The game was over. Babe, who had made one of his famous drives that day, was tired and wanted to go home. “Not tonight, Babe,” I said. “Tonight you go to college with me. You're going to take scientific tests which will reveal your secret.”

“Who wants to know it?” asked Babe.

“I want to know it,” I replied, “and so do several hundred thousand fans. We want to know why it is that one man has achieved a unique batting skill like yours—just why you can slam the ball as nobody else in the world can.”

So away we went. Babe in his baseball uniform, not home to his armchair, but out to Columbia University to take his first college examination.

Babe went at the test with the zeal of a schoolboy, and the tests revealed why his rise to fame followed suddenly after years of playing during which he was known as an erratic although a powerful hitter. How he abruptly gained his unparalleled skill has been one of baseball's mysteries.

Albert Johanson, M.A., and Joseph Holmes, M.A., of the research laboratory of Columbia University's psychological department, who, in all probability, never saw Ruth hit a baseball, and who neither know or care if his batting average is .007 or .450, are .500 hitters in the psychology game. They led Babe Ruth into the great laboratory of the university, figuratively took him apart, watched the wheels go round; analyzed his brain, his eye, his ear, his muscles; studied how these worked together; reassembled him, and announced the exact reasons for his supremacy as a batter and a ball-player.

Baseball employs scores of scouts to explore the country and discover baseball talent. These scouts are known as “Ivory hunters,” and if baseball-club owners take the hint from the Ruth experiments, they can organize a clinic, submit candidates to the comprehensive tests undergone by Ruth, and discover whether or not other Ruths exist. By these tests it would be possible for the club owners to discover—during the winter, perhaps—whether the ball-players are liable to be good, bad, or mediocre; and, to carry the practical results of the experiments to the limit, then may be able to eliminate the possibility, or probability, of some player “pulling a boner” in mid-season by discovering, before the season starts, how liable he is to do so.

The scientific ivory hunters of Columbia University discovered that the secret of Babe Ruth’s batting, reduced to non-scientific terms, is that his eyes and ears function more rapidly than those of other players; that his brain records sensations more quickly and transmits its orders to the muscles much faster than does that of the average man. The tests proved that the coordination of eye, brain, nerve system, and muscle is practically perfect, and that the reason he did not acquire his great batting power before the sudden burst at the beginning of the baseball season of 1920, was because, prior to that time, pitching and studying batters disturbed his almost perfect coordination.

Ruth the superman

The tests revealed the fact that Ruth is 90 per cent efficient compared with a human average of 60 per cent.

That his eyes are about 12 per cent faster than those of the average human being.

That his ears function at least 10 per cent faster than those of the ordinary man. That his nerves are steadier than those of 499 out of 500 persons.

That in attention and quickness of perception he rated one and a half times above the human average.

That in intelligence, as demonstrated by the quickness and accuracy of understanding, he is approximately 10 per cent above normal.

It must not be forgotten that the night on which the tests were made was an extremely warm one, and that in the afternoon he had played a hard, exhausting game of baseball before a large crowd, in the course of which he had made one of those home-run hits which we at Columbia were so eager to understand and account for. Under such circumstances, one would think that some signs of nerve exhaustion would be revealed. The instigation lasted more than three hours, during which Ruth stood for most of the time, walked up and down stairs five times, and underwent the tests in a close warm room. At the end of that time I was tired and nervous, and, although Ruth showed no symptoms of weariness, it is probable that under more favorable conditions his showing would have been even better.

The tests used were ones that primarily test motor functions and give a measure of the integrity of the psychophysical organism. Babe Ruth was posed first in an apparatus created to determine the strength, quickness, and approximate power of the swing of his bat against his ball. A plane covered with electrically charges wires, strung horizontally, was placed behind him and a ball was hung over the theoretical plate, so that it could be suspended at any desired height.

I learned something then which, perhaps, will interest the American League pitchers more than it will the scientists. This was that the ball Ruth likes best to hit, and can hit hardest, is a low ball pitched just above his knees on the outside corner of the plate. The scientists did not consider this of extreme importance in their calculations, but the pitchers will probably find it of great scientific interest.

Science discovers the secret

The ball was adjusted at the right height, and, taking up a bat that was electrically wired, Ruth was told to get into position and to swing his bat exactly as if striking the ball for a home run, to make the end of it touch one of the transverse wires on the plate behind him, then swing it through its natural arc and hit the ball lightly. The bat, weighing fifty-four ounces (exactly the weight of the bats Ruth uses on the diamond), was swung as directed, touched the ball, and the secret of his power—or, rather, the amount of force with which the strikes the ball—was calculated. At least, the basis of the problem was secured: The bat, weighing fifty-four ounces, swinging at a rate of 110 feet a second, hits a ball travelling at the rate of, say, sixty feet a second, the ball weighing four and a quarter ounces, and striking the bat at a point four inches from the end. How far will it travel? 

There are other elements entering into the problem, such as the resilience of the ball, the “English” placed on it by the pitcher’s hand, and a few minor details. But the answer, as proved by the measurements, is somewhere between 450 and 500 feet. This problem cannot be worked down to exact figures because of the unknown quantities.

The experimenters, however, were not so much interested in the problem in physics as they were in the problems in psychology. The thing they wanted to know was what made Ruth superior to all other ball-players in hitting power, rather than to measure that power.

Babe could beat his own record!

Before proceeding to the psychological tests, however, we tried another in physics to satisfy my curiosity. A harness composed of rubber tubing was strapped around Ruth's chest and shoulders and attached by hollow tubes to a recording cylinder. By this means his breathing was recorded on a revolving disk. He was then placed in position to bat, an imaginary pitcher pitched an imaginary ball, and he went through the motions of hitting a home run. The test proved that, as a ball is pitched to him, Babe draws in his breath sharply as he makes the back-swing with his bat, and really “holds his breath” or suspends the operation of his breathing until after the ball is hit. But for that fact, he would hit the ball much harder and more effectively than he now does. It has been discovered that the act of drawing in the breath and holding it results in a sharp tension of the muscles and a consequent loss of striking power. If Ruth expelled his breath before striking the ball, the muscles would not become tense and his swing would have greater strength and rhythm.

The first test to discover the efficiency of his psychophysical organism was one designed to try his coordination; a simple little test. The scientists set up a triangular board, looking some thing like a ouija-board, with a small round hole at each angle. At the bottom of each hole was an electrified plate that registered every time it was touched. Ruth was presented with a little instrument that looked like a doll-sized curling iron, the end of which just fitted into the holes. Then he was told to take the instrument in his right hand and jab it into the holes successively, as often as he could in one minute, going around the board from left to right.

He grew interested at once. Here was something at which he could play. The professor “shushed” me, fearing that I would disturb Ruth or distract his attention as he started around the board, jabbing the curling-iron into the holes with great rapidity. He would put it into the holes twelve to sixteen times so perfectly that the instrument barely touched the sides. Then he would lose control and touch the sides, slowing down. Only twice did he pass the hole without getting the end of the iron into it. With his right hand he made a score of 122. Not unnaturally, his wrist was tired and Babe shook it and grinned ruefully.

Then he tried it with his left hand, scored 132 with it, proving himself a bit more left- than right-handed—at least in some activities. The significance of the experiment, however, lies in the fact that the average of hundreds of persons who have taken that test is 82 to the minute, which shows how much swifter in the coordination of hand, brain, and eye Ruth is than the average.

Every test but another triumph

In a sequel to this test that followed, Babe tapped an electrified plate with an electrically charged stylus with the speed of a drum-roll, scoring 193 taps per minute with his right hand and 176 with his left hand. The average score for right-handed persons undergoing this wrist-wracking experiment is 180, and, while there is no data covering right-handed persons using the left hand, it is certain that Ruth's record is much above the average, as he is highly efficient with the left hand.

But steadiness must accompany speed and so they tested the home-run king for his steadiness of nerve and muscle by having him thrust the useful little curling-iron stylus in different-sized holes pierced through an electrified plate which registered contacts between the stylus and the side of the hole. These measured respectively sixteen, eleven, nine, eight, and seven sixty-fourths of an inch; small enough, but not too small for Babe, for he made a score that showed him better than 499 persons out of 500.

The tests that interested me most were those to determine how quickly Ruth’s eye acts and how quickly its signals are flashed through the brain to the muscles. Showing an amazingly quick reaction time, they interpreted what happens on the ball-field when the stands rock under the cheering that greets another of Ruth's smashes to the fence, proved an eye so quick that it sees the ball make an erratic curve and guides the bat to follow.

The scientists discovered exactly how quickly Ruth’s eye functions by placing him in a dark cabinet, setting into operation a series of rapidly flashing bulbs and listening to the tick of an electric key by which he acknowledged the flashes.

The average man responds to the stimulus of the light in 180 one thousandths of a second. Babe Ruth needs only 160 one thousandths of a second. There is the same significance in the fact that Babe's response to the stimulus of sound comes 140 one thousandths of a second as against the averages man's 150 thousandths.

Human beings differ very slightly in these sight and sound tests, or rather the fractions are so small that they seem inexpressive; yet a difference of 20 or 10 one thousandths of a second indicates a superiority of the highest importance.

Translate the findings of the sight test into baseball if you want to see what they mean in Babe Ruth’s case. 

They mean that a pitcher must throw a ball 20 one thousandths of a second faster to “fool” Babe than to “fool” the average person.

If the results of these tests at Columbia are a revelation to us, who know Ruth as a fast thinking player, they must be infinitely more amazing to the person who only comes into contact with the big fellow off the diamond and finds him unresponsive and even slow when some non-professional topic in under discussion.

The scientific “ivory hunters” up at Columbia demonstrated that Babe Ruth would have been the “home-run king” in almost any line of activity he chose to follow; that his brain would have won equal success for him had he drilled it for as long a time on some line entirely foreign to the national game. They did it, just as they proved his speed and his steadiness—by simple laboratory tests.

