fivethirthyeight--2020-10-08--Trump Doesn’t Know Why Crime Rises or Falls. Neither Does Biden. Or Any Other Politician.

The billboards started popping up around Minneapolis in June .
“ Uptown reels after gunfire , bloodshed.
” “ Multiple shootings in metro area overnight.
” Referencing quotes from local newspapers and TV stations , the signs were part of an ad campaign aimed at turning concerns over a spike in gun violence into a pro-police political movement .
The city of Minneapolis had a long , exhausting spring and summer .
COVID-19 lockdowns starting in March were followed by the release of a graphic video showing a police officer killing George Floyd , sparking massive protests against police brutality @ @ @ @ @ @ @ made news around the world .
Then came the heat wave .
And a withered job market that disproportionately affected Black residents .
In August , another , smaller bout of unrest broke out after a murder suspect shot himself and community members initially believed that he ’ d been killed by police .
Through it all , crime ticked upward .
By September 1 , the city ’ s violent crime rate was 16.8 % higher than the previous five-year average .
The rise in crime in Minneapolis has been mirrored across @ @ @ @ @ @ @ city seeing an increase in murder compared with recent years .
It ’ s enough of a trend that op-eds have begun to refer to a “ Minneapolis effect , ” a nationwide crime spike driven , ostensibly , by civil unrest in one city .
President Trump has blamed the increase in crime on Democratic mayors and positioned a return to law and order as a major platform of his reelection campaign .
Stop criticizing police and crack down on crime , the argument goes , and the problem will be solved @ @ @ @ @ @ @ , but here ’ s the catch : We don ’ t actually know why crime went up this year .
To be fair , we don ’ t truly know why crime goes up … well , ever .
Nor do we know how to make it go down in the long term .
Despite — or perhaps because of — half a century of modern criminology data keeping and analysis , all researchers have to go on are correlations — and none of them clearly explain all the times crime has @ @ @ @ @ @ @ claim they know how to bring down crime , even though no single political policy can reduce crime or stop it from rising in the first place .
When political figures push solutions to crime , they ’ re effectively trying to build a platform on the deck of a ghost ship — and their proposals and prevarications are often about something other than crime itself .
It all started with Goldwater On September 10 , 1964 , Barry Goldwater flew a chartered jet to Minneapolis to warn the people of the city @ @ @ @ @ @ @ speech was part of the senator ’ s presidential campaign , and crime was a major feature of his platform .
Crime wasn ’ t just a safety problem for America , Goldwater told voters ; it was part of an identity problem .
“ [ N ] othing prepares the way for tyranny more than the failure of public officials to keep the streets safe from bullies and marauders , ” he said in his speech accepting the Republican nomination .
America was in danger .
Americans , personally , were in @ @ @ @ @ @ @ to do something about it .
This campaign marked the first time crime became a national issue in American society , said Katherine Beckett , a professor of sociology at the University of Washington .
Sure , Americans had thought about crime on a national scale before — during the Prohibition era , the federal government created an entire agency to enforce a federal law banning alcohol sales .
But Goldwater was the first national politician to turn local crime into a national issue solvable by the executive branch .
Crime was trending @ @ @ @ @ @ @ the violent crime rate — murder and nonnegligent manslaughter , rape , robbery and aggravated assault — had been about 161 offenses per 100,000 people .
By the year of the presidential election , it was up to about 191 , according to the FBI ’ s Uniform Crime Reports , a collection of data from thousands of local law enforcement agencies used to estimate national averages .
The fact that crime was rising in the mid-1960s did not come as a huge surprise to criminologists , said Richard Rosenfeld , a professor @ @ @ @ @ @ @ Louis .
Even today , experts seem to treat this particular increase in crime as almost boring .
That ’ s because it correlated strongly with demographic shifts .
The perpetration of crime isn ’ t evenly distributed across our lifespans .
Instead , it ’ s a curve , peaking in our late teens and early 20s .
Why that happens so reliably is a question that could fill a whole other article , but suffice it to say , a population that is disproportionately young is one of the very few @ @ @ @ @ @ @ in crime .
In other words , Goldwater should have blamed the Baby Boomers .
The simple explanations aren ’ t the right ones But there ’ s never just one thing that causes crime to go up or down .
The national crime rise of the mid-1960s is probably the most straightforward , everybody-agrees situation we have on record , but even there , a swell of young people wasn ’ t the only thing going on that could have led to an increase in crime .
“ What do you need @ @ @ @ @ @ @ asked Gary LaFree , a professor of criminology at the University of Maryland .
“ Someone willing to do it .
Things like legitimacy really play into that.
” To LaFree , it matters that during the mid-to-late 1960s many Americans were questioning and challenging the legitimacy of police and government .
“ In the ’ 60s , respect for police was so low , ” he said .
“ It wasn ’ t uncommon in Baltimore for a body to show up at 2 a.m. with no witnesses and no one willing @ @ @ @ @ @ @ and other , confounding factors wipe away the possibility of demographic determinism as a neat , tidy explanation for crime .
And that ’ s even before you get to the far steeper crime increase of the mid-1980s ( which experts told us no one saw coming ) or the crime decline of the mid-1990s ( ditto ) .
Neither cleanly fits with the Youth Cause Crime theory of the 1960s .
This is the main problem with all theories of what causes a crime wave : Everything is based on correlation .
@ @ @ @ @ @ @ obligated to remind you — finding a correlation ain ’ t the same thing as identifying a cause .
“ There ’ s no way to conduct a randomized controlled experiment on changes in aggregate-level crime rates , and even if we could , we shouldn ’ t , ” Rosenfeld said .
Instead , researchers are left to look for other shifts in society that match with the timing of the shifts in crime .
That might be demographic changes .
Or economic ones .
It could be social distress and the @ @ @ @ @ @ @ the introduction of a new drug , like crack cocaine in the ’ 80s .
It could be environmental contaminants , like leaded gasoline .
It could be a political change , like the legalization of abortion .
Too many guns , not enough guns .
They all can sound pretty damn convincing on their own .
But dig too hard at any one correlation and its explanatory power falls apart .
At least as a single , predictable cause .
One way to really poke at crime-cause theories is by comparing the @ @ @ @ @ @ @ similar nations , such as Canada .
That ’ s what Franklin Zimring , a professor of criminology at Berkeley Law , did in the mid-2000s .
He was looking at the massive decline in crime that began in the U.S. around 1994 and found that Canada had a large increase in crime about the same time , and a large decrease that also closely tracked the timing in the U.S .
Between 1990 and 2000 , crime fell by 35 percent in the U.S. and 33 percent in Canada .
But many @ @ @ @ @ @ @ as causes of crime decline in the U.S. — the falling popularity of crack , a booming economy in the ’ 90s , higher abortion rates in the ’ 70s and ’ 80s , increased imprisonment rates , more police on the street — didn ’ t necessarily happen in Canada .
Canada ’ s unemployment rate , for example , peaked much higher in the early 1990s and never recovered to the extent that it did in the U.S. Why would two countries that share a border and many cultural characteristics have @ @ @ @ @ @ @ shared correlational causes ?
The mystery eventually led Zimring to suspect that crime is cyclical .
It ’ s going to go up , and it ’ s going to go down .
And eventually it will go up again .
When we told him we didn ’ t understand how that explained anything , he was cheerfully blunt .
“ Neither do I !
When you see that cyclicality , what I ’ m telling you is to be puzzled , ” he said .
All of this leaves a vacuum that @ @ @ @ @ @ @ .
More often than not during a crime wave , they want to deter crime by imposing stricter punishments .
But talk to social scientists and they ’ ll probably tell you that because we don ’ t know what the primary driver of crime is , we should be expansive in our solutions .
That includes thinking about nonpunitive measures that appear to help reduce crime — like education , health care access or after-school programs — in addition to more standard responses like putting more police on the streets .
It @ @ @ @ @ @ @ idea what helped drive the decline in violence , after all .
Research by Patrick Sharkey , a sociology professor at Princeton University , has indicated that a huge expansion of nonprofits and neighborhood groups contributed to the crime decline in the 1990s .
But the expansion of police forces and mass incarceration also seem to have had an impact , and even changes like the growth of surveillance technology and cellphone ownership appear to have helped drive down property crime like car thefts .
The trouble for researchers trying to pick apart @ @ @ @ @ @ @ none of those effects happened independently of one another .
“ The efforts of nonprofits to take back parks and playgrounds would probably have been less effective if the police hadn ’ t been cracking down at the same time , ” Sharkey said .
“ But similarly , it wasn ’ t just that the police came in and kicked ass and cleared the streets of troublemakers .
It was also that residents were out in public spaces demanding that those communities would no longer be places where kids were not allowed @ @ @ @ @ @ @ not allowed to go to a park.
” Trying to untangle which of those factors was responsible for more of the decline , he said , is a “ misleading exercise.
” In other words , there are multiple control levers policymakers can try pulling .
Research even shows that people who live in high-crime neighborhoods want to see all the levers pulled at once , in addition to police reform .
But politicians tend to gravitate toward law-and-order solutions — a trend that dates back to the first push to make crime @ @ @ @ @ @ @ that Goldwater speech in Minneapolis in 1964 .
His rhetoric didn ’ t leave space for a mixture of increased law enforcement and nonpunitive measures .
That ’ s because he saw things like government-funded social-welfare programs as the cause of crime .
“ If it is entirely proper for government to take from some to give to others , then won ’ t some be led to believe that they can rightfully take from anyone who has more than they ?
” Goldwater said .
His law-and-order speeches freely bounced between people @ @ @ @ @ @ @ rights activists participating in lawful protest and people participating in riots linked to racial injustice .
At the time , it was enough for the executive secretary of the NAACP to warn that a Goldwater win would likely lead to the creation of a police state .
And even though Goldwater lost , that punishment-first attitude came to define our national strategy — in part because Richard Nixon picked it up and used it , successfully , in his 1968 presidential campaign .
Politicians on both sides of the aisle ran with that @ @ @ @ @ @ @ Joe Biden , for example , was deeply involved in tough-on-crime legislation throughout the ’ 70s , ’ 80s , and ’ 90s , working with Sen. Strom Thurmond on a series of bills that helped create America ’ s system of minimum sentences and mass incarceration .
It ’ s a record Biden apologizes for now , but at the time , he seemed confident in the merits of punitive measures , and confident it was what his constituents wanted .
This , too , tracks with research .
Researchers have found @ @ @ @ @ @ @ 20th century , so did Americans ’ support for punitive measures .
Peter K. Enns , a political scientist at Cornell University who studies public opinion , analyzed Americans ’ attitudes toward crime and punishment from the 1960s through the 1990s and found that the public grew significantly more enthusiastic about harsher disciplinary responses to crime on a variety of metrics , including the death penalty .
Part of that was in response to genuine anxiety about crime .
But those fears were amplified by the fact that crime became a fixture of @ @ @ @ @ @ @ common refrain from politicians .
Michael Fortner , a political science professor at the City University of New York Graduate Center , told us that the rising crime rates created the backdrop for politicians to focus on crime .
The crime wave , he said , “ allow [ ed ] political elites to develop narratives and programs and use them strategically , ” so even if people weren ’ t personally affected by crime , their fear could be “ mobilized for political purposes.
” Over this period , politicians were focused @ @ @ @ @ @ @ some grassroots efforts to push for more comprehensive reform , according to Lisa Miller , a political science professor at Rutgers University who studies the politics of crime .
But it was harder for those complicated responses to gain traction , in part because responses to crime tend to be handled at the local level .
( This is , to some extent , why nationalized police reform remains a near political impossibility — it ’ s just difficult for the federal government to force the country ’ s 18,000 police departments to @ @ @ @ @ @ @ Meanwhile , Miller said , “ it ’ s not that hard to push money down from the federal government to build new prisons and hire more police ” — which is exactly what happened .
And the politics of crime — something that ’ s never really been free of racial dimensions — became hopelessly entangled with the backlash to the civil rights movement , which was happening just as the first crime wave was taking off .
According to Beckett , both Goldwater and Nixon conflated protest and crime in their @ @ @ @ @ @ @ t believe their law-and-order rhetoric was rooted in any careful observation of the data , ” she said .
“ With a sleight of hand they combined [ protest and crime ] and equated all protests and riots with crime and violence.
” Over the following decades , crime became a code word for much more than homicide or property crime — politicians used it to harness white voters ’ racial fears and resentments .
“ It was an effective way of tapping into and amplifying racial tensions in a way that affords @ @ @ @ @ @ @ calls you out for being racist , ” Beckett said .
And it still is .
Research shows that , regardless of actual crime levels , Americans report feeling less safe in their neighborhoods if more young black men also live there .
All of this helps explain why law and order is resurfacing as one of the major themes of the 2020 campaign .
A summer of simultaneously spiking crime rates and nationwide protests against racialized police brutality makes for a brew that ’ s similar to what we saw in the @ @ @ @ @ @ @ on rising racial resentment , protests and riots across the country , and an actual crime wave in his presidential campaign .
Then — as now — Nixon , Goldwater , and other politicians didn ’ t really know why crime was rising , or whether the trend would continue .
They also didn ’ t know what would bring the crime rate down .
But that didn ’ t stop them from turning the nascent trend to their political advantage — something that could have long-term consequences .
If the crime spike @ @ @ @ @ @ @ , we ’ ll have to grapple with the fact that although the punitive responses of the 1980s and 1990s are now largely regarded as a mistake , they probably did something to reduce crime .
Adaner Usmani , a sociologist at Harvard University who studies crime and punishment , said that it ’ s too easy to forget that a policy can be at least partially effective and also the wrong choice to make .
“ I ’ m in agreement with many people that [ criminal justice ] policy choices over @ @ @ @ @ @ @ .
But there ’ s a lot of good evidence that they ’ ve had the effect that , narrowly speaking , politicians and the public hoped they would have , ” he said .
That ’ s not a politically easy answer — that our past response to crime may have worked , but at a cost too great to repeat .
That ’ s the trouble with responses to crime , though , Sharkey said .
There ’ s no incentive for politicians , thinking about their next reelection cycle , @ @ @ @ @ @ @ that could keep crime rates down .
Instead , there are potentially great political rewards for using crime as a dog whistle for other things , like mobilizing racial resentment .
The irony is that this political pattern may actually worsen crime itself , insofar as it makes certain communities less likely to trust politicians and political institutions , and resources aren ’ t directed to the parts of communities that can actually prevent crime from rising .
Remember LaFree ’ s theories about how the loss of institutional legitimacy can lead to @ @ @ @ @ @ @ don ’ t trust the police to treat them fairly , they ’ re also unlikely to report crimes or work with police in ways that could prevent crime .
The stories politicians tell us about why crime matters , how much it matters and what to do about it have not done a great job of matching up with reality , Miller said .
The consequence is that our view of potential solutions to crime gets narrower — punishment starts to seem like the silver bullet , but anyone with an eye @ @ @ @ @ @ @ .
And the more that picture of the world narrows , the more people of color get crushed by it .
From Goldwater to Minneapolis ( and long before ) law and order has affected those groups differently than it has white Americans .
After half a century of dog whistles , it ’ s hard to disentangle tough-on-crime rhetoric from white fears about Black and brown people .
And it ’ s impossible to impose tough-on-crime solutions without disproportionate ( and unfair ) impacts on their lives .
It matters that we @ @ @ @ @ @ @ in all its complexity , because there are people at that other end of society ’ s sticks and carrots .
“ We just sort of fill in with whatever causal explanation is most recent and most at the ready , which I guess is just how our brains work , ” Miller said .
“ But if we get the causal story wrong , they ’ re the ones who will [ bear ] the brunt .
”

