, the melodramatic story of an innocent French girl seduced by wealth, whose reluctance to leave her riches for true love leads to her arrest and tragic death. Photographers captured images of the era’s social celebrities as they arrived at opening night, their flash bulbs blinding the crowd that had gathered to see the famous faces and expensive gowns.
No one toasting the beginning of the opera season that night knew they were marking the end of an era.
At ten o’clock the next morning, when the opening gong sounded in the great hall of the New York Stock Exchange, men began to unload their stocks. So fast did trading go that by the end of the day, the ticker recording transactions ran two and a half hours late. When the final tally could be read, it showed that an extraordinary 16,410,030 shares had traded hands, and the market had lost $14 billion. The market had been uneasy for weeks before the twenty-ninth, but Black Tuesday began a slide that seemingly would not end. By mid-November the industrial average was half of what it had been in September. The economic boom that had fueled the Roaring Twenties was over.
Once the bottom fell out of the stock market, the economy ground down. Manufacturing output dropped to levels lower than those of 1913. The production of pig iron fell to what it had been in the 1890s. Foreign trade dropped by $7 billion, down to just $3 billion. The price of wheat fell from $1.05 a bushel to 39 cents; corn dropped from 81 to 33 cents; cotton fell from 17 to 6 cents a pound. Prices dropped so low that selling crops meant taking a loss, so struggling farmers simply let them rot in the fields.
By 1932, over one million people in New York City were unemployed. By 1933 the number of unemployed across the nation rose to 13 million people—one out of every four American workers. Unable to afford rent or pay mortgages, people lived in shelters made of packing boxes.
No one knew how to combat the Great Depression, but certain wealthy Americans were sure they knew what had caused it. The problem, they said, was that poor Americans refused to work hard enough and were draining the economy. They must be forced to take less. “Liquidate labor, liquidate stocks, liquidate the farmers, liquidate real estate,” Treasury Secretary Andrew Mellon told President Herbert Hoover. “It will purge the rottenness out of the system. High costs of living and high living will come down. People will work harder, live a more moral life. Values will be adjusted, and enterprising people will pick up the wrecks from less competent people.”
Slash government spending, agreed the Chicago Tribune: lay off teachers and government workers, and demand that those who remain accept lower wages. Richard Whitney, a former president of the Stock Exchange, told the Senate that the only way to restart the economy was to cut government salaries and veterans’ benefits (although he told them that his own salary—which at sixty thousand dollars was six times higher than theirs—was “very little” and couldn’t be reduced).
President Hoover knew little about finances, let alone how to fix an economic crisis of global proportions. He tried to reverse the economic slide by cutting taxes and reassuring Americans that “the fundamental business of the country, that is, production and distribution of commodities, is on a sound and prosperous basis.”
But taxes were already so low that most folks would see only a few extra dollars a year from the cuts, and the fundamental business of the country was not, in fact, sound. When suffering Americans begged for public works programs to provide jobs, Hoover insisted that such programs were a “soak the rich” program that would “enslave” taxpayers, and called instead for private charity.
By the time Hoover’s term ended, Americans were ready to try a new approach to economic recovery. They refused to reelect Hoover and turned instead to New York Governor Franklin Delano Roosevelt, who promised to use the federal government to provide jobs and a safety net to enable Americans to weather hard times. He promised the American people a “New Deal”: a government that would work for everyone, not just for the wealthy and well connected.
As soon as Roosevelt was in office, Democrats began to pass laws protecting workers’ rights, providing government jobs, regulating business and banking, and beginning to chip away at the racial segregation of the American South. New Deal policies employed more than 8.5 million people, built more than 650,000 miles of highways, built or repaired more than 120,000 bridges, and put up more than 125,000 buildings.
They regulated banking and the stock market and gave workers the right to bargain collectively. They established minimum wages and maximum hours for work. They provided a basic social safety net and regulated food and drug safety. And when World War II broke out, the new system enabled the United States to defend democracy successfully against fascists both at home—where they had grown strong enough to turn out almost 20,000 people to a rally at Madison Square Garden in 1939—and abroad.
The New Deal worked so well that common men and women across the country hailed FDR as their leader, electing him an unprecedented four times. Republican Dwight D. Eisenhower built on the New Deal when voters elected him in 1952. He bolstered the nation’s infrastructure with the Federal-Aid Highway Act, which provided $25 billion to build 41,000 miles of highway across the country; added the Department of Health, Education, and Welfare to the government and called for a national healthcare system.
Eisenhower nominated former Republican governor of California Earl Warren as chief justice of the Supreme Court to protect civil rights, which he would begin to do with the 1954 Brown v. Board of Education decision months after joining the court. Eisenhower also insisted on the vital importance of the North Atlantic Treaty Organization (NATO) to stop the Soviet Union from spreading communism throughout Europe.
Eisenhower called his vision “a middle way between untrammeled freedom of the individual and the demands of the welfare of the whole Nation.”
The system worked: between 1945 and 1960 the nation’s gross national product (GNP) jumped by 250%, from $200 billion to $500 billion. The vast majority of Americans of both parties liked the new system that had helped the nation to recover from the Depression and to equip the Allies to win World War II.
Politicians and commentators agreed that most Democrats and Republicans shared a “liberal consensus” that the government should regulate business, provide for basic social welfare, promote infrastructure, and protect civil rights. It seemed the country had finally created a government that best reflected democratic values.
Indeed, that liberal consensus seemed so universal that the only place to find opposition was in entertainment. Popular radio comedian Fred Allen’s show included a caricature, Senator Beauregard Claghorn, a southern blowhard who pontificated, harrumphed, and took his reflexive hatred of the North to ridiculous extremes. A buffoon who represented the past, the Claghorn character was such a success that he starred in his own Hollywood film and later became the basis for the Looney Tunes cartoon rooster Foghorn Leghorn.
Newspapers shouldn’t be in the business of endorsing political candidates.