For instance, they had an apparatus with a sort of a camera shutter arrangement that opened, winked, and closed at any desired speed. Cards with letters of the alphabet on them were placed behind this shutter and exposed to view for one fifty-thousandth of a second. Ruth read them as they flashed into view, calling almost instantly the units of groups of three, four, five, and six letters. With eight shown he got the first six, and was uncertain of the others. The average person can see four and one half letters on the same test.

When cards marked with black dots were used, Ruth was even faster. He called up the number of dots on every card up to twelve without one mistake, The average person can see eight.

To test him for quickness of perception and understanding, he was given a card showing five different symbols—a star, a cross, and three other shapes—many times repeated, and was told to select a number—one, two, three, four, or five—for each symbol, then to mark the selected number under each one as rapidly as he could go over the card. He scored 103 hits on that test, which his the average of all who have tried it. But when given a card covered with printed matter and told to cross out all the a's, he made a score of sixty, which is one and a half times the average.

The secret of Babe Ruth’s ability to hit is clearly revealed in these tests. His eye, his ear, his brain, his nerves all function more rapidly than do those of the average person. Further the coordination between eye, ear, brain, and muscle is much nearer perfection than that of the normal healthy man.

The scientific “ivory hunters” dissecting the “home-run king” discovered brain instead of bone, and showed how little mere luck, or even mere hitting strength, has to do with Ruth's phenomenal record.

Reprinted from: Fullerton, H. S. (1921). Why Babe Ruth is Greatest Home­ Run Hitter. Popular Science Monthly, 99(4), 19-21, 110. Now in the public domain. (Source 1, Source 2)

Bonus fact one: The term "inside baseball" originated from the home run debate sparked by players like Babe Ruth. “The original meaning appears to have referred to a particular style of play which relied on bunts, stealing bases, and minor hits, rather than on flashier tactics, such as home runs," according to Merriam Webster, before evolving to mean "minutiae or things about which only a few insiders care."

Bonus fact two: In a 2006 feature for GQ investigating the science of hitting a baseball, journalist Nate Penn, inspired by the Ruth experiments, brought MLB-great Albert Pujols into the psychology lab to participate in similar tests.

Acknowledgements: Thank you to Alfred Fuchs for unearthing the experiments in his 1998 article in the Journal of the History of the Behavioral Sciences; Christopher D. Green, who has developed a terrific archive of the classics in the history of psychology; and to the Cummings Center for the History of Psychology at the University of Akron for the original cover image.

The post The Psychology of the Home Run in 1921 appeared first on Behavioral Scientist.

Grinding through 16-hour shifts, standing behind inmates (never in front), and trying to stay human in an inhuman environment with Bill Farrell, a correctional officer in Massachusetts. What happens when an officer gets "frozen"? And why does the sound of scuffling sneakers stop him in his tracks?

[buzzsprout episode='19183441' player='true']

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About What It's Like to Be...
In each episode of What It's Like to Be..., bestselling author Dan Heath speaks with someone about what it's like to walk in their (work) shoes. Behavioral Scientist serves as a distribution partner with episodes released every other week. Learn more about the podcast's mission of "slow curiosity" here, and head here to get Dan's reflections on how the mission is going after a year of conversations.

The “Correctional Officer” episode of What It’s Like To Be… featured Bill Farrell. It was produced and edited by Matt Purdy. Copyright © 2026 by Dan Heath. All rights reserved.

The post What It’s Like to Be…a Correctional Officer appeared first on Behavioral Scientist.

A man was arrested for entering a New York subway station through an emergency gate without paying the fare. When police patted him down, they found he was illegally carrying a loaded gun. When another man was arrested for fare evasion at a different stop, police found he was carrying 38 decks of heroin and a loaded gun that had been reported as stolen. Yet another was arrested for not paying the subway fare in another part of the city, and it turned out he was carrying a gun, ammunition, and crack cocaine. New York police argue that enforcing a seemingly minor offense (fare evasion) helps them catch people like these who are up to no good—perhaps preventing violent crime.

And yet, how to handle such offenses has been hotly debated for decades. Some worry that allowing arrests will result in violent confrontations or jail time for people already struggling to make ends meet. For what, a $2.90 subway ticket? While some of those arrested for fare evasion will have a track record of crime, for many others this would be their first arrest. Is a criminal charge really our best option?

In 2023, the board of directors of BART—Bay Area Regional Transit, the San Francisco subway agency—voted to oppose a bill moving through the California legislature that would decriminalize fare evasion. “The public is speaking very loud to us right now—and they have been—about the lack of enforcement of rules in our system,” said BART board member Debora Allen. Local residents were worried about safety on the subway system, with stories about violent crime at the top of everyone’s minds. “I can’t help but say we could help prevent some of the bad behavior in our system by getting tougher on fare evasion.” Daly City resident Howard Bernstein agreed that such a move would only embolden offenders: “The more we decriminalize criminal behavior, the more criminal behavior we’re going to experience.”

A few years earlier, in 2017, Manhattan district attorney Cy Vance Jr. made headlines when he announced he would no longer prosecute fare evasion cases. “Prosecuting for turnstile jumping is counter to this city’s efforts to be a sanctuary,” Anthony Posada of Legal Aid NYC told reporters at the time. The move was generally motivated by a recognition that fare evasion was a crime often committed due to poverty. Clearly, pressing criminal charges in such situations would not address the problem—that the person had no money—and risked making the problem worse. But in 2023, the debate raged on. The New York Times journalist Ana Ley reported that the Metropolitan Transportation Authority (MTA) had lost $690 million to fare evasion the previous year. Turnstile hoppers were apparently undeterred by tickets written by the police hovering nearby, and seeing some people ride without paying made others feel like suckers for buying a ticket. A year later, Ley followed up with an equally dire statistic: 48 percent of bus riders in the city did not pay the required fare. (The number for subway riders was 14 percent.) “If the transit system does not work and nobody plays by the rules, it feels lawless. It is lawless,” said Janno Lieber, chief executive of the MTA. “This is really tearing at the social compact of New York.”

Current debates about how to handle low-level nonviolent crimes are reminiscent of those from thirty years ago. In 1993, Rudy Giuliani was elected mayor of New York City. He came to office promising to make the city safer, and quickly adopted a strategy that had previously been discussed only in academic circles: “broken windows” policing. The idea underlying this approach was that disorder begets disorder. By addressing low-level offending—trespassing, vandalism, prostitution, urinating in public—police could deter more serious offenses. People would know that police were paying attention and that the community was well cared for, and so they would behave better. Fix the broken windows, and arrest the guy who broke them, and you’ll prevent violent crime as well.

Crime fell dramatically in New York City during the 1990s, and Giuliani claimed victory. In his farewell address in 2001, he credited this strategy—cracking down on low-level offenders as a way to prevent crime from escalating—as the key to his success. “The broken windows theory replaced the idea that we were too busy to pay attention to street-level prostitution, too busy to pay attention to panhandling, too busy to pay attention to graffiti. Well, you can’t be too busy to pay attention to those things, because those are the things that underlie the problems of crime that you have in your society.”

Since then, it’s become less clear how helpful that strategy really was. Crime fell dramatically throughout the US in the 1990s and early 2000s, not just in New York City. And yet this theory is still appealing to voters, and still motivates the policies of many police departments and prosecutors’ offices. Fast-forward to the present, when many cities are struggling with persistent and increasingly brazen public drug use, homeless encampments, vandalism, petty theft, and, yes, turnstile hopping. More serious crime, including organized retail theft rings, carjackings, and even homicide, also became serious problems in many cities—a shock after decades of declining crime rates. In 2022, the San Francisco resident and political commentator Richie Greenberg described what he saw as a turn toward lawlessness, to The Atlantic’s Annie Lowery. “People are sick and tired of the whole atmosphere of the city. It’s not fun to live here anymore,” he lamented.

The past several years have prompted calls to return to a Giuliani-style zero-tolerance approach to disorder, with stiff penalties for even the most minor offenses. Today, when I speak with policy stakeholders across the United States, I’m frequently asked if a broken windows approach could be the solution to their problems. Could a tougher approach to minor offenses be the key to reducing more serious crime?

Many voters have decided it’s at least worth trying—again—and not just in the subway. In 2023, police in San Francisco began cracking down on public drug use, arresting more than seventeen hundred people between May and December. “You’ll never hear me say that arresting folks will solve addiction, but these are still crimes,” Police Chief Bill Scott told The San Francisco Standard. San Francisco sheriff Paul Miyamoto saw punishment as a compassionate incentive for people to get the help they need: “Justice-involved persons with substance use disorder sometimes need the threat of jail time to compel them to remain in programs that successfully address the root causes of addiction,” he said, explaining the city’s efforts to dismantle open-air drug markets. In Philadelphia’s Kensington neighborhood, police crackdowns targeted public drug use as well as other minor offenses and quality-of-life issues—they shooed away people who were loitering, towed unregistered cars, and cleaned vacant lots. “The neighbors really didn’t complain,” Deputy Commissioner Pedro Rosario responded when asked about community pushback. “They were happy. They were thumbs-upping me a lot.”

There is at least a kernel of wisdom in this approach. We know that people respond to incentives, and swift and certain punishment for bad behavior deters future offending. That is important, and to the extent that broken windows means making consequences more likely, it could indeed reduce crime and put people on a better path. But increasing the probability of punishment is different from making the punishment harsher. Many proponents of the broken windows approach don’t simply want to arrest people for their bad behavior, they want to throw the book at them. (Because of this, broken windows, as a philosophy, extends beyond what police do and into the courtroom, where prosecutors and judges decide the consequence for an offense.) It’s not clear that harsher punishment would be productive. On top of that, it’s possible that prosecuting and punishing low-level offenders has other, detrimental effects that cancel out any benefits we get from deterrence—especially if it’s someone’s first brush with the law.