The billboards started popping up around Minneapolis in June. “Uptown reels after gunfire, bloodshed.” “Multiple shootings in metro area overnight.” Referencing quotes from local newspapers and TV stations, the signs were part of an ad campaign aimed at turning concerns over a spike in gun violence into a pro-police political movement.
The city of Minneapolis had a long, exhausting spring and summer. COVID-19 lockdowns starting in March were followed by the release of a graphic video showing a police officer killing George Floyd, sparking massive protests against police brutality — some of which turned violent and made news around the world. Then came the heat wave. And a withered job market that disproportionately affected Black residents. In August, another, smaller bout of unrest broke out after a murder suspect shot himself and community members initially believed that he’d been killed by police.
Through it all, crime ticked upward. By September 1, the city’s violent crime rate was 16.8% higher than the previous five-year average.
The rise in crime in Minneapolis has been mirrored across the nation, with nearly every major city seeing an increase in murder compared with recent years. It’s enough of a trend that op-eds have begun to refer to a “Minneapolis effect,” a nationwide crime spike driven, ostensibly, by civil unrest in one city. President Trump has blamed the increase in crime on Democratic mayors and positioned a return to law and order as a major platform of his reelection campaign. Stop criticizing police and crack down on crime, the argument goes, and the problem will be solved.
It’s a neat explanation, but here’s the catch: We don’t actually know why crime went up this year. To be fair, we don’t truly know why crime goes up … well, ever. Nor do we know how to make it go down in the long term. Despite — or perhaps because of — half a century of modern criminology data keeping and analysis, all researchers have to go on are correlations — and none of them clearly explain all the times crime has gone up.
But politicians continue to claim they know how to bring down crime, even though no single political policy can reduce crime or stop it from rising in the first place. When political figures push solutions to crime, they’re effectively trying to build a platform on the deck of a ghost ship — and their proposals and prevarications are often about something other than crime itself.
1964
DENVER POST VIA GETTY IMAGES
It all started with Goldwater
On September 10, 1964, Barry Goldwater flew a chartered jet to Minneapolis to warn the people of the city about crime in the streets. The speech was part of the senator’s presidential campaign, and crime was a major feature of his platform. Crime wasn’t just a safety problem for America, Goldwater told voters; it was part of an identity problem. “[N]othing prepares the way for tyranny more than the failure of public officials to keep the streets safe from bullies and marauders,” he said in his speech accepting the Republican nomination. America was in danger. Americans, personally, were in danger, and the federal government needed to do something about it.
This campaign marked the first time crime became a national issue in American society, said Katherine Beckett, a professor of sociology at the University of Washington. Sure, Americans had thought about crime on a national scale before — during the Prohibition era, the federal government created an entire agency to enforce a federal law banning alcohol sales. But Goldwater was the first national politician to turn local crime into a national issue solvable by the executive branch.
Crime was trending upward in 1964. In 1960, the violent crime rate — murder and nonnegligent manslaughter, rape, robbery and aggravated assault — had been about 161 offenses per 100,000 people. By the year of the presidential election, it was up to about 191, according to the FBI’s Uniform Crime Reports, a collection of data from thousands of local law enforcement agencies used to estimate national averages.
The fact that crime was rising in the mid-1960s did not come as a huge surprise to criminologists, said Richard Rosenfeld, a professor of criminology at the University of Missouri-St. Louis. Even today, experts seem to treat this particular increase in crime as almost boring. That’s because it correlated strongly with demographic shifts.
The perpetration of crime isn’t evenly distributed across our lifespans. Instead, it’s a curve, peaking in our late teens and early 20s. Why that happens so reliably is a question that could fill a whole other article, but suffice it to say, a population that is disproportionately young is one of the very few variables that can consistently predict a rise in crime. In other words, Goldwater should have blamed the Baby Boomers.
1976
DENVER POST VIA GETTY IMAGES
The simple explanations aren’t the right ones
But there’s never just one thing that causes crime to go up or down. The national crime rise of the mid-1960s is probably the most straightforward, everybody-agrees situation we have on record, but even there, a swell of young people wasn’t the only thing going on that could have led to an increase in crime.
“What do you need for a crime to happen?” asked Gary LaFree, a professor of criminology at the University of Maryland. “Someone willing to do it. Things like legitimacy really play into that.” To LaFree, it matters that during the mid-to-late 1960s many Americans were questioning and challenging the legitimacy of police and government. “In the ’60s, respect for police was so low,” he said. “It wasn’t uncommon in Baltimore for a body to show up at 2 a.m. with no witnesses and no one willing to work with the system.”
This and other, confounding factors wipe away the possibility of demographic determinism as a neat, tidy explanation for crime. And that’s even before you get to the far steeper crime increase of the mid-1980s (which experts told us no one saw coming) or the crime decline of the mid-1990s (ditto). Neither cleanly fits with the Youth Cause Crime theory of the 1960s.
This is the main problem with all theories of what causes a crime wave: Everything is based on correlation. And — as we’re contractually obligated to remind you — finding a correlation ain’t the same thing as identifying a cause.
“There’s no way to conduct a randomized controlled experiment on changes in aggregate-level crime rates, and even if we could, we shouldn’t,” Rosenfeld said.
Instead, researchers are left to look for other shifts in society that match with the timing of the shifts in crime. That might be demographic changes. Or economic ones. It could be social distress and the delegitimization of police. It could be the introduction of a new drug, like crack cocaine in the ’80s. It could be environmental contaminants, like leaded gasoline. It could be a political change, like the legalization of abortion. Too many guns, not enough guns. They all can sound pretty damn convincing on their own. But dig too hard at any one correlation and its explanatory power falls apart. At least as a single, predictable cause.
One way to really poke at crime-cause theories is by comparing the correlations in the U.S. with those in similar nations, such as Canada. That’s what Franklin Zimring, a professor of criminology at Berkeley Law, did in the mid-2000s. He was looking at the massive decline in crime that began in the U.S. around 1994 and found that Canada had a large increase in crime about the same time, and a large decrease that also closely tracked the timing in the U.S. Between 1990 and 2000, crime fell by 35 percent in the U.S. and 33 percent in Canada. But many of the things that experts have proposed as causes of crime decline in the U.S. — the falling popularity of crack, a booming economy in the ’90s, higher abortion rates in the ’70s and ’80s, increased imprisonment rates, more police on the street — didn’t necessarily happen in Canada. Canada’s unemployment rate, for example, peaked much higher in the early 1990s and never recovered to the extent that it did in the U.S. Why would two countries that share a border and many cultural characteristics have a decline in crime but no obvious shared correlational causes?
The mystery eventually led Zimring to suspect that crime is cyclical. It’s going to go up, and it’s going to go down. And eventually it will go up again. When we told him we didn’t understand how that explained anything, he was cheerfully blunt. “Neither do I! When you see that cyclicality, what I’m telling you is to be puzzled,” he said.
2016
SAMUEL CORUM / ANADOLU AGENCY / GETTY IMAGES
How politicians fill the void
All of this leaves a vacuum that politicians are more than happy to fill. More often than not during a crime wave, they want to deter crime by imposing stricter punishments. But talk to social scientists and they’ll probably tell you that because we don’t know what the primary driver of crime is, we should be expansive in our solutions. That includes thinking about nonpunitive measures that appear to help reduce crime — like education, health care access or after-school programs — in addition to more standard responses like putting more police on the streets.
It’s not that we have no idea what helped drive the decline in violence, after all. Research by Patrick Sharkey, a sociology professor at Princeton University, has indicated that a huge expansion of nonprofits and neighborhood groups contributed to the crime decline in the 1990s. But the expansion of police forces and mass incarceration also seem to have had an impact, and even changes like the growth of surveillance technology and cellphone ownership appear to have helped drive down property crime like car thefts. The trouble for researchers trying to pick apart what was the biggest driver is that none of those effects happened independently of one another.
“The efforts of nonprofits to take back parks and playgrounds would probably have been less effective if the police hadn’t been cracking down at the same time,” Sharkey said. “But similarly, it wasn’t just that the police came in and kicked ass and cleared the streets of troublemakers. It was also that residents were out in public spaces demanding that those communities would no longer be places where kids were not allowed to go outside at night, or not allowed to go to a park.” Trying to untangle which of those factors was responsible for more of the decline, he said, is a “misleading exercise.”
1970
OLIVA FALL / THE DENVER POST VIA GETTY IMAGES
In other words, there are multiple control levers policymakers can try pulling. Research even shows that people who live in high-crime neighborhoods want to see all the levers pulled at once, in addition to police reform.
But politicians tend to gravitate toward law-and-order solutions — a trend that dates back to the first push to make crime a national issue.
Think back to that Goldwater speech in Minneapolis in 1964. His rhetoric didn’t leave space for a mixture of increased law enforcement and nonpunitive measures. That’s because he saw things like government-funded social-welfare programs as the cause of crime. “If it is entirely proper for government to take from some to give to others, then won’t some be led to believe that they can rightfully take from anyone who has more than they?” Goldwater said.
His law-and-order speeches freely bounced between people committing illegal acts of violence, civil rights activists participating in lawful protest and people participating in riots linked to racial injustice. At the time, it was enough for the executive secretary of the NAACP to warn that a Goldwater win would likely lead to the creation of a police state.
And even though Goldwater lost, that punishment-first attitude came to define our national strategy — in part because Richard Nixon picked it up and used it, successfully, in his 1968 presidential campaign. Politicians on both sides of the aisle ran with that baton for the next few decades. Joe Biden, for example, was deeply involved in tough-on-crime legislation throughout the ’70s, ’80s, and ’90s, working with Sen. Strom Thurmond on a series of bills that helped create America’s system of minimum sentences and mass incarceration. It’s a record Biden apologizes for now, but at the time, he seemed confident in the merits of punitive measures, and confident it was what his constituents wanted.
This, too, tracks with research. Researchers have found that as crime rose in the late 20th century, so did Americans’ support for punitive measures. Peter K. Enns, a political scientist at Cornell University who studies public opinion, analyzed Americans’ attitudes toward crime and punishment from the 1960s through the 1990s and found that the public grew significantly more enthusiastic about harsher disciplinary responses to crime on a variety of metrics, including the death penalty.
Part of that was in response to genuine anxiety about crime. But those fears were amplified by the fact that crime became a fixture of media coverage during this period and a common refrain from politicians. Michael Fortner, a political science professor at the City University of New York Graduate Center, told us that the rising crime rates created the backdrop for politicians to focus on crime. The crime wave, he said, “allow[ed] political elites to develop narratives and programs and use them strategically,” so even if people weren’t personally affected by crime, their fear could be “mobilized for political purposes.”
Over this period, politicians were focused primarily on punitive solutions. There were some grassroots efforts to push for more comprehensive reform, according to Lisa Miller, a political science professor at Rutgers University who studies the politics of crime. But it was harder for those complicated responses to gain traction, in part because responses to crime tend to be handled at the local level. (This is, to some extent, why nationalized police reform remains a near political impossibility — it’s just difficult for the federal government to force the country’s 18,000 police departments to play by the same rules.) Meanwhile, Miller said, “it’s not that hard to push money down from the federal government to build new prisons and hire more police” — which is exactly what happened.
2020
STEPHEN MATUREN / GETTY IMAGES
And the politics of crime — something that’s never really been free of racial dimensions — became hopelessly entangled with the backlash to the civil rights movement, which was happening just as the first crime wave was taking off. According to Beckett, both Goldwater and Nixon conflated protest and crime in their presidential campaigns. “I don’t believe their law-and-order rhetoric was rooted in any careful observation of the data,” she said. “With a sleight of hand they combined [protest and crime] and equated all protests and riots with crime and violence.” Over the following decades, crime became a code word for much more than homicide or property crime — politicians used it to harness white voters’ racial fears and resentments. “It was an effective way of tapping into and amplifying racial tensions in a way that affords [a politician] protection if someone calls you out for being racist,” Beckett said. And it still is. Research shows that, regardless of actual crime levels, Americans report feeling less safe in their neighborhoods if more young black men also live there.
All of this helps explain why law and order is resurfacing as one of the major themes of the 2020 campaign. A summer of simultaneously spiking crime rates and nationwide protests against racialized police brutality makes for a brew that’s similar to what we saw in the late 1960s, when Nixon successfully capitalized on rising racial resentment, protests and riots across the country, and an actual crime wave in his presidential campaign. Then — as now — Nixon, Goldwater, and other politicians didn’t really know why crime was rising, or whether the trend would continue. They also didn’t know what would bring the crime rate down. But that didn’t stop them from turning the nascent trend to their political advantage — something that could have long-term consequences.
If the crime spike of this summer turns into a wave, we’ll have to grapple with the fact that although the punitive responses of the 1980s and 1990s are now largely regarded as a mistake, they probably did something to reduce crime. Adaner Usmani, a sociologist at Harvard University who studies crime and punishment, said that it’s too easy to forget that a policy can be at least partially effective and also the wrong choice to make. “I’m in agreement with many people that [criminal justice] policy choices over the last 30 years have been disastrous. But there’s a lot of good evidence that they’ve had the effect that, narrowly speaking, politicians and the public hoped they would have,” he said.
That’s not a politically easy answer — that our past response to crime may have worked, but at a cost too great to repeat. That’s the trouble with responses to crime, though, Sharkey said. There’s no incentive for politicians, thinking about their next reelection cycle, to prioritize the long-term investments in communities that could keep crime rates down. Instead, there are potentially great political rewards for using crime as a dog whistle for other things, like mobilizing racial resentment.
The irony is that this political pattern may actually worsen crime itself, insofar as it makes certain communities less likely to trust politicians and political institutions, and resources aren’t directed to the parts of communities that can actually prevent crime from rising. Remember LaFree’s theories about how the loss of institutional legitimacy can lead to crime — if people in a community don’t trust the police to treat them fairly, they’re also unlikely to report crimes or work with police in ways that could prevent crime.
The stories politicians tell us about why crime matters, how much it matters and what to do about it have not done a great job of matching up with reality, Miller said. The consequence is that our view of potential solutions to crime gets narrower — punishment starts to seem like the silver bullet, but anyone with an eye on the data knows it is not.
And the more that picture of the world narrows, the more people of color get crushed by it. From Goldwater to Minneapolis (and long before) law and order has affected those groups differently than it has white Americans. After half a century of dog whistles, it’s hard to disentangle tough-on-crime rhetoric from white fears about Black and brown people. And it’s impossible to impose tough-on-crime solutions without disproportionate (and unfair) impacts on their lives. It matters that we get the story on crime right, in all its complexity, because there are people at that other end of society’s sticks and carrots.
“We just sort of fill in with whatever causal explanation is most recent and most at the ready, which I guess is just how our brains work,” Miller said. “But if we get the causal story wrong, they’re the ones who will [bear] the brunt.”