For instance, a criminal record makes it more difficult to find a job, and it means you might lose the job you had before your conviction. This creates economic hardship that can make criminal behavior more likely, as a way to make ends meet. A criminal record also makes it more difficult to find housing, as most landlords run background checks just like employers do. Without a safe place to live, you might find yourself in more dangerous situations, with less to lose, and more vulnerable to future charges for offenses such as trespassing when you have nowhere else to go. To the extent that your previous offenses were the result of untreated mental illness or substance use, the stress of criminal charges and any punishment could make those problems worse.

How much do all these factors matter in practice? Would reducing the consequences for low-level offenses be helpful? Those who say no—like proponents of broken windows policing—think the threat of harsh punishment has a big deterrent effect. But others say yes. Reform-minded prosecutors, elected in many cities over the past decade, have promised to go easier on minor offenses so that they can focus more attention on violent crimes. In 2019, Wesley Bell, the prosecuting attorney in St. Louis County, Missouri, told NBC News that diverting nonviolent offenders from jail to rehabilitative programming “not only brings our crime rates down, but most importantly, it helps people and families.” Still others believe that the challenges faced by those who commit low-level crimes—poverty, limited education, untreated mental illness—are so large that only a massive reform of our social safety net will keep people from cycling back through the criminal justice system. Who’s right?

* * *

Prosecution in Suffolk County

With such diverging opinions on what to do with people arrested for low-level offenses, figuring out the best path forward requires turning to data. I teamed up with the economist Amanda Agan, now at Cornell University, and political scientist Anna Harvey, from New York University, to study this issue. We wanted to know what effect the decision to prosecute someone for a nonviolent misdemeanor—minor offenses like trespassing, shoplifting, and minor drug possession—would have on a defendant’s future criminal justice involvement. Would cracking down on that low-level offense reduce their likelihood of reoffending (as broken windows proponents expect) or increase it (as reform prosecutors argue)?

We managed to get data from the District Attorney’s Office in Suffolk County, Massachusetts, where Boston is located. The DA there at the time, Rachael Rollins, also wanted to know the answer to this question, and so enthusiastically handed over her office’s data, no strings attached. This is a researcher’s dream. Many policymakers are hesitant to share data when they can’t control the results of the study, and can’t block unfavorable results from being published. But such restrictions are a nonstarter for researchers like us. Luckily, then-DA Rollins was on board with our scientific approach and wanted to follow the evidence. She understood that this was the best way to figure out how to improve public safety—and perhaps end this long-standing debate. 

In Suffolk County, once police make an arrest or issue a summons, and then determine that probable cause exists for the charge, the case goes to an arraignment hearing. In that hearing, an assistant district attorney (ADA) representing the government decides whether to pursue the charges or dismiss the case. They are essentially deciding whether they think the case is a good use of prosecutors’ time. This is the decision we were interested in. What if more cases were dismissed up front? Would that lead to more recidivism, or less?

What if more cases were dismissed up front? Would that lead to more recidivism, or less?

Simply comparing people who were prosecuted with those who were not wouldn’t answer this question, because prosecutors intentionally choose whom to prosecute. If we found that those who were prosecuted were more likely to reoffend in the future, we wouldn’t know if this was the effect of the prosecution decision, or because prosecutors only move forward with cases against higher-risk defendants. Prosecution might be correlated with recidivism, but that doesn’t necessarily mean prosecution causes recidivism.

So once we had the data, it was time to hunt for natural experiments that would allow us to distinguish correlation from causation. The ideal experiment in this context would randomly assign some defendants to be prosecuted and others not. We could then attribute any differences in future behavior across these two groups to the effect of being prosecuted, without worrying there are other underlying differences between them that explain their differences in behavior.

Of course, no one would agree to prosecute cases at random (nor should they). But it turns out that the way nonviolent misdemeanor cases are assigned to ADAs mimics this ideal experiment.

What determines which ADA handles each case? Handling arraignments is the “grunt work” of the prosecutors’ office. (The more interesting work comes later in the case proceedings.) So everyone takes a turn, especially junior ADAs who haven’t specialized yet.

ADAs are assigned to the arraignment courtroom in an ad hoc way that changes week to week, depending on their other meetings and case schedules. This Monday, Tom might be assigned to handle arraignments, but next Monday, Anne might be assigned to that task. This assignment schedule is unrelated to the types of cases expected on that day—this is the key. Because of this, we don’t need to worry that ADAs are selected to handle particular cases on account of their expertise or preferences—at least for the nonviolent misdemeanor cases we are interested in. (They might pull someone with more expertise in for more serious offenses.)

It’s important to understand the huge volume of these cases that go through the courts in any given week—misdemeanors make up 70 to 80 percent of all cases. For these very minor offenses, ADAs have just a few moments to decide whether to proceed with a case or drop it. The goal is to keep the cases moving; this is the only way the courts don’t become completely overwhelmed by minor charges and grind to a halt.

Because everything moves so quickly, and because ADAs’ schedules are so unpredictable, it is not possible for defendants to game the system to get a particular ADA. When their case is at the top of the pile on the ADA’s desk, it’s their turn. They get what they get.

This all means that which ADA handles a particular case is effectively random—there is no correlation between case characteristics and the characteristics or relative harshness of the ADA.

Human discretion as a natural experiment

So we have randomization of ADAs, but this doesn’t help if all ADAs behave the same way. What we also need from this natural experiment is randomness in the decision to prosecute.

This is where we could rely on human nature, and a fact that we see in every domain where humans make decisions: People have different preferences, and so they will use any discretion they have in different ways. And prosecutors have a lot of discretion. In this context, this means that two different prosecutors considering identical cases might make completely different decisions. One might drop the case immediately, while the other might choose to move the case forward with the goal of conviction and punishment.

This probably sounds extremely unfair. Shouldn’t identical cases get the same outcome regardless of who the prosecutor is? That is certainly the ideal, but in contexts like this, there is no right answer about what should happen in a case. We count on human decision-makers to use their best judgment. This leads to differences in outcomes that we’d rather not have. 

In the U.S., we tend to swing back and forth between limiting the discretion of criminal justice actors like prosecutors and judges and giving them more discretion. We hear about big differences in outcomes across similar cases—for instance, Black defendants receiving harsher sentences than similar white defendants—and we demand restrictions on discretion. This is part of the reason for policies like sentencing guidelines and mandatory minimum sentences. These tie the hands of prosecutors and judges, at least on some dimensions.

Having your case dismissed rather than pursuing prosecution—reduced the likelihood of showing up in court again with new charges by 53 percent, and it reduced the number of future charges by 60 percent.

But then we hear about a case that, based on these standardized rules, resulted in an outcome that seems totally unfair given some extenuating circumstances, and we demand that decision-makers have more discretion to deviate from those rules when it is warranted. We want them to use their judgment to provide the best outcome. And then when they do, we wind up with different outcomes across similar cases, and we swing back toward wanting less discretion.

What we want is for prosecutors and judges to use their discretion only for good—to reach the decision we think is most appropriate. But the problem is that different people disagree about what is appropriate. Allowing people to use their best judgment has trade-offs, and we have to take the bad with the good.

One silver lining to this complicated dilemma is that human discretion creates great settings for research. In Suffolk County, random assignment of cases across ADAs meant that we effectively had random assignment of cases to different treatments—the ideal experiment we’d hoped for. Some defendants get lucky and their case is handled by a lenient ADA; because of this, they are more likely to have their case dismissed outright. Other defendants are unlucky and their case is handled by a harsh ADA; their case is more likely to move forward to the next stage. Through the luck of the draw—which ADA happened to be in that courtroom that day—we have identical cases that are treated in different ways.

What happened to those lucky defendants whose cases were dropped because they happened to be in the right courtroom at the right time with a lenient ADA? Proponents of broken-windows-style punishment as a deterrent would predict that those defendants would be emboldened. Facing little consequence for their actions the first time, they’d realize the costs of bad behavior were low and commit even more crime in the future.

But that’s not what the data showed. It turns out that leniency at this early stage—having your case dismissed rather than pursuing prosecution—reduced the likelihood of showing up in court again with new charges by 53 percent, and it reduced the number of future charges by 60 percent. The effects were larger for first-time defendants—those with no prior arrest or conviction on their record.

* * *

The power of leniency

David Eil is an assistant public defender in Mecklenburg County, North Carolina, where Charlotte is located. He has seen firsthand the damage that a first conviction can do. And—unlike most lawyers—he used to be an economist. So he has a keen eye for natural experiments. This makes him a great person to compare notes with about how the criminal justice system works in practice.

“I had two misdemeanor clients who were similarly situated,” he told me recently. “Both were facing the same charge, but their cases had different outcomes due to random chance.”

Both clients were charged with misdemeanor assault on a government official—a charge that sounds really bad, but David assured me that such a charge at the misdemeanor, rather than felony, level is almost always pretty minor. (“I literally had a client get charged with assault of a government official for not saying, ‘Excuse me,’ when moving past a cop through a doorway,” he recalled.) The first client, Tiffany, arrived at the courthouse for her hearing to find that the officer accusing her of assault had not shown up. His partner, who had witnessed the incident, was there, but the prosecutor told him he could leave, then asked the judge for a continuance—a delay to a new date—so that they could get the first officer to the court. The judge denied that request. This led the prosecutor to scramble to get the second officer back to court, to testify as a witness. He succeeded—“a miracle for the prosecutor,” David noted—and Tiffany was convicted. This was devastating for her. As a result of that conviction—her first—she was not able to obtain an employment certification she’d been working toward. The training program she had invested time and money into was suddenly worthless. This first criminal record changed her trajectory for the worse, even though (because the charge was so minor) no meaningful punishment was handed down by the court.

David’s second client, Sam, faced the exact same charge. When he showed up to court, the accusing officer was not there. Just as in Tiffany’s case, the officer had failed to appear. (It turns out that this is a pretty common occurrence, which isn’t great for the smooth functioning of our justice system.) This time there wasn’t another officer who could testify as a witness. The judge again denied the prosecutor’s request for a continuance, and this time the case was dismissed. Sam was relieved—he worked as a security guard, but had been suspended from his job because of this pending charge. (A criminal record—even a misdemeanor like this one—is typically disqualifying for a position focused on public safety.) He had a limited amount of time before his employer would have needed to replace him. Even if the judge had granted the continuance and the case had been dismissed a month later, it would have been too late; he would have lost his job. Because the dominoes fell as they did that day, Sam kept his clean record and got to return to a job he liked, continuing his life as it had been before.

Just like the similar defendants in our study, who were lucky or unlucky depending on which prosecutor they faced during their arraignment hearing, David’s clients faced different consequences as a result of luck rather than anything about them or their cases. It is easy to see how such luck can play out case after case, day after day, putting similar people—like Tiffany and Sam—onto radically different paths. The results of our study support David’s observation that a first misdemeanor record can do a great deal of harm—at least for nonviolent defendants. (The assault charges that Tiffany and Sam faced would not be in this category, of course, but future studies may show similar impacts for violent misdemeanor charges like theirs.) With worse employment options, additional criminal behavior is more likely.

I asked David how aware his clients are of the impact of a first criminal record. “It’s usually me who brings it up,” he told me. “It’s more common that people first feel the impact of a pending charge, and then learn—probably accurately—that if the case is resolved quickly, even if it’s not in their favor, the problem goes away.” For example: “A class 2 misdemeanor for carrying a concealed weapon—a very common misdemeanor in North Carolina that is viewed as relatively minor—probably wouldn’t bar you from driving for Uber, but a pending criminal case will.” So there is a strong incentive to quickly take a plea deal so that you can keep your current job. Even so, there might be longer-term consequences from that conviction, depending on where you live or what types of jobs you might want in the future. So David tries to persuade his clients that waiting for a dismissal might be worth some temporary pain.

“Sometimes I’m in a position where I’m trying to talk somebody out of [taking a plea bargain immediately], reminding them that once a conviction is there [on your record] it will be there until it can be expunged, which is a long time from now and you might not qualify when that time comes. It might be worth trying to get to the next court date and beating this case, even if it’s going to cause you some more short-term difficulty. . . . I’m often the one who is trying to describe for them the problems of having a conviction, and they’re the one saying, ‘Look, I just want to get this over with.’”

More lessons from Suffolk County

Our results from Suffolk County tell us that prosecutors should avoid putting first-time defendants in this situation. They should err more toward leniency at the arraignment hearing and focus instead on trying fewer, more serious cases. This would give us more results like Sam’s, and fewer like Tiffany’s.

As an economist, I’m used to most policies involving trade-offs. And when my colleagues and I started working on the Suffolk County study, I fully expected to find some costs to leniency. Surely we would see some increase in criminal behavior, if only in minor offenses like trespassing and drug possession. The question in my mind was whether those costs outweighed the benefits, like how much time it saved everyone (including defendants) when a case was dropped. But when we followed the data, we found only benefits. Criminal behavior didn’t increase, it fell. And it fell by a lot. The other benefits to the court and defendants were icing on that cake.

As researchers, we are skeptical by nature. We wondered: What if these defendants didn’t offend again because they realized they’d gotten lucky? What would happen if there were an actual policy change that pushed all ADAs to become more lenient? Those defendants might change their behavior, and members of the community might hear about the change and decide obeying the law wasn’t worth it. Would we see crime rates go up then?

Luckily, we had such a policy change to consider. DA Rachael Rollins had implemented a “presumption of nonprosecution” for a list of fifteen nonviolent misdemeanor offenses when she took office. This meant that she instructed her ADAs to dismiss such cases unless they had a good reason not to. (A good reason might be that that person had already cycled through the court several times, and leniency was clearly not working.) This pushed all ADAs to be more lenient, particularly toward first-time defendants—exactly the group we’d found benefited the most from such decisions.

When we looked at the effects of this policy change, we found similar benefits as before: For defendants, we found that dismissing their cases led to fewer future charges, not more, just as we’d found was the case before the policy change. (This rules out the “I got lucky” effect.) And when we looked at local crime rates, we found no increases. Some types of reported crime may even have fallen.

Declining to prosecute low-level offenses isn’t unheard of. All prosecutors consider which cases are worth pursuing and which are not, and decline to prosecute many of them, for a variety of reasons. Under Rollins’s more conservative predecessor Dan Conley, the DA’s office chose not to prosecute 34 to 38 percent of nonviolent misdemeanor cases. Under Rollins’s policy, this rate increased by 5 to 8 percentage points—so her office became more lenient, but it wasn’t a radical shift. The change was on the margin, but it was big enough to make a difference for quite a few people.

“We have to give credit—DA Conley was doing this,” Rollins told reporters, poking fun at those who had criticized her approach as too liberal. “He just wasn’t as vocal about it as I was, and we’ve increased it a bit as well.”

The data vindicated DA Rollins, who had faced extreme pressure from local police officials to be tougher on misdemeanor defendants. Reporters asked what would have happened if the study’s results had come out the other way. “We would be adapting right now because at the end of the day, it’s not about policies, it’s about what are we doing to keep the people of Suffolk County safe,” she told The Boston Globe at the time—an answer that any researcher would love. “What I hope this does is say we are really serious about data-based, and evidence-based, solutions. This data shows the policies we proposed are working.”

Economists like to say there’s no such thing as a free lunch—there are always trade-offs. But we’d found a free lunch! Erring toward leniency, particularly for first-time defendants, made everyone better off.

This was for nonviolent misdemeanor cases, the most minor type of offense. There are many such cases, so this could make a big dent in the number of charges going through the courts, but what might leniency look like for people charged with more serious crimes?

* * *

Leniency in felony cases

Nonviolent felony cases are more serious offenses, like burglary and motor vehicle theft. These types of cases are much less likely to be dismissed outright. But in many places, prosecutors have the option to wait and see if a defendant is a public safety threat before convicting them.

In Texas, this option is called “deferred adjudication.” When prosecutors choose this option, the defendant begins a probationary period. If they successfully complete that probation with no new offenses, their initial charges will be dropped completely and they avoid that conviction. On the other hand, if they do get into additional trouble, their conviction goes into effect, along with some punishment (usually community supervision).

The country star Zach Bryan made headlines in 2023 when he was arrested in Oklahoma on obstruction charges. “It was ridiculous, it was immature, and I just pray everyone knows I don’t think I’m above the law,” Bryan said the next day. “I was just being disrespectful, and I shouldn’t have been. It was my mistake.” He received a deferred prosecution—that state’s equivalent of a deferred adjudication—and completed the terms of his probationary period six months later. A spokesperson for the Craig County District Attorney’s Office explained that Bryan “admitted responsibility and followed all the rules and conditions of probation. [Deferred prosecution agreements] are commonly used in cases where the person has no criminal record. It is an opportunity to take responsibility for their actions, follow probation rules, and avoid having a criminal conviction on their records.”

Does this second chance to avoid a felony conviction lead to more future offending, or less? Again, we face the same potential trade-offs: Reducing the consequences for committing a crime might embolden the defendant, leading to more crime in the future. On the other hand, avoiding a conviction could help them keep their job and housing, allowing them to course-correct on their own.

The net effect is an empirical question, and only real-world data can tell us what happens in practice.

The University of Michigan economist Michael Mueller-Smith and Simon Fraser University economist Kevin Schnepel were able to study this question in Harris County, Texas, where Houston is located. They linked a variety of administrative datasets that allowed them to see not only criminal justice involvement but also employment and earnings.

Linking such datasets is surprisingly difficult in the United States. These datasets are maintained by separate government agencies at county and state levels, and linking them requires complex negotiations and lengthy data use agreements. Many agencies simply say no when researchers ask to use their data, and even more say no when researchers ask to link their data with data from other agencies. This makes it difficult to understand how our criminal justice system affects other aspects of people’s lives—like whether they have a job.

But Mueller-Smith and Schnepel pulled these negotiations off. As a result, they had amazing data on felony defendants in a major American city (one that I now call home).

As before, data wasn’t enough. These researchers couldn’t simply compare defendants who received a deferred adjudication with those who were prosecuted and convicted as usual, because prosecutors carefully choose who gets this second chance. Deferred adjudications might be correlated with lower recidivism, but that could be because prosecutors give this option only to lower-risk defendants.

Mueller-Smith and Schnepel needed a natural experiment—something that sorted similar defendants into “deferred adjudication” and “regular conviction” groups, as if at random. Luck was on their side: They found not just one natural experiment but two.

Policy change one

The first natural experiment was a policy change that had unintended consequences. In 1993, the Texas legislature enacted a reform that imposed a new probationary requirement for low-level offenders. The policy sounded like it was in line with diversionary goals—that is, helping first-time offenders avoid being pulled into the criminal justice system—but in practice it made diversion less appealing to prosecutors. If they granted a defendant a deferred adjudication, and that defendant did not comply with the terms of the probationary period, they could not simply revert to the original conviction and sentence. The new policy said they’d have to put them on probation again before the sentence could go into effect. This gave the first probationary period no teeth.

Prosecutors warned the legislature that this policy could backfire, but to no avail. The policy went into effect on September 1, 1994. Deferred adjudications immediately dropped, by 24 percentage points for first-time defendants.

This meant that identical defendants, charged with the same nonviolent felony offense but who committed their crimes just before and just after September 1, 1994, faced different consequences. The person who offended just before the policy change was dramatically more likely to receive a deferred adjudication than the person who offended just after the policy change.