fivethirthyeight--2020-10-08--The Vice Presidential Debate Was Civil. But Did It Shake Up The Race?

In this episode of the FiveThirtyEight Politics podcast , the crew reacts to the first and only vice presidential debate @

The Vice Presidential Debate Was Civil. But Did It Shake Up The Race?
In this episode of the FiveThirtyEight Politics podcast, the crew reacts to the first and only vice presidential debate.


fivethirthyeight--2020-10-08--The L.A. Rams Are Running Their Way Back Into Contention

The Los Angeles Rams were the toast of football under second-year coach Sean McVay in 2018 , finishing 13-3 and going all the way to the Super Bowl before losing a defensive struggle to Bill Belichick ’ s New England Patriots .
Despite the defeat , L.A. remained the team to emulate ; an arms race to hire McVay clones became the dominant theme of the following offseason .
But the Rams struggled to keep building on their success , missing the playoffs last year with a 9-7 record .
By the end of the season , there were concerns @ @ @ @ @ @ @ Angeles ’ s tricks — and that the McVay magic was suddenly gone .
And yet , here the 2020 Rams are , off to a 3-1 start and looking like legitimate Super Bowl contenders again .
Our forecast model gives Los Angeles a 71 percent chance of returning to the playoffs , with a 4 percent chance of winning it all — tied for eighth-best in the league .
And although some of the principals involved have changed , McVay has managed to reclaim key elements of the formula that made the @ @ @ @ @ @ @ charmed 2018 season .
Last year ’ s Rams were undone in large part by a noticeable decline on offense , dipping from third overall in schedule-adjusted expected points added ( EPA ) per game to 14th .
The biggest culprit ?
Surprisingly — given how important the passing game is in determining a team ’ s offensive fate — it was actually the Rams ’ rushing that fell off a cliff , falling from No .
1 in EPA per game to No .
28 .
Running back Todd Gurley , who @ @ @ @ @ @ @ per carry ) for most of 2018 , struggled with only 3.8 yards per carry , and his backups were just as ineffective .
( It wasn ’ t all their fault : L.A. also dropped from sixth in yards before first contact per rush , a measure of run-blocking , to 30th last year . )
Either way , for a hyper-modern offense that everyone was scrambling to copy , it ’ s amazing how quickly Los Angeles was made mortal by simply neutralizing its efficiency running the ball .
That lack @ @ @ @ @ @ @ The Rams feature a heavy play-action-based passing scheme , and while there ’ s no evidence the effectiveness of a team ’ s rushing boosts the effectiveness of its play-fakes , it is true that play-action does at least work much better in down-and-distance situations in which the threat of running is more credible .
So when L.A. ’ s early down rushing fell from sixth in yards per carry in 2018 to 27th in 2019 — and when it couldn ’ t force opponents to stack more defenders in the box to @ @ @ @ @ @ @ often found themselves in situations in which play-action was less effective .
As a result , Jared Goff ’ s QBR on play-passes dropped from 77.2 ( 11th-best ) in 2018 to 59.2 ( 25th ) in 2019 .
But this season , the Rams ’ rushing attack has returned in a big way .
Second-year running back Darrell Henderson is averaging 5.2 yards per carry , 11th-best among qualified rushers , and as a team , Los Angeles ranks third in schedule-adjusted rushing EPA per game .
Rushing makes up 36 percent @ @ @ @ @ @ @ season , which ranks seventh in the league ; compare that with last year ’ s 25 percent mark ( 28th ) , and you get a sense of how much McVay has gone back to the basics to rediscover what worked so well during L.A. ’ s Super Bowl run .
And because the Rams have been so much more successful running early in offensive series — they ’ re averaging 5.3 yards per carry on first down , for instance — they ’ ve put themselves in more favorable play-action situations @ @ @ @ @ @ @ play-fakes is back up to 85.7 , which ranks 15th among qualified passers this season , and Los Angeles ranks second in the league ( behind the Tennessee Titans ) with 51.8 percent of its passing yards coming off of play-action attempts .
It ’ s all coming together to propel the Rams back near the top of the league in offensive EPA , with the team ranking sixth this season after last year ’ s drop-off .
Together with the ninth-best EPA defense in the NFL so far , Los Angeles is @ @ @ @ @ @ @ with the Kansas City Chiefs — sitting among the top 10 on both offense and defense at the moment .
Although the Rams play in a very tough division , featuring both the surging Seattle Seahawks and the defending NFC champion San Francisco 49ers — and their schedule gets tougher from here on — Los Angeles does seem to have fixed some of the major problems behind its Super Bowl hangover last season .
Looking ahead : The best game of Week 5 was shaping up to be Bills vs. Titans , but @ @ @ @ @ @ @ status of that contest will be after more Tennessee players tested positive for COVID-19 on Wednesday .
( Welcome to sports in 2020 ! )
Instead , we turn our attention to Cleveland , where the Browns will host the Indianapolis Colts in a battle between two serious playoff contenders .
Both teams have postseason odds north of 60 percent ; the Colts have won three straight games , while the Browns are coming off an extremely impressive 49-38 victory at Dallas .
Indy has the edge at QB according to our ratings @ @ @ @ @ @ @ 2 in EPA ) will probably put up more resistance than the Cowboys ’ D did last week .
But the Browns do have home-field advantage on their side , in theory ( home and road teams have actually split games 50-50 this season ) , and we ’ re considering Cleveland-Indianapolis a true pick- ’ em .
Elo ’ s spread : Cleveland PK