This created the first natural experiment. The date of the policy change—September 1, 1994—sorted defendants into treatment and control groups, as if at random, based on the date of their offense. Nothing else changed at that date. The only difference between these defendants was whether they got a second chance to avoid a felony conviction.

It turns out this second chance was very helpful. First-timers who got lucky and received a deferred adjudication committed fewer crimes going forward. They were 31 percentage points less likely to be convicted of any new crime over the next ten years—a 44 percent reduction compared with the control group.

First-timers who got lucky and received a deferred adjudication were 31 percentage points less likely to be convicted of any new crime over the next ten years—a 44 percent reduction compared with the control group.

This second chance also increased labor market participation. Employment rates increased by 18 percentage points (49 percent relative to the control group), and total earnings over the following 10 years grew by more than $85,000 (93 percent relative to what the control group earned). A large share of those who received this second chance took full advantage of it.

Policy change two

In the early 2000s, policymakers in Harris County, Texas, were increasingly worried about overcrowding in the local jail. By 2005, there were nearly two thousand inmates sleeping on mattresses on the floor—very bad conditions that were clearly unsustainable.

Government officials sought to raise money to expand jail capacity. In November 2007, they put an initiative on the ballot in the county election to fund construction of a new jail facility. Particularly in conservative states like Texas, such initiatives are usually successful.

This one was not. To everyone’s surprise, the ballot initiative was narrowly defeated, with 50.6 percent of voters voting against it—even as they overwhelmingly approved additional statewide funding for increasing prison capacity. This defeat shocked local policymakers and criminal justice practitioners. They suddenly realized they’d need to solve their overcrowding crisis some other way.

One result was a sudden increase in diversion—either deferred adjudications or outright case dismissal—for nonviolent felony defendants. First-time offenders who committed a crime just after the failed ballot initiative got lucky—they were dramatically more likely to get a second chance. Overnight, the probability of diversion increased by 18 percentage points.

Again, this set up a beautiful natural experiment. Mueller-Smith and Schnepel could compare defendants sentenced on either side of the election on November 6, 2007. The only difference between those sentenced before and after this date was that those sentenced after were much more likely to avoid a conviction. This difference wasn’t because of underlying differences between these defendants or their cases; it was because of the failed ballot initiative. This gave the researchers confidence that any future differences in recidivism or employment would be due to the diversion decision and not to something else about those defendants.

Just as in 1994, there were big benefits to greater leniency. As the likelihood of diversion suddenly increased, the likelihood of new, future convictions fell, by 26 percentage points (46 percent). This is a dramatic change. Nearly half of the first-time offenders who would have committed another crime in the future if they’d been prosecuted and convicted as usual cleaned up their acts and avoided future crime when their cases were dropped or they received a deferred adjudication. It is really difficult to find interventions that reduce recidivism this much. This second chance to avoid a first felony conviction had a much bigger impact than most rehabilitation programs do.

* * *

Putting it all together

When I first saw these results, they seemed too good to be true. We can cut recidivism by half simply by not convicting first-time defendants? This feels like magic, particularly in a context where many highly praised reentry programs struggle to reduce recidivism at all.

But these studies are extremely compelling, with natural experiments that closely mimic ideal experiments with control groups. And the findings are remarkably consistent—a second chance for first-time defendants cuts future crime by half, in all these contexts. As more research comes out, I become more and more convinced that a criminal record is a terrible bludgeon that we should use much more sparingly than we do now. It is very difficult to undo the damage of a criminal record, once it has been imposed.

I become more and more convinced that a criminal record is a terrible bludgeon that we should use much more sparingly than we do now.

Best of all, these dramatic results don’t require dramatic reforms. Small shifts, making leniency the default rather than the exception, are enough. Cutting recidivism in half for first-time offenders will quickly reduce reported crime and court caseloads, allowing greater attention on those who do offend again.

Leniency doesn’t mean no consequences

When we first released our research from Suffolk County, some responded that we should completely decriminalize minor offenses like disorderly conduct and shoplifting. But that’s not what this research showed. Dropping someone’s charges at their arraignment hearing doesn’t mean there were no consequences for their actions.

That person had likely been arrested and booked in jail, and had to show up in court for that initial hearing. This might mean taking time off work, and it certainly meant worrying about what might happen during the hearing. All this isn’t nothing—it is an inconvenience at best and a costly and stressful event at worst.

In the Harris County study, “lucky” defendants also had to successfully complete a probationary period, during which they had to demonstrate that they could refrain from future criminal behavior. That involved following additional rules to earn their second chance.

What this research shows is these earlier steps in the case—arrest and an initial hearing for nonviolent misdemeanors, and a probationary period for nonviolent felonies—are often punishment enough. Adding a criminal record on top is what has big, detrimental effects, at least for first-time offenders. Helping someone avoid that first conviction gives them a second chance. It’s as if they’re standing at a fork in the road, considering what to do next. One direction leads toward more criminal behavior and criminal justice involvement, and the other leads toward a productive, law-abiding life. It turns out that many first-time defendants will choose the better path if we simply get out of their way.

Excerpted from The Science of Second Chances by Jennifer Doleac, published by Henry Holt and Co. Copyright © 2026 by Jennifer Doleac. All rights reserved. Reprinted with permission.

The post What Becomes of Second Chances? appeared first on Behavioral Scientist.

Harvesting five million bushels of wheat and corn from Texas to Montana, outrunning hailstorms that decimate a year's income in 20 minutes, and running a multimillion-dollar convoy of equipment down the highway with Josh Beckley, a third-generation custom harvester from Kansas. Why do farmers outsource the harvesting of their own crops? And what happens when you drive a combine into a ditch?

[buzzsprout episode='19032277' player='true']

View the episode transcript

About What It's Like to Be...
In each episode of What It's Like to Be..., bestselling author Dan Heath speaks with someone about what it's like to walk in their (work) shoes. Behavioral Scientist serves as a distribution partner with episodes released every other week. Learn more about the podcast's mission of "slow curiosity" here, and head here to get Dan's reflections on how the mission is going after a year of conversations.

The “Custom Harvester” episode of What It’s Like To Be… featured Josh Beckley. It was produced and edited by Matt Purdy. Copyright © 2026 by Dan Heath. All rights reserved.

The post What It’s Like to Be…a Custom Harvester appeared first on Behavioral Scientist.

In 2010, Joseph Henrich, Steven Heine, and Ara Norenzayan showed that 96 percent of the data that scientists had relied on to understand human psychology and behavior was from W.E.I.R.D. research participants—people living in Western, educated, industrialized, rich, and democratic countries. That biased sample, they argued, severely limited what we could say we really knew about ourselves. Their work was a wake-up call to many scientists to expand where and how they conduct their research.

But recognizing the need to expand and diversify research is one thing, and actually doing it is another. A decade later, Henrich, Norenzayan, and Coren Apicella conducted a follow-up study to see if participant samples had gotten more diverse. They hadn’t. The research team found that 94 percent of studies were still conducted with W.E.I.R.D. participants. 

The W.E.I.R.D problem persists not because scholars fail to see it as a problem worth solving but because conducting research in new, unfamiliar places is difficult. There are language and cultural barriers, obstacles to finding participants, and complications with technology. But overcoming these difficulties is doable, and it’s essential. 

The W.E.I.R.D problem persists not because scholars fail to see it as a problem worth solving but because conducting research in new, unfamiliar places is difficult.

In 2023, I founded Besample, a platform designed to help scientists reach participants all over the globe, in order to help solve these challenges. As a social psychologist trained in the United States, but born and raised in Russia, helping researchers address the W.E.I.R.D. problem feels both personal and professional. And in Besample’s first three years, we’ve learned that many scientists, when given the opportunity, are ready to address the W.E.I.R.D. problem too, by expanding where they conduct their research.

So far, we’ve worked with over 1,700 scholars on more than 880 studies, collecting nearly 330,000 data points from participants in 42 countries across Asia, Africa, Eastern Europe, and South America. Data collected through Besample has covered a range of phenomena and is now making its way into the academic literature, including cross-cultural research on loneliness and investigations into value systems, perceptions of climate change, and family dynamics.

Through this work, we’ve learned quite a bit about how scientists can conduct high-quality, culturally grounded research beyond the West. Here are seven key lessons we would like to share.

1. The world does not speak English

Researchers from North America and Western Europe often default to running studies in English, even when targeting non-English-speaking countries in the Global South. While English may work in former British colonies, like India, South Africa, or Kenya, it falls short elsewhere, especially in Asia and Latin America.

This is a problem, because people from non-English speaking countries who read and write in English are special, not representative. Most likely, they’ve been economically privileged enough to learn the language in good schools or colleges. 

Another problem with running studies in English is that even highly proficient speakers can experience the foreign-language effect, where they feel more emotionally detached from the material simply because it’s not in their native language. People find it easier and more natural to complete tasks in their native language, which can influence how they respond. 

For some, this is a matter of dignity. In Turkey, for instance, some of Besample’s respondents declined to participate in studies conducted in English, because the lack of a Turkish translation felt disrespectful. Kazakhstan presented an even greater challenge; respondents dropped out at the consent stage if it was presented in dense legal English—they treat formal agreements very seriously, and the inability to fully understand the text was perceived as a risk.

At Besample, we recommend translating studies into local languages for countries where the average English proficiency is below 50 percent, which helps boost sample size and representativeness. Today, it’s easy to generate a first draft of translations with AI, and local experts can help proofread and ensure that materials are appropriate given the cultural context.

2. Standard attention checks create more noise than signal

As the popularity of online studies grew in the scientific community, researchers became more concerned with whether participants were actually paying attention. So they developed attention checks—questions to assess whether a participant was reading the materials carefully—to filter out low-quality responses. 

In studies with non-Western populations, researchers frequently exclude those who fail attention checks, assuming this reflects a participant’s lack of focus and indicates low-quality data. However, in global research, such failures are often a matter of a language barrier or less familiarity with participating in studies rather than a lack of engagement or incoherent data. 