The Los Angeles Rams were the toast of football under second-year coach Sean McVay in 2018, finishing 13-3 and going all the way to the Super Bowl before losing a defensive struggle to Bill Belichick’s New England Patriots. Despite the defeat, L.A. remained the team to emulate; an arms race to hire McVay clones became the dominant theme of the following offseason. But the Rams struggled to keep building on their success, missing the playoffs last year with a 9-7 record. By the end of the season, there were concerns that opposing coaches had figured out Los Angeles’s tricks — and that the McVay magic was suddenly gone.
And yet, here the 2020 Rams are, off to a 3-1 start and looking like legitimate Super Bowl contenders again. Our forecast model gives Los Angeles a 71 percent chance of returning to the playoffs, with a 4 percent chance of winning it all — tied for eighth-best in the league. And although some of the principals involved have changed, McVay has managed to reclaim key elements of the formula that made the Rams so tough to stop during that charmed 2018 season.
Last year’s Rams were undone in large part by a noticeable decline on offense, dipping from third overall in schedule-adjusted expected points added (EPA) per game to 14th. The biggest culprit? Surprisingly — given how important the passing game is in determining a team’s offensive fate — it was actually the Rams’ rushing that fell off a cliff, falling from No. 1 in EPA per game to No. 28. Running back Todd Gurley, who had been so dangerous (4.9 yards per carry) for most of 2018, struggled with only 3.8 yards per carry, and his backups were just as ineffective. (It wasn’t all their fault: L.A. also dropped from sixth in yards before first contact per rush, a measure of run-blocking, to 30th last year.)
Either way, for a hyper-modern offense that everyone was scrambling to copy, it’s amazing how quickly Los Angeles was made mortal by simply neutralizing its efficiency running the ball.
L.A. is back to its successful formula Leaguewide ranks in schedule-adjusted expected points added (EPA) for the Los Angeles Rams by season and category, 2018-20 Offense Defense Season Total Passing Rushing Total Passing Rushing Sp. Teams Overall 2018 3 6 1 14 10 21 15 3 2019 14 9 28 7 12 12 21 10 2020* 6 9 3 9 5 23 31 6 *2020 schedule adjustment uses a combination of 2019 and 2020 stats to measure opponent strength. Sources: ESPN Stats & Information Group
That lack of rushing success had ripple effects. The Rams feature a heavy play-action-based passing scheme, and while there’s no evidence the effectiveness of a team’s rushing boosts the effectiveness of its play-fakes, it is true that play-action does at least work much better in down-and-distance situations in which the threat of running is more credible. So when L.A.’s early down rushing fell from sixth in yards per carry in 2018 to 27th in 2019 — and when it couldn’t force opponents to stack more defenders in the box to help contain the run — the Rams often found themselves in situations in which play-action was less effective. As a result, Jared Goff’s QBR on play-passes dropped from 77.2 (11th-best) in 2018 to 59.2 (25th) in 2019.
But this season, the Rams’ rushing attack has returned in a big way. Second-year running back Darrell Henderson is averaging 5.2 yards per carry, 11th-best among qualified rushers, and as a team, Los Angeles ranks third in schedule-adjusted rushing EPA per game. Rushing makes up 36 percent of the Rams’ total yardage this season, which ranks seventh in the league; compare that with last year’s 25 percent mark (28th), and you get a sense of how much McVay has gone back to the basics to rediscover what worked so well during L.A.’s Super Bowl run.
And because the Rams have been so much more successful running early in offensive series — they’re averaging 5.3 yards per carry on first down, for instance — they’ve put themselves in more favorable play-action situations again. Goff’s QBR after play-fakes is back up to 85.7, which ranks 15th among qualified passers this season, and Los Angeles ranks second in the league (behind the Tennessee Titans) with 51.8 percent of its passing yards coming off of play-action attempts.
It’s all coming together to propel the Rams back near the top of the league in offensive EPA, with the team ranking sixth this season after last year’s drop-off. Together with the ninth-best EPA defense in the NFL so far, Los Angeles is one of only two teams — along with the Kansas City Chiefs — sitting among the top 10 on both offense and defense at the moment. Although the Rams play in a very tough division, featuring both the surging Seattle Seahawks and the defending NFC champion San Francisco 49ers — and their schedule gets tougher from here on — Los Angeles does seem to have fixed some of the major problems behind its Super Bowl hangover last season.
FiveThirtyEight’s NFL Elo ratings How each team ranks through Week 4 of the 2020 season, according to our quarterback-adjusted predictions Chance To … Rk Team Starting QB QB Rk* Elo Rating Proj. Record Make Playoffs Win Division Win SB 1 Chiefs Mahomes 1 1737 14-2 >99% 95% 25% 2 Packers Rodgers 6 1655 12-4 95 77 13 3 Ravens Jackson 4 1648 11-5 87 47 8 4 Seahawks Wilson 3 1639 12-4 92 60 10 5 Bills Allen 7 1619 11-5 88 71 6 6 Steelers Roethlisberger 9 1603 11-5 80 36 5 7 Rams Goff 13 1585 10-6 71 24 4 8 Saints Brees 5 1584 9-7 63 38 4 9 Buccaneers Brady 16 1581 10-6 73 50 5 10 Titans Tannehill 11 1580 11-5 79 57 4 11 49ers Garoppolo✚ 24 1575 9-7 47 11 3 12 Colts Rivers 20 1572 10-6 68 40 3 13 Bears Foles 21 1544 9-7 63 19 2 14 Browns Mayfield 26 1539 10-6 64 17 2 15 Cowboys Prescott 2 1530 8-8 58 54 1 16 Vikings Cousins 27 1497 7-9 21 2 <1 17 Eagles Wentz 22 1496 7-8-1 37 33 <1 18 Raiders Carr 8 1495 8-8 28 4 <1 19 Cardinals Murray 10 1481 7-9 24 4 <1 20 Patriots Newton✚ 19 1464 9-7 61 28 2 21 Panthers Bridgewater 17 1458 7-9 23 8 <1 22 Falcons Ryan 14 1447 5-11 6 3 <1 23 Chargers Taylor✚ 31 1444 6-10 8 <1 <1 24 Dolphins Fitzpatrick 12 1438 6-10 7 1 <1 25 Texans Watson 15 1434 5-11 5 2 <1 26 Broncos Lock✚ 29 1433 6-10 15 2 <1 27 Lions Stafford 18 1421 6-10 10 <1 <1 28 Bengals Burrow 25 1402 5-10-1 7 <1 <1 29 Jaguars Minshew 23 1364 5-11 3 <1 <1 30 Washington Allen 32 1364 5-11 11 9 <1 31 Giants Jones 28 1354 4-12 4 4 <1 32 Jets Flacco 30 1351 3-13 <1 <1 <1 *Ranking among Week 5 starters, according to our QB Elo ratings. ✚ Starter is currently injured and may not play. Simulations as of Oct. 7, 2020. Source: ESPN
Looking ahead: The best game of Week 5 was shaping up to be Bills vs. Titans, but it’s not clear what the status of that contest will be after more Tennessee players tested positive for COVID-19 on Wednesday. (Welcome to sports in 2020!) Instead, we turn our attention to Cleveland, where the Browns will host the Indianapolis Colts in a battle between two serious playoff contenders. Both teams have postseason odds north of 60 percent; the Colts have won three straight games, while the Browns are coming off an extremely impressive 49-38 victory at Dallas. Indy has the edge at QB according to our ratings, and its defense (No. 2 in EPA) will probably put up more resistance than the Cowboys’ D did last week. But the Browns do have home-field advantage on their side, in theory (home and road teams have actually split games 50-50 this season), and we’re considering Cleveland-Indianapolis a true pick-’em. Elo’s spread: Cleveland PK
Check out our latest NFL predictions.


fivethirthyeight--2020-10-09--Can You Parallel Park Your Car?

Can You Parallel Park Your Car?

Welcome to The Riddler .
Every week , I offer up problems related to the things we hold dear around here : math , logic and probability .
Two puzzles are presented each week : the Riddler Express for those of you who want something bite-size and the Riddler Classic for those of you in the slow-puzzle movement .
Submit a correct answer for either , and you may get a shoutout in next week ’ s column .
Please wait until Monday to publicly share your answers !
If you need a hint or have a favorite puzzle collecting @ @ @ @ @ @ @ on Twitter .
Every weekend , I drive into town for contactless curbside pickup at a local restaurant .
Across the street from the restaurant are six parking spots , lined up in a row .
While I can parallel park , it ’ s definitely not my preference .
No parallel parking is required when the rearmost of the six spots is available or when there are two consecutive open spots .
If there is a random arrangement of cars currently occupying four of the six spots , what ’ s the @ @ @ @ @ @ @ park ?
Parking cars is one thing — parking trucks is another thing entirely .
Suppose I ’ m driving a very long truck ( with length L ) with two front wheels and two rear wheels .