For example, in an analysis I coauthored on the data quality of online research platforms, we found that Besample respondents with lower English proficiency could fail attention checks but provide high-quality data to other questions. These findings suggest that attention-check performance is not a definitive proxy for data quality. 

Before making the easy call to dismiss responses, scientists should view attention-check failures through a linguistic lens—or, even better, design localized quality checks based on consistency and accuracy prior to launching a study in a new context. 

3. Questions about race and ethnicity are not universal

Another trap researchers can fall into is using Western-centric templates for questions on race and ethnicity. Though it’s common to think about one’s identity in terms of race in places like the United States or United Kingdom, in other countries it’s not. And when it comes to ethnicity, there are over 800 distinct ethnicities (or over 7,000 if you use ethnolinguistic groups as a taxonomy).

To better understand the diversity of our participants, we surveyed nearly 1,000 people from 11 countries: Brazil, Colombia, Indonesia, Japan, Mexico, Morocco, Nigeria, Spain, Ukraine, the United Kingdom, and the United States. We asked respondents about their self-identification regarding race and ethnicity, providing both open-ended and multiple-choice questions. Open-ended responses showed that many participants described themselves by ethnic group or geographic region rather than conventional racial classifications. 

For the multiple-choice questions, people in countries such as Ukraine, Morocco, and Indonesia selected commonly used categories 50 percent less often and were more inclined to select a category when presented with options from an extended ethnic scale, because it included ethnic identifiers that standard questions leave out.

When launching a study in a new, culturally distinct place, failing to adapt questions around race and ethnicity can lead to meaningless or even misleading data.

4. Simple questions about gender aren’t so simple

Cultural nuances can also alter the meaning of even the most basic-seeming gender identity terms. A couple of years ago, when we were building an early pool of respondents, we noticed a puzzling pattern in Indonesia: In a demographic pre-screener, an unexpected number of people were selecting “other” when asked whether they identified as pria (male), perempuan (female), or lainnya (other). We were curious to learn why. 

We knew that Indonesia was among a few world societies where, in certain provinces, more than two gender categories were accepted. But most of our respondents were not from those provinces. When we added an open text field to the “other” option, we started to see an influx of typed-in responses, all similar to laki-laki. Young Indonesian men were just not calling themselves pria because that was a term for older, adult men. For younger males, there was a different word: laki-laki. While distinctly identifying as male, young men were selecting “other” to type in this exact word. 

Another example is hijra, a gender category found in India, Pakistan, Bangladesh, and Nepal. Hijra are neither “men” nor “women,” nor simply “transgender” in the Western sense. They are often recognized as a third gender, with long-standing social and ritual roles that stretch back hundreds of years. When people identify as nonbinary around the world, it often means something very different from what we’re used to in the Western context.

Asking about gender also requires more than just understanding the correct terminology. In many places, certain gender identities and sexual orientations face prejudice or are even punishable offences, so researchers need to be aware of this before launching their studies. 

5. Standard questions about marital status are not sufficient 

Marital status is deeply intertwined with family makeup, household decision-making, economic life, and a host of other things that social and behavioral scientists are interested in. But in some cultural contexts, asking about marital status is far more complicated than it might seem. 

For instance, in South Africa, researchers may need to distinguish between a civil ceremony and a traditional union formalized through lobola, a practice involving the negotiated transfer of property (in cash or in kind) from the prospective husband or his family to the bride’s family. 

Additionally, in the West, marital status is often interpreted as monogamy. But in countries such as Senegal, Guinea, Liberia, Mali, Burkina Faso, Benin, and Togo, polygynous unions account for 40–60 percent of reported marriages.

Turning to divorce—another key variable in studies of close relationships—Western researchers often assume that people are free to exit marriage through divorce. But in many countries, divorce is legally restricted, socially stigmatized, or practically inaccessible, making it a poor proxy for relationship quality or stability. A striking example is the Philippines, where divorce is not legally available for most citizens. Instead, marital dissolution occurs through Catholic annulment, a costly and rare process. As a result, less than two percent of the population has divorced, separated, or had a marriage annulled.

6. Households and household income look differently around the world 

It is common for researchers in the United States to assess participants’ economic standing by asking about their household income. But the idea of the household—a cornerstone unit in Western economics and connected with income, consumption, and decision-making—is frequently different in non-Western cultures. 

For example, in rural Malawi, households often diverge from the idealized Western model. Families can be spatially dispersed, household membership fluid, and major decisions follow matrilineal or patrilineal kinship lines. So in Malawi, kin social networks and resource flows often capture economic reality better than the Western household template. 

Additionally, many people assess their income in monthly terms and in immediate purchasing power, rather than in abstract annual household income terms (and especially not in foreign currencies like dollars or euros). 

Another financial difference worth pointing out is that many researchers assume they can pay online participants using bank transfers or PayPal. However, the ways people bank and handle everyday purchases is extremely variable. In many countries, cash and mobile transfers are the default rather than bank cards, and PayPal is virtually unknown. Bureaucratic hurdles can also make it highly inconvenient for people to receive a small $1–$3 reward for participating in a study via bank transfer. In some cases, this even requires visiting a bank in person to justify the transfer. This reality led us to build a network of more than 20 country- and region-specific partners, offering more than 45 different payment options to reward research participants. 

7. Conventional technical criteria do not indicate data quality

Traditionally, certain technical criteria, such as a unique IP address, served as a proxy for data quality. If many people logged in from the same IP address, researchers assumed that the same participant was taking the survey multiple times, and the data should be thrown out. But this isn’t necessarily the case.

In regions with limited IP availability, such as parts of Africa and Asia, it’s common for multiple users to share the same IP address. Many mobile operators assign a single public IP to hundreds—or even thousands—of devices, especially in mobile broadband networks where dynamic IP allocation manages connectivity for large user bases.

Researchers have also traditionally assumed that respondents using a desktop or laptop computer will provide higher quality data, and have often optimized their studies for PCs. But in many non-Western countries access to PCs are limited—in some countries less than 10 percent of people have access to a computer or laptop. Limiting studies to PCs can create a barrier to data collection and bias samples toward higher-income, urban participants with better digital access. 

But even if a survey is designed to work on a mobile device, people may lack reliable internet or have limited mobile data. These factors make it difficult for respondents to complete long surveys, especially those with large files or videos. 

What appears to be “low-quality” data based on a technical criterion may actually reflect local infrastructural and socioeconomic realities. Relying on technical checks like PC-only access or unique IP addresses leads to biased samples, slower data collection, and a failure to capture the true diversity of non-Western regions. 

* * *

These lessons detail some of the practical steps that researchers can take to move beyond W.E.I.R.D. populations. Taken together, these lessons also point to a broader shift that is needed if we want to make the social and behavioral sciences truly global: We need to have the courage to admit that things will likely go differently than we expect. And as we venture out to study the world, intellectual humility should be our starting point.

The post Helping Scientists Take Their Research Global: 7 Lessons appeared first on Behavioral Scientist.

There is a popular belief that technological innovation will solve climate change without fundamental shifts in society and politics. For example, the World Economic Forum claims “we must invent our way out of climate change.” Solving climate change, the thinking goes, means investing in innovation.

Technocratic policies, such as the carbon tax, also assume a direct path between problem and solution. The idea of a carbon tax assumes that if emissions are priced correctly, firms and consumers will automatically reduce carbon use and invest in cleaner alternatives. The “solution” lies in engineering policies to calibrate the tax rate, coverage, and enforcement mechanisms.

Technological innovation and tech-oriented policies are a vital part of the way forward, but the approaches suffer from a blind spot. Both overlook key social and political factors underpinning climate action. This tech-first mindset rests on three myths about how global social change happens.

Myth 1: Environmental policies, activism, and solutions develop as a natural response to environmental problems. 

When environmental problems get worse, we might assume that we’ll naturally respond with more ambitious action. But that’s not necessarily the case. More extreme wildfires or heat waves, for example, ought to generate support for stronger climate change policies. But decades of research in sociology and political science shows that grievances and need alone do not automatically produce movements or reforms. 

Consider the “London Fog,” one of the most well-known examples of an environmental problem that persisted for decades without meaningful reform. For more than a century across the nineteenth and twentieth centuries, Londoners lived with a lethal smog that blanketed the city. It was such a feature of everyday life that it became normalized in media at the time; the opening chapter of Charles Dickens’s Bleak House famously characterizes a dense fog that chokes the city as an ordinary part of urban life. It wasn’t until 1956, when political conditions made action possible and people also saw pollution as a preventable public health problem, that the Clean Air Act was passed in the United Kingdom.

In the case of climate change, extensive evidence shows that environmental understanding and concern does not automatically translate into action. For example, among developing countries, environmental associations tend to emerge in countries where ties to global environmental networks are deepest rather than in countries facing the most severe environmental degradation.

The presence of a problem alone, even if there is awareness, is not enough to generate mobilization or reform. Social causes require organization, political opportunities, and compelling narratives in order to succeed.

Myth 2: The right technology and policies will automatically lead to change on the ground.

If the first myth assumes problems naturally produce solutions, the second assumes that once the right technology or policy appears, meaningful change will follow. 

When it comes to policy, research in sociology and political science shows that countries and organizations frequently adopt policies for reasons that have little to do with solving the underlying problem. Policies often serve as a signal of modernity or demonstrate alignment with global norms, producing legitimacy. At times, symbolic adoption can create the appearance of action without necessarily producing real change, a phenomenon known as “loose coupling.” Although some instances of loose coupling are intentional acts of “greenwashing” intended to gain legitimacy while avoiding the costs of action, in other cases actors may simply lack the capacity to enforce or implement policies.