( The truck is so long compared to its width that I can consider the two front wheels as being a single wheel , and the two rear wheels as being a single wheel . )
Question 1 : Suppose I can rotate the front wheels up to 30 degrees in either direction ( right @ @ @ @ @ @ @ wheels do not turn .
What is the truck ’ s turning radius ?
Question 2 : Suppose I can also rotate the rear wheels — independently from the front wheels — 30 degrees in either direction .
Now what is the truck ’ s turning radius ?
Congratulations to 👏 Derek Carnegie 👏 of Geneva , Switzerland , winner of last week ’ s Riddler Express .
Last week , you considered “ hip ” numbers that could be written as the difference between two perfect squares .
For example , the @ @ @ @ @ @ @ equals 72−32 , or 49−9 .
But hold the phone , 40 was doubly hip , because it also equals 112−92 , or 121−81 .
Meanwhile , 42 was not particularly hip .
It was then left to you to determine the hipness of the number 1,400 — how many ways could 1,400 be written as the difference of two perfect squares ?
You could have tested out lots of square numbers or written code to do it for you , like solver Eero Kuusi from Helsinki , Finland .
But most readers @ @ @ @ @ @ @ written as A2−B2 , could be factored as ( A+B ) ( A−B ) .
So to find the different possible values of A and B , you had to identify the factor pairs of 1,400 — the greater factor was equal to A+B and the lesser factor was equal to A−B .
In other words , A was the average of the two factors , while B was half their difference .
The number 1,400 had a prime factorization of 23×52×71 .
So for a number to be a divisor of 1,400 @ @ @ @ @ @ @ and three powers of 2 , between zero and two powers of 5 and zero or one power of 7 .
That meant 1,400 had a total of 24 factors ( four times three times two ) , or 12 factor pairs .
Here they are : At this point , you might have thought the answer was 12 .
But not so fast !
Remember , when it came to the difference of squares , the root of the greater square was the average of the two factors .
For this to @ @ @ @ @ @ @ factors had to be even or both factors had to be odd .
Among the 12 factor pairs of 1,400 , six of them had one even number and one odd number ( 1×1,400 , 5×800 , 7×200 , 8×175 , 25×56 and 35×40 ) .
The remaining factors pairs had two even numbers .
( Since 1,400 was an even number , it couldn ’ t have been the product of two odd factors . )
In all , there were six factor pairs with two even numbers , which meant six @ @ @ @ @ @ @ be written as the difference of squares in exactly six ways : For extra credit ( which admittedly went well beyond “ Riddler Express territory ” ) , you had to find a general approach for determining how many ways a whole number N could be written as the difference of squares .
Like the original puzzle , a good first step was to start with the number ’ s prime factorization , which we could write as N = 2a×3b×5c×7d×… .
Again , you wanted to determine the number of unique factor @ @ @ @ @ @ @ or both factors were odd .
But first , it was helpful to count the total number of odd factors , ( b+1 ) ( c+1 ) ( d+1 ) … , which we ’ ll call F. When a was zero , all F of N ’ s factors were odd .
That meant N had F/2 factor pairs .
( Okay , technically it was the ceiling of F/2 , accounting for cases in which N was a square number . )
And when a was one , every factor pair @ @ @ @ @ @ @ odd number , so there were no ways to write N as a difference of squares .
When a was greater than one , at least one number in each factor pair was even , so you wanted to count the factor pairs in which both numbers were even .
There were ( a+1 ) ×F/2 total factor pairs , F of which included an odd factor .
That meant there were ( a−1 ) ×F/2 pairs of even factors , and so this was the number of ways you could write N @ @ @ @ @ @ @ Again , it was technically the ceiling of ( a−1 ) ×F/2 , accounting for when N was a square number . )
In other words , when N was even and divisible by 4 , the answer was the number of factor pairs for N/4 .
This math checked out in the case when N was 1,400 , or 23×52×71 .
For this value of N , N/4 was 350 , or 21×52×71 , which had 12 factors , or six factor pairs — the answer to the Express .
Anyway , @ @ @ @ @ @ @ indeed a sextuply hip number .
Congratulations to 👏 Gary M. Gerken 👏 of Littleton , Colorado , winner of last week ’ s Riddler Classic .
Last week , I had 10 chocolates in a bag : Two were milk chocolate , while the other eight were dark chocolate .
One at a time , I randomly pulled chocolates from the bag and ate them — that is , until I picked a chocolate of the other kind .
When I got to the other type of chocolate , I put it @ @ @ @ @ @ @ again with the remaining chocolates .
I kept going until I had eaten all 10 chocolates .
For example , if I first pulled out a dark chocolate , I ate it .
( I always ate the first chocolate I pulled out . )
If I pulled out a second dark chocolate , I ate that as well .
If the third one was milk chocolate , I did not eat it ( yet ) , and instead placed it back in the bag .
Then I started again , eating the @ @ @ @ @ @ @ were the chances that the last chocolate I ate was milk chocolate ?
But before we get into any analytical solutions , let ’ s check in with our Monte Carlo-minded friends .
Ian Greengross and Kyle Giddon both ran 1 million simulations of the problem , while Josh Silverman ran 10 million simulations .
All three of them found the same result : In about half of the simulations , the last chocolate was milk chocolate .
Could it be that the answer was simply… a half ?
Yes !
The answer @ @ @ @ @ @ @ is a proof of why this is true , based on the explanation of solver Guy D. Moore : Suppose there are two chocolates in the bag : one dark and one milk .
In this “ base case , ” they each have a 50 percent chance of being the last ( i.e.
, the second ) chocolate you ’ ll eat .
Next , we ’ ll take a mathematical leap of faith .
Suppose we ’ ve proven — somehow — that there ’ s a 50 percent chance the @ @ @ @ @ @ @ chocolate whenever the total starting number of chocolates is less than some value N. What would happen if I now started with N chocolates ?
Well , one of three things could happen .
( Again , let ’ s suppose that d of these N chocolates are dark and m are milk .
Note that this implies d+m = N , since every chocolate must be either dark or milk . )
• I go on a “ dark ” streak and pick out all d dark chocolates first , which means @ @ @ @ @ @ @ milk .
This is one of the N choose d total ways to order the chocolates , so the probability this occurs is one divided by N choose d , which is d !
( N−d ) !
/N !
, or d !
m !
/N !
, since N−d equals m. • I go on a “ milk ” streak and pick out all m milk chocolates first , which means the last chocolate I eat will be dark .
Again , this is one of the N choose d ways @ @ @ @ @ @ @ probability this occurs is also d !
m !
/N !
.
• I don ’ t go on either streak .
I ’ ll eat some milk or dark chocolates until I pick out a chocolate of the other kind .
At this point , I ’ m effectively starting over with a bag that has fewer than N chocolates .
By my earlier leap of faith , I assumed the probability of now finishing with a milk chocolate was 50 percent .
So then what are the chances of finishing with @ @ @ @ @ @ @ chocolates in the bag ?
It ’ s 50 percent !
That ’ s because finishing with dark or milk is equally likely in the third case , and equally likely when you consider the first and second cases together .
Let ’ s take a final step back to get a bigger picture of what just happened .
When there were two chocolates in the bag ( one of each type ) , you had a 50 percent chance of finishing with a milk chocolate .
We also showed that if there @ @ @ @ @ @ @ fewer than N chocolates , there ’ s also a 50 percent chance for N chocolates .
Since it was 50 percent when there were two chocolates , it must also be true when there were three .
That means it must also be true when there were four .
And five .
And then six .
And so on !
All of this amounts to a proof by induction : showing something is true for a “ base case ” ( here , two ) , and then using an induction step @ @ @ @ @ @ @ higher cases .
Indeed , this was a beautiful problem with an even more beautiful result .
No matter how many chocolates of either type you started with — as long as you had at least one of each — the chances of finishing with either were precisely 50 percent .
In a neat little extension , solver Laurent Lessard proved that this was not the case when there were three types of chocolates .
So it ’ s a good thing we left out the white chocolate .
( That , and @ @ @ @ @ @ @ . )
Well , aren ’ t you lucky ?
There ’ s a whole book full of the best puzzles from this column and some never-before-seen head-scratchers .
It ’ s called “ The Riddler , ” and it ’ s in stores now !

Welcome to The Riddler. Every week, I offer up problems related to the things we hold dear around here: math, logic and probability. Two puzzles are presented each week: the Riddler Express for those of you who want something bite-size and the Riddler Classic for those of you in the slow-puzzle movement. Submit a correct answer for either, and you may get a shoutout in next week’s column. Please wait until Monday to publicly share your answers! If you need a hint or have a favorite puzzle collecting dust in your attic, find me on Twitter.
Riddler Express
Every weekend, I drive into town for contactless curbside pickup at a local restaurant. Across the street from the restaurant are six parking spots, lined up in a row.
While I can parallel park, it’s definitely not my preference. No parallel parking is required when the rearmost of the six spots is available or when there are two consecutive open spots. If there is a random arrangement of cars currently occupying four of the six spots, what’s the probability that I will have to parallel park?
The solution to this Riddler Express can be found in the following week’s column.
Riddler Classic
Parking cars is one thing — parking trucks is another thing entirely. Suppose I’m driving a very long truck (with length L) with two front wheels and two rear wheels. (The truck is so long compared to its width that I can consider the two front wheels as being a single wheel, and the two rear wheels as being a single wheel.)
Question 1: Suppose I can rotate the front wheels up to 30 degrees in either direction (right or left), but the rear wheels do not turn. What is the truck’s turning radius?
Question 2: Suppose I can also rotate the rear wheels — independently from the front wheels — 30 degrees in either direction. Now what is the truck’s turning radius?
The solution to this Riddler Classic can be found in the following week’s column.
Solution to last week’s Riddler Express
Congratulations to 👏 Derek Carnegie 👏 of Geneva, Switzerland, winner of last week’s Riddler Express.
Last week, you considered “hip” numbers that could be written as the difference between two perfect squares. For example, the number 40 was hip, since it equals 72−32, or 49−9. But hold the phone, 40 was doubly hip, because it also equals 112−92, or 121−81. Meanwhile, 42 was not particularly hip.
It was then left to you to determine the hipness of the number 1,400 — how many ways could 1,400 be written as the difference of two perfect squares?
You could have tested out lots of square numbers or written code to do it for you, like solver Eero Kuusi from Helsinki, Finland. But most readers recognized that any difference of squares, written as A2−B2, could be factored as (A+B)(A−B). So to find the different possible values of A and B, you had to identify the factor pairs of 1,400 — the greater factor was equal to A+B and the lesser factor was equal to A−B. In other words, A was the average of the two factors, while B was half their difference.
The number 1,400 had a prime factorization of 23×52×71. So for a number to be a divisor of 1,400, it had to have between zero and three powers of 2, between zero and two powers of 5 and zero or one power of 7. That meant 1,400 had a total of 24 factors (four times three times two), or 12 factor pairs. Here they are:
1 and 1,400
2 and 700
4 and 350
5 and 280
7 and 200
8 and 175
10 and 140
14 and 100
20 and 70
25 and 56
28 and 50
35 and 40
At this point, you might have thought the answer was 12. But not so fast! Remember, when it came to the difference of squares, the root of the greater square was the average of the two factors. For this to be a whole number, either both factors had to be even or both factors had to be odd. Among the 12 factor pairs of 1,400, six of them had one even number and one odd number (1×1,400, 5×800, 7×200, 8×175, 25×56 and 35×40). The remaining factors pairs had two even numbers. (Since 1,400 was an even number, it couldn’t have been the product of two odd factors.)
In all, there were six factor pairs with two even numbers, which meant six was the correct answer — 1,400 could be written as the difference of squares in exactly six ways:
351 2 − 349 2 = 123,201 − 121,801 = 1,400
− 349 = 123,201 − 121,801 = 1,400 177 2 − 173 2 = 31,329 − 29,929 = 1,400
− 173 = 31,329 − 29,929 = 1,400 75 2 − 65 2 = 5,625 − 4,225 = 1,400
− 65 = 5,625 − 4,225 = 1,400 57 2 − 43 2 = 3,249 − 1,849 = 1,400
− 43 = 3,249 − 1,849 = 1,400 45 2 − 25 2 = 2,025 − 625 = 1,400
− 25 = 2,025 − 625 = 1,400 392 − 112 = 1,521 − 121 = 1,400
For extra credit (which admittedly went well beyond “Riddler Express territory”), you had to find a general approach for determining how many ways a whole number N could be written as the difference of squares. Like the original puzzle, a good first step was to start with the number’s prime factorization, which we could write as N = 2a×3b×5c×7d×….
Again, you wanted to determine the number of unique factor pairs in which both factors were even or both factors were odd. But first, it was helpful to count the total number of odd factors, (b+1)(c+1)(d+1)…, which we’ll call F.
When a was zero, all F of N’s factors were odd. That meant N had F/2 factor pairs. (Okay, technically it was the ceiling of F/2, accounting for cases in which N was a square number.) And when a was one, every factor pair had exactly one even number and one odd number, so there were no ways to write N as a difference of squares.
When a was greater than one, at least one number in each factor pair was even, so you wanted to count the factor pairs in which both numbers were even. There were (a+1)×F/2 total factor pairs, F of which included an odd factor. That meant there were (a−1)×F/2 pairs of even factors, and so this was the number of ways you could write N as a difference of squares. (Again, it was technically the ceiling of (a−1)×F/2, accounting for when N was a square number.) In other words, when N was even and divisible by 4, the answer was the number of factor pairs for N/4.
This math checked out in the case when N was 1,400, or 23×52×71. For this value of N, N/4 was 350, or 21×52×71, which had 12 factors, or six factor pairs — the answer to the Express.
Anyway, no matter your approach, 1,400 was indeed a sextuply hip number.
Solution to last week’s Riddler Classic
Congratulations to 👏 Gary M. Gerken 👏 of Littleton, Colorado, winner of last week’s Riddler Classic.
Last week, I had 10 chocolates in a bag: Two were milk chocolate, while the other eight were dark chocolate. One at a time, I randomly pulled chocolates from the bag and ate them — that is, until I picked a chocolate of the other kind. When I got to the other type of chocolate, I put it back in the bag and started drawing again with the remaining chocolates. I kept going until I had eaten all 10 chocolates.
For example, if I first pulled out a dark chocolate, I ate it. (I always ate the first chocolate I pulled out.) If I pulled out a second dark chocolate, I ate that as well. If the third one was milk chocolate, I did not eat it (yet), and instead placed it back in the bag. Then I started again, eating the first chocolate I pulled out.
What were the chances that the last chocolate I ate was milk chocolate?
But before we get into any analytical solutions, let’s check in with our Monte Carlo-minded friends. Ian Greengross and Kyle Giddon both ran 1 million simulations of the problem, while Josh Silverman ran 10 million simulations. All three of them found the same result: In about half of the simulations, the last chocolate was milk chocolate. Could it be that the answer was simply… a half?
Yes! The answer was precisely a half. What follows is a proof of why this is true, based on the explanation of solver Guy D. Moore:
Suppose there are two chocolates in the bag: one dark and one milk. In this “base case,” they each have a 50 percent chance of being the last (i.e., the second) chocolate you’ll eat.
Next, we’ll take a mathematical leap of faith. Suppose we’ve proven — somehow — that there’s a 50 percent chance the last chocolate is either milk or dark chocolate whenever the total starting number of chocolates is less than some value N. What would happen if I now started with N chocolates?
Well, one of three things could happen. (Again, let’s suppose that d of these N chocolates are dark and m are milk. Note that this implies d+m = N, since every chocolate must be either dark or milk.)
I go on a “dark” streak and pick out all d dark chocolates first, which means the last chocolate I eat will be milk. This is one of the N choose d total ways to order the chocolates, so the probability this occurs is one divided by N choose d , which is d !( N − d )!/ N !, or d ! m !/ N !, since N − d equals m .
dark chocolates first, which means the last chocolate I eat will be milk. This is one of the choose total ways to order the chocolates, so the probability this occurs is one divided by choose , which is !( − )!/ !, or ! !/ !, since − equals . I go on a “milk” streak and pick out all m milk chocolates first, which means the last chocolate I eat will be dark. Again, this is one of the N choose d ways to order the chocolates, so the probability this occurs is also d ! m !/ N !.
milk chocolates first, which means the last chocolate I eat will be dark. Again, this is one of the choose ways to order the chocolates, so the probability this occurs is ! !/ !. I don’t go on either streak. I’ll eat some milk or dark chocolates until I pick out a chocolate of the other kind. At this point, I’m effectively starting over with a bag that has fewer than N chocolates. By my earlier leap of faith, I assumed the probability of now finishing with a milk chocolate was 50 percent.
So then what are the chances of finishing with a milk chocolate when there are N chocolates in the bag? It’s 50 percent! That’s because finishing with dark or milk is equally likely in the third case, and equally likely when you consider the first and second cases together.
Let’s take a final step back to get a bigger picture of what just happened. When there were two chocolates in the bag (one of each type), you had a 50 percent chance of finishing with a milk chocolate. We also showed that if there’s a 50 percent chance for fewer than N chocolates, there’s also a 50 percent chance for N chocolates. Since it was 50 percent when there were two chocolates, it must also be true when there were three. That means it must also be true when there were four. And five. And then six. And so on!
All of this amounts to a proof by induction: showing something is true for a “base case” (here, two), and then using an induction step to show it is true for all higher cases.
Indeed, this was a beautiful problem with an even more beautiful result. No matter how many chocolates of either type you started with — as long as you had at least one of each — the chances of finishing with either were precisely 50 percent.
In a neat little extension, solver Laurent Lessard proved that this was not the case when there were three types of chocolates. So it’s a good thing we left out the white chocolate. (That, and because it’s not even chocolate.)
Want more riddles?
Well, aren’t you lucky? There’s a whole book full of the best puzzles from this column and some never-before-seen head-scratchers. It’s called “The Riddler,” and it’s in stores now!
Want to submit a riddle?
Email Zach Wissner-Gross at riddlercolumn@gmail.com