Take the Paris Climate Accords: Nearly every country in the world ratified the international treaty a decade ago, but many are not meeting their promises to cut world pollution levels. Many countries failed to submit their updated nationally determined contribution plans by the 2025 deadline, as required by the treaty. Airline carbon offset programs offer another example. Companies often adopt policies that allow passengers to pay to “offset” emissions from their flights, but there is limited evidence that these policies meaningfully reduce overall emissions in practice.

When it comes to technology, successful solutions can fail to spread because of social and political dynamics. For example, from a technical standpoint, induction cooktops use less energy, offer faster cook times, and provide substantial safety and indoor air quality benefits relative to traditional gas and electric stovetops. The technology has been available for decades, yet uptake is slow due to a range of individual, social, and institutional barriers. These include the hassle and expense of replacing your stove, the norm of gas stoves as the “professional” standard, and the failure of big box retailers to add induction stoves to their display rooms.

Myth 3. Scale is a silver bullet.

The third myth is that solutions work better if they are scaled. If the problem is global, then the solution must be to scale promising technologies and policies to everyone, everywhere. 

This line of thinking tends to equate local effectiveness with scalability. But interventions that are effective in one context often fail when transplanted elsewhere, even to settings within the same country. Moreover, research also shows that large-scale reforms can generate reaction and backlash. As environmental policies and institutions spread globally, they can provoke reactions from groups who see these changes as threats to their values, autonomy, or ways of life. These groups emerge in reaction to large, ambitious reforms that seem disconnected from their own interests and work to challenge, deny, and roll back environmental policies.

Consider the farmers’ protests that erupted in Europe from 2023 to ’24. In response to the European Union’s Green Deal, many farmers blocked highways, dumped manure on roads and outside government buildings, and drove tractors through key cities to protest laws they saw as threatening their livelihoods. Ultimately, these actions forced the European Commission to delay or relax key climate measures, which is a trend that has continued to this day. These actions are part of a broader trend, which also includes the Yellow Vest protests in France that emerged in response to a proposed fuel tax hike in 2018 and the recent push against carbon pricing taxes in Canada that led to their partial repeal in 2025. 

Policies and technologies provoke resistance when they disrupt established practices, challenge existing identities, or are misaligned with local conditions. Scale can amplify all of these effects.

What can be done?

Our discussion points to the importance of understanding the social, political, and historical conditions that shape how solutions emerge, whether solutions work, and when inventions and climate policies can provoke backlash. Climate solutions do not operate in a vacuum: They interact with existing norms, identities, and interests, and they can fail when they conflict with them. 

This means that top-down regulations and efforts to scale inventions and policy need to come with serious attention to understanding and addressing the concerns of groups whose identities or livelihoods might be threatened. Relevant stakeholders should be meaningfully engaged from the very start of design processes rather than as an afterthought during implementation. We can also work from the bottom-up, developing local or community-based solutions. 

At the same time, we should think of new inventions, interventions, or policies as a first step toward the goal we really care about, not the end point. We should focus on outcomes like whether emissions fall, infrastructure changes, or behaviors shift at least as much as we focus on policy design and the development of technical solutions. This requires sustained attention to implementation. Potentially effective technologies, interventions, and policies can fall short not because they are wrong but because a lack of attention to social and political dynamics inhibits widespread behavioral change. For instance, energy companies routinely adopt voluntary methane reduction initiatives and publish extensive sustainability reports in some countries, but in practice implementation is weak as they evade substantial emissions reductions by continuing flaring practices in other countries with low enforcement or excluding overseas facilities from their emissions reports.

Finally, because countries and organizations routinely adopt policies to conform to what others are doing, public narratives have an important role to play in shaping what kinds of policies are adopted in the first place. These narratives are capable of provoking broad pro-environmental change by shaping our beliefs about climate change, creating more pressures on countries or organizations to act, and empowering new actors to advocate for pro-environmental change. The cumulative result of these cultural processes acting in the same direction is a systemic shift that can provoke social change, even when single policies or institutions look like they are weak or ineffective in isolation.

Addressing climate change means that people from different backgrounds with different viewpoints and different motives will need to act together to address the problem. When our solutions don’t acknowledge that, or are based more on hope than reality, we fall short of what the situation demands. If we treat climate change as purely a technological problem, we miss the necessary role of norms, identities, and worldviews in creating enduring social change.

The post Climate Change Is Getting Worse. Why Don’t We See More Action? appeared first on Behavioral Scientist.

Guiding grieving families through arrangement meetings, orchestrating meaningful memorial services within days, and preparing bodies for viewing with Heather Hill, a funeral director in North Carolina. What's different about doing makeup on a dead person? And what is it like to field a death call?

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About What It's Like to Be...
In each episode of What It's Like to Be..., bestselling author Dan Heath speaks with someone about what it's like to walk in their (work) shoes. Behavioral Scientist serves as a distribution partner with episodes released every other week. Learn more about the podcast's mission of "slow curiosity" here, and head here to get Dan's reflections on how the mission is going after a year of conversations.

The “Funeral Director” episode of What It’s Like To Be… featured Heather Hill. It was produced and edited by Matt Purdy. Copyright © 2026 by Dan Heath. All rights reserved.

The post What It’s Like to Be…a Funeral Director appeared first on Behavioral Scientist.

Approximately 2 billion people live in conflict-affected areas. Yet the field of behavioral science has developed most of its theories, run most of its experiments, and built most of its interventions in stable contexts. When behavioral scientists do work in conflict settings, we tend to follow a familiar pattern: take what worked elsewhere, “localize” it, and evaluate it. But this isn’t enough. 

This is an urgent problem. Conflict is reshaping lives globally at an unprecedented scale. In 2024, 123 million people were forcibly displaced—the highest number on record. Civilian casualties in Gaza, Lebanon, and Ukraine have reached levels unseen in over a decade, including for children. 

I’ve spent nearly a decade applying behavioral science in conflict settings across 15 countries and 4 continents, and here is the hard truth: Our field is still missing critical understanding about how behavioral science works in active conflict—and there’s more to learn than we might realize.

At the Neuropaz conference this past February, I was asked to speak about the hard truths those working at the intersection of behavioral science and peacebuilding need to confront. 

What follows are five of those hard truths, and what we can do about them.

Hard truth #1: We don’t have much evidence about what works from conflict settings

The vast majority of theories, experiments, and interventions we use in applied behavioral science were developed in stable contexts. Political science has studied conflict dynamics; development economics has studied postconflict recovery; and social scientists have run studies in conflict settings evaluating specific programs. But we lack systematic evidence about how conflict reshapes decision-making, how to co-design interventions grounded in what communities actually need, and how to measure and scale what works in these contexts.

Why don’t we have good evidence from conflict settings?

First, doing research amid conflict is difficult—logistically, ethically, and politically. Access and security is limited, populations are displaced, and the basic infrastructure needed for research can be absent (though we’re beginning to figure out ways to navigate these challenges).

Second, our field tends to bring existing frameworks, measures, and theories, all developed elsewhere, and then adapt them at the margins. What we need more of is systematic understanding of how conflict shapes psychology and what communities actually need from the outset, before deciding what interventions to test. Too often, qualitative research with communities happens after an intervention has been designed and evaluated, to explain what worked or didn’t. By then, we may have missed the chance to get the fundamentals of the intervention right, for the people who need it most.

Third, there is also a deeper problem: Research in this space can be optimized for measurability over impact. Research questions are often chosen based on what we can easily evaluate, not necessarily where intervention would matter most. As a field, we haven’t invested as much in developing the foundational knowledge for conflict settings as we have for stable contexts.

Conflict isn’t just harder development or more extreme poverty. It fundamentally shapes how people think, decide, and cooperate. We've made some progress moving beyond WEIRD research in recent years, but we cannot assume that evidence from stable contexts—even in the Global South—readily transfers to conflict settings.

Hard truth #2: Conflict creates different psychologies, and we often misdiagnose behaviors we don’t understand as “biases”

In northeast Syria, years of conflict and climate change have devastated farmland and dismantled the seed system. Starting in 2021, our teams at the Airbel Impact Lab—the International Rescue Committee (IRC) research and innovation unit—partnered with IRC’s Syria Country Team and local stakeholders to address this crisis. Working with farmers, they developed an innovative seed multiplication program where farmers would grow climate-resilient wheat varieties and donate a portion of their harvest back to a collective pool, spreading high-quality seed across their community.

The model’s success depended on farmers being willing to set aside part of their harvest for collective benefit—trading today’s security for tomorrow’s gains. For this to work, we needed to understand how people in active conflict think about the future and make trade-offs between immediate and delayed rewards. So we ran a standard time discounting survey to understand how people in this context think about the future.

We asked farmers: Would you take 500,000 Syrian pounds today, or 1 million in one month?

Forty percent chose the immediate amount, a daily discount rate of 10 percent, compared to a global average of 0.3 percent. The behavioral economics literature would call this hyperbolic discounting, or present bias—a behavior to correct.

But when we talked to farmers, we found something different. As one farmer explained: “I cannot be sure I will be alive in one month to collect a larger payment.”

This wasn’t bias; it was a rational adaptation to chronic uncertainty. When the future is genuinely unstable, when conflict is ongoing, when you might be displaced next week, prioritizing the present is survival, not error.

This is why we need to be more thoughtful with the term “bias” in crisis settings. When behavior looks “irrational,” we need to get more curious about people and context. Ask: What’s the logic of this behavior in this environment? In our program, we didn’t try to “correct” farmers’ time preferences. We adapted our approach to provide benefits sooner rather than later.

Conflict doesn’t just amplify existing behaviors. It fundamentally reshapes how people think about the future, trust, risk, and cooperation. The psychological adaptations are different in kind, not just degree.

Hard truth #3: We can’t just adapt existing interventions. We must co-design from the beginning

In the past decade, there has been significant focus on “localizing” behavioral interventions. The aim of localization is to ensure that programs are culturally appropriate, contextually relevant, and led by local actors rather than imposed by international organizations. The push for localization is a long-overdue shift away from decades of top-down development.

But in practice, localization often becomes: take what worked elsewhere, translate the materials into the local language, add some cultural elements, and evaluate it. This falls short of what is needed. 

Take the case of social-emotional learning (SEL). SEL interventions have demonstrated significant impact with vulnerable children globally—improving academic achievement, attendance, and mental health. Based on this evidence, international organizations began adapting evidence-based SEL programs developed in stable contexts for use in conflict, crisis, and displacement settings. The goal was to test whether these adapted interventions could improve both learning and well-being outcomes among conflict-affected children.

IRC ran a series of randomized controlled trials (RCTs) evaluating SEL programs that had been adapted and implemented in northeast Nigeria—a place which has experienced ongoing conflict with Boko Haram for over 16 years. The RCTs were rigorously designed to test program impact on children’s social-emotional and academic outcomes.

However, the studies showed limited or null effects on the social-emotional outcomes they were designed to address. The programs had been translated, cultural elements added, frameworks adjusted, but they were still built around assumptions from elsewhere. 

Teachers weren’t using them, as they found them disconnected from what mattered locally—both the skills and values children needed to succeed in their communities and the classroom realities teachers faced daily.

Sometimes the problem isn’t that researchers don’t adapt interventions or even that communities won’t adopt behavioral science research. It’s that interventions designed in different places, with different people, under stable conditions are less likely to work in conflict settings.

It’s not that we can’t draw from the broader behavioral science evidence base, but we have to acknowledge that adaptation can only go so far. Developing effective interventions requires co-designing with the community from the start. 

In Nigeria, we shifted to this approach. Our behavioral science team at Airbel joined the project to identify barriers and co-design interventions that could overcome them.

We didn’t ask ourselves, “How do we get teachers to use these SEL activities?”

We asked teachers, parents, and community leaders: “What do children in your community need to grow up to become successful adults—beyond academics? What values matter here? What skills? And how can behavioral science help design supports that work for what people actually need?”

Community members identified skills and values that mattered most to them. Some overlapped with standard SEL frameworks, like self-regulation and empathy. Others were different, like respect, obedience, and discipline.

As one teacher told us: “Discipline is the most important thing because you need to be disciplined to achieve a lot in life.” This wasn’t in our original SEL framework. But it was central to what communities saw as essential for children’s success.

We then co-designed new activities with teachers and community members around the skills they had identified—discipline, respect, tolerance. We kept the active ingredients—the psychological mechanisms that make SEL effective, such as conflict resolution and social problem solving, and focused on short, targeted activities that build specific skills. But the specific activities were co-designed from the ground up with teachers and community members around the skills they had identified. 

Same psychological mechanisms, different expressions, and co-designed from the start.

In a pilot study after this, teachers were implementing SEL activities for an average of 18 minutes per day—the intended dose—compared to the previous program, where most teachers reported they hadn’t used the SEL activities since their initial training.

This is the difference between the light touch localization and genuine co-design. Localization takes what works elsewhere and adapts it. Co-design starts with what matters here and uses behavioral science to support it.

Hard truth #4: We still need to learn how to sustain and scale what works 

In northeast Syria, years of conflict have also created deep tensions between internally displaced people and host communities—those who stayed in place during the war. Our behavioral science team at Airbel, again in partnership with IRC Syria, is currently working on a project to increase peacebuilding behaviors between these two groups, including internally displaced people and hosts serving together on local committees, and jointly deciding how to resolve intergroup conflict and allocate resources within the community. 

In an early workshop testing behavioral interventions to build these behaviors, an internally displaced person said: “I used to think the hosts are racist, but after the exercise I realize that we are the same.” 

That moment of rehumanization was profound. And it happened in a single workshop with a few dozen people.

In many cases, exciting behavioral science interventions that address conflict risk remaining one-offs. Even when we find interventions that create real change, we lack clear, evidence-based pathways for scaling them. Contact interventions, one of the most well-documented interventions in conflict settings, show short-term prejudice reduction. But how do we move from workshops with dozens of people to population-level change? How do we design for scale from the beginning, in a way that is both deep (contextually relevant) and wide (reaching most of the population)?

In our recent seed-security Syria work, we’re designing and testing this from the beginning. What behaviors need to spread for social cohesion to improve at a population level? How do we design and measure interventions that can reach entire communities across a region, not just individuals? Who are the most effective spreaders of behaviors? What motivates them? Under what conditions do people invite others into programs? 

Hard truth #5: We’re measuring the wrong things

Most peacebuilding research measures individual-level attitudes, like prejudice reduction, trust, or empathy. But we need to measure actual behaviors, not just attitudes. Do people cooperate across group lines? Do they engage in violence? Self-reported attitudes are easier to measure, but behavior is what matters.

And still there’s a deeper mismatch: We’re intervening at the individual level and measuring at the individual level, but often the things we're trying to prevent—for example, intergroup violence—happen at the community level. We can’t assume that changing individual attitudes or behaviors translates to preventing community-level violence without actually measuring whether it does.

* * *

A different approach: Five principles for research in conflict settings

If our field were to approach behavioral science in conflict settings differently, here’s what it might look like.

First, start with communities, not problems. Conventional approaches often pick a problem first, then ask, “What’s measurable?” This means optimizing for what we can count, not what counts. Instead, ask people directly: What challenges do they face in their day-to-day lives? What are their goals? What does a better, healthier, safer life look like to them? This scopes where intervention would matter most. 

Second, co-design with communities and with local researchers as true co-scientists. Local teams bring lived experience, cultural expertise, and community trust that outside researchers cannot. This should shape intervention design from the start, before deciding what to test. This includes specific wording, delivery mechanisms, and measurement approaches. We need to design for the realities people actually live, not the ones we assume.

Third, identify the active ingredient, then ask how it works here. Don’t just translate an intervention. Ask: What’s the psychological mechanism that worked elsewhere? Then ask: How does that mechanism work in this specific context? For example, in our initial testing of “conversational receptiveness,” an intervention that helps people listen across disagreement, in Syria, we don’t plan to just translate scripts. We’re asking: How do people actually express active listening across group lines in this context?

Fourth, test assumptions at a small scale before full rollout. This is good practice in any setting, but it becomes even more critical in conflict settings, where the context is likely to be novel and rapidly changing. Start by prototyping—turning solution ideas into simple, tangible mockups (drawings, paper concepts, role-plays) and testing them directly with users to learn what resonates and co-design what needs to change. Then run small behavioral tests or experiments to check: Does this actually work as we think? Does it help or hurt? This rapid, iterative testing with users allows teams to surface contextual misalignments early, before investing in full-scale implementation. 

In our seed-security work in Syria, we found that farmers donated 38 percent more to others when they perceived the “others” as similar to them, confirming our hypothesis that emphasizing common ground can increase cooperation.

But small-scale testing also caught assumptions that would have derailed the program. We hypothesized that women would need to bring a family member to enroll, based on what we'd been told about cultural norms. Testing revealed this was wrong in some areas and right in others for completely different reasons: In areas with recent attacks, women needed someone for physical safety traveling to sites, not for cultural reasons. Without testing, we would have applied a one-size-fits-all rule that failed everywhere.

Finally, design for scale from the beginning, but define what scale means for your context. Scale doesn't always mean exact replication or global reach. Given that conflict creates different psychologies and contexts vary enormously, an intervention might only spread effectively within a specific area or region—and might need to adapt as it spreads. The question isn’t, “How do we scale this everywhere?” It’s: “What’s the right scope for this intervention given the context? And what conditions allow it to spread within that scope? Ask from the start: What behaviors need to take hold for this to work at the target population level in this setting? Who can help them spread, and what social infrastructure needs to be in place? 

As global foreign aid faces unprecedented cuts and humanitarian needs reach all-time highs, we cannot afford to keep testing interventions that aren’t grounded in the realities of people’s lives. We cannot afford to treat 2 billion people as an edge case.

This work would not have been possible without the IRC Syria and Nigeria Country Programs who co-designed, led and implemented these projects, the Climate Innovation Team at Airbel, Vaidehi Uberoi, and Tahirat Omolara Eniola.

The post The Hard Truths Behavioral Science Must Face in Conflict Settings appeared first on Behavioral Scientist.

If you live in America in the twenty-first century you’ve probably had to listen to a lot of people tell you how busy they are. It’s become the default response when you ask anyone how they’re doing: “Busy!” “So busy.” “Crazy busy.” It is, pretty obviously, a boast disguised as a complaint. And the stock response is a kind of congratulation: “That’s a good problem to have,” or “Better than the opposite.”

Notice it isn’t generally people pulling back-to-back shifts in the I.C.U. or commuting by bus to three minimum-wage jobs who tell you how busy they are; what those people are is not busy but tired. Exhausted. Dead on their feet. It’s almost always people whose lamented busyness is purely self-imposed: work and obligations they’ve taken on voluntarily, classes and activities they’ve “encouraged” their kids to participate in. They’re busy because of their own ambition or drive or anxiety, because they’re addicted to busyness and dread what they might have to face in its absence.

Almost everyone I know is busy. They feel anxious and guilty when they aren’t either working or doing something to promote their work. They schedule in time with friends the way students with 4.0 G.P.A.s make sure to sign up for community service because it looks good on their college applications. I recently wrote a friend to ask if he wanted to do something this week, and he answered that he didn’t have a lot of time but if something was going on to let him know and maybe he could ditch work for a few hours. I wanted to clarify that my question had not been a preliminary heads-up to some future invitation; this was the invitation. But his busyness was like some vast churning noise through which he was shouting out at me, and I gave up trying to shout back over it.

Even children are busy now, scheduled down to the half-hour with classes and extracurricular activities. They come home at the end of the day as tired as grown-ups. I was a member of the latchkey generation and had three hours of totally unstructured, largely unsupervised time every afternoon