fivethirthyeight--2020-10-09--Trump’s Bout With COVID-19 Might Be Hurting His Reelection Chances

Welcome to Pollapalooza , our weekly polling roundup .
It ’ s been exactly one week since we learned that President Trump had tested positive for COVID-19 .
While it ’ s still hard to know what effect his diagnosis has had on the race , we do have some new polls to share ; they don ’ t necessarily paint a consistent picture , though .
As my colleagues Geoffrey Skelley and Amelia Thomson-DeVeaux wrote on Monday , polls conducted in the immediate aftermath of Trump ’ s diagnosis found that an overwhelming majority of Americans believed that Trump @ @ @ @ @ @ @ avoid getting sick .
Newer polling agrees : For instance , CNN/SSRS found that 63 percent of Americans thought Trump acted irresponsibly in risking the health of the people around him .
However , it ’ s not clear that this affected people ’ s perceptions of whether Trump could continue to govern effectively .
Sixty-six percent of respondents in the poll said they weren ’ t concerned about the government ’ s ability to operate while Trump was ill .
There is some evidence , though , that Trump ’ s illness @ @ @ @ @ @ @ SurveyUSA was in the field with a national poll from Oct. 1 ( before Trump announced his diagnosis ) to Oct. 4 ( when Trump was in the hospital ) , and the pollster found that Joe Biden led Trump by just 4 points in interviews conducted before Trump was hospitalized .
But in interviews after Trump ’ s hospitalization , Biden led by 16 points .
A Franklin Pierce University/Boston Herald poll identified a similar pattern : Biden led by 5 points in interviews conducted before Trump ’ s diagnosis and by @ @ @ @ @ @ @ it .
But not every poll showed this shift .
Monmouth University , one of the best pollsters in the business , was also in the field with a Pennsylvania survey late last week , and it found that the horse race largely did not change after Trump ’ s diagnosis .
Biden led by 12 points in interviews on Sept. 30 and Oct. 1 and by 13 points in interviews from Oct. 2 to Oct. 4 .
Civiqs/Daily Kos , polling just after Trump ’ s diagnosis , asked a detailed question @ @ @ @ @ @ @ or in [ their ] daily life ” might affect people ’ s votes , but they found that essentially no one was changing their minds .
In addition , Skelley and Thomson-DeVeaux talked to multiple political scientists who said that attitudes on the coronavirus have hardened over the past several months , especially along party lines , so a big shift in public opinion is unlikely .
Not to mention , a solid majority of Americans already believed that Trump was mishandling the pandemic ; to them , his illness may merely @ @ @ @ @ @ @ believed , whereas Trump ’ s defenders may not be inclined to change their minds since he has downplayed his illness .
Indeed , our tracker of Trump ’ s approval rating on the coronavirus hasn ’ t budged since last week — and it is still heavily split by party .
But these surveys are far from the final word .
Trump ’ s illness is an incredibly fluid story , and public opinion may change if his condition worsens — or depending on the actions he takes now that he ’ @ @ @ @ @ @ @ week alone , he briefly left the hospital to wave to well-wishers from an enclosed car with Secret Service agents ; tweeted , “ Don ’ t be afraid of Covid ” ; returned to the White House after only three days of hospitalization ; and took his mask off before stepping inside .
And these actions were pretty unpopular .
For example , Americans told YouGov , 62 percent to 28 percent , that it was inappropriate for Trump to leave the hospital to wave to supporters .
And Morning Consult/Politico found @ @ @ @ @ @ @ Trump was wrong to tell Americans not to be afraid of COVID-19 , whereas only 28 percent said he was right .
Finally , by a 56 percent to 29 percent margin , Americans said it was a bad idea for him to discharge himself from the hospital and return to the White House , according to a separate YouGov poll .
Trump ’ s illness could also have a domino effect on the rest of the campaign .
For instance , it appears as though the next two debates will be delayed @ @ @ @ @ @ @ debate being held on Oct. 15 .
But according to Morning Consult/Politico , a virtual format is actually a fairly popular solution , at least when compared with the alternatives .
In a poll conducted before the announcement , 41 percent of voters thought the rest of the debates should be held virtually , versus only 12 percent who wanted the debates to be canceled or delayed .
Thirty-six percent of voters thought the debates should be held in person , either indoors ( 16 percent ) or out ( 20 percent ) @ @ @ @ @ @ @ s rollout of Amy Coney Barrett as his nominee for the Supreme Court has been pretty successful .
Despite people ’ s belief that the current Supreme Court vacancy should not be filled before the election , registered voters told YouGov/HuffPost , 43 percent to 38 percent , that they would like their senators to vote in favor of Barrett .
And respondents approved of Trump ’ s decision to appoint Barrett , 47 percent to 42 percent .
Similarly , Morning Consult/Politico found 46 percent of voters in favor of confirming Barrett @ @ @ @ @ @ @ And in a shift from late September , a plurality of voters now say Barrett should be confirmed as soon as possible .
• On Tuesday , Trump announced that he was cutting off negotiations over a new coronavirus relief bill and that nothing would be passed before the election .
But Morning Consult/Politico finds that this tactic could play poorly with the American public .
Sixty-eight percent of registered voters said “ stimulating the economy to recover from COVID-19 ” should be a top priority for Congress .
Thirty-two percent of respondents @ @ @ @ @ @ @ , and another 23 percent blamed Republicans in Congress ; 35 percent , however , blamed congressional Democrats .
• A new University of North Florida poll finds a close race for Florida ’ s Amendment 3 , which would implement a top-two primary system ( similar to California ’ s and Washington ’ s ) in the Sunshine State .
Likely voters said 58 percent to 36 percent that they would vote for the amendment , but it requires 60 percent in order to pass .
• The pandemic could make for @ @ @ @ @ @ @ a Leger poll , only 54 percent of Americans whose children went trick-or-treating last year said they would allow their kids to go door to door this year .
Meanwhile , 43 percent of Americans said that governments should proactively cancel Halloween this year .
• Now this is a good icebreaker question for parties : On Monday , YouGov asked Americans , “ How many enemies , if any , do you have ?
” Forty-four percent of respondents said they had no enemies , 5 percent said they had one enemy @ @ @ @ @ @ @ or three and 2 percent said they had four or five .
A concerning 4 percent of Americans said they have five or more enemies .
The remaining 36 percent were like , “ WTF , YouGov ?
” ( read : they said they didn ’ t know ) .
According to FiveThirtyEight ’ s presidential approval tracker , 43.2 percent of Americans approve of the job Trump is doing as president , while 53.4 percent disapprove ( a net approval rating of -10.2 points ) .
At this time last week @ @ @ @ @ @ @ disapproved ( a net approval rating of -8.9 points ) .
One month ago , Trump had an approval rating of 43.1 percent and a disapproval rating of 52.7 percent , for a net approval rating of -9.6 points .
In our average of polls of the generic congressional ballot , Democrats currently lead by 6.5 percentage points ( 49.3 percent to 42.8 percent ) .
A week ago , Democrats led Republicans by 6.1 points ( 48.8 percent to 42.7 percent ) .
At this time last month , voters preferred Democrats @ @ @ @ @ @ @ 41.4 percent ) .
Check out all the polls we ’ ve been collecting ahead of the 2020 elections .

Welcome to Pollapalooza, our weekly polling roundup.
Poll(s) of the week
It’s been exactly one week since we learned that President Trump had tested positive for COVID-19. While it’s still hard to know what effect his diagnosis has had on the race, we do have some new polls to share; they don’t necessarily paint a consistent picture, though.
As my colleagues Geoffrey Skelley and Amelia Thomson-DeVeaux wrote on Monday, polls conducted in the immediate aftermath of Trump’s diagnosis found that an overwhelming majority of Americans believed that Trump did not take the proper precautions to avoid getting sick. Newer polling agrees: For instance, CNN/SSRS found that 63 percent of Americans thought Trump acted irresponsibly in risking the health of the people around him. However, it’s not clear that this affected people’s perceptions of whether Trump could continue to govern effectively. Sixty-six percent of respondents in the poll said they weren’t concerned about the government’s ability to operate while Trump was ill.
There is some evidence, though, that Trump’s illness may be hurting his reelection chances. SurveyUSA was in the field with a national poll from Oct. 1 (before Trump announced his diagnosis) to Oct. 4 (when Trump was in the hospital), and the pollster found that Joe Biden led Trump by just 4 points in interviews conducted before Trump was hospitalized. But in interviews after Trump’s hospitalization, Biden led by 16 points. A Franklin Pierce University/Boston Herald poll identified a similar pattern: Biden led by 5 points in interviews conducted before Trump’s diagnosis and by a shocking 21 points in interviews after it.
But not every poll showed this shift. Monmouth University, one of the best pollsters in the business, was also in the field with a Pennsylvania survey late last week, and it found that the horse race largely did not change after Trump’s diagnosis. Biden led by 12 points in interviews on Sept. 30 and Oct. 1 and by 13 points in interviews from Oct. 2 to Oct. 4. Civiqs/Daily Kos, polling just after Trump’s diagnosis, asked a detailed question about how “anything in the news or in [their] daily life” might affect people’s votes, but they found that essentially no one was changing their minds.
Recent events are not changing people’s minds Share of adults in a national Oct. 2-5 Civiqs/Daily Kos poll who gave each answer to the question, “A lot has happened in the past few weeks. Thinking back, has anything in the news or in your daily life affected how you plan to vote in the presidential election?” Response Share I was going to vote for Biden, and I still am 46% I was going to vote for Trump, and I still am 40 I was going to vote for Biden, but I am reconsidering 1 I was going to vote for Trump, but I am reconsidering 1 I was going to vote for Biden, but I have changed my mind 1 I was going to vote for Trump, but I have changed my mind 1 I already voted 4 I am not going to vote 1 Unsure 5 Source: Civiqs/Daily Kos
In addition, Skelley and Thomson-DeVeaux talked to multiple political scientists who said that attitudes on the coronavirus have hardened over the past several months, especially along party lines, so a big shift in public opinion is unlikely. Not to mention, a solid majority of Americans already believed that Trump was mishandling the pandemic; to them, his illness may merely serve as confirmation of what they already believed, whereas Trump’s defenders may not be inclined to change their minds since he has downplayed his illness. Indeed, our tracker of Trump’s approval rating on the coronavirus hasn’t budged since last week — and it is still heavily split by party.
But these surveys are far from the final word. Trump’s illness is an incredibly fluid story, and public opinion may change if his condition worsens — or depending on the actions he takes now that he’s sick.
For instance, this week alone, he briefly left the hospital to wave to well-wishers from an enclosed car with Secret Service agents; tweeted, “Don’t be afraid of Covid”; returned to the White House after only three days of hospitalization; and took his mask off before stepping inside. And these actions were pretty unpopular. For example, Americans told YouGov, 62 percent to 28 percent, that it was inappropriate for Trump to leave the hospital to wave to supporters. And Morning Consult/Politico found that 60 percent of registered voters said Trump was wrong to tell Americans not to be afraid of COVID-19, whereas only 28 percent said he was right. Finally, by a 56 percent to 29 percent margin, Americans said it was a bad idea for him to discharge himself from the hospital and return to the White House, according to a separate YouGov poll.
Trump’s illness could also have a domino effect on the rest of the campaign. For instance, it appears as though the next two debates will be delayed by a week instead of a virtual debate being held on Oct. 15. But according to Morning Consult/Politico, a virtual format is actually a fairly popular solution, at least when compared with the alternatives. In a poll conducted before the announcement, 41 percent of voters thought the rest of the debates should be held virtually, versus only 12 percent who wanted the debates to be canceled or delayed. Thirty-six percent of voters thought the debates should be held in person, either indoors (16 percent) or out (20 percent).
Other polling bites
It looks like Trump’s rollout of Amy Coney Barrett as his nominee for the Supreme Court has been pretty successful. Despite people’s belief that the current Supreme Court vacancy should not be filled before the election, registered voters told YouGov/HuffPost, 43 percent to 38 percent, that they would like their senators to vote in favor of Barrett. And respondents approved of Trump’s decision to appoint Barrett, 47 percent to 42 percent. Similarly, Morning Consult/Politico found 46 percent of voters in favor of confirming Barrett, with only 31 percent opposed. And in a shift from late September, a plurality of voters now say Barrett should be confirmed as soon as possible.
On Tuesday, Trump announced that he was cutting off negotiations over a new coronavirus relief bill and that nothing would be passed before the election. But Morning Consult/Politico finds that this tactic could play poorly with the American public. Sixty-eight percent of registered voters said “stimulating the economy to recover from COVID-19” should be a top priority for Congress. Thirty-two percent of respondents blamed Trump for the breakdown in negotiations, and another 23 percent blamed Republicans in Congress; 35 percent, however, blamed congressional Democrats.
A new University of North Florida poll finds a close race for Florida’s Amendment 3, which would implement a top-two primary system (similar to California’s and Washington’s) in the Sunshine State. Likely voters said 58 percent to 36 percent that they would vote for the amendment, but it requires 60 percent in order to pass.
The pandemic could make for an eerily quiet Halloween. According to a Leger poll, only 54 percent of Americans whose children went trick-or-treating last year said they would allow their kids to go door to door this year. Meanwhile, 43 percent of Americans said that governments should proactively cancel Halloween this year.
Now this is a good icebreaker question for parties: On Monday, YouGov asked Americans, “How many enemies, if any, do you have?” Forty-four percent of respondents said they had no enemies, 5 percent said they had one enemy, 8 percent said they had two or three and 2 percent said they had four or five. A concerning 4 percent of Americans said they have five or more enemies. The remaining 36 percent were like, “WTF, YouGov?” (read: they said they didn’t know).
Trump approval
According to FiveThirtyEight’s presidential approval tracker, 43.2 percent of Americans approve of the job Trump is doing as president, while 53.4 percent disapprove (a net approval rating of -10.2 points). At this time last week, 43.9 percent approved and 52.8 percent disapproved (a net approval rating of -8.9 points). One month ago, Trump had an approval rating of 43.1 percent and a disapproval rating of 52.7 percent, for a net approval rating of -9.6 points.
Generic ballot
In our average of polls of the generic congressional ballot, Democrats currently lead by 6.5 percentage points (49.3 percent to 42.8 percent). A week ago, Democrats led Republicans by 6.1 points (48.8 percent to 42.7 percent). At this time last month, voters preferred Democrats by 7.2 points (48.7 percent to 41.4 percent).
Check out all the polls we’ve been collecting ahead of the 2020 elections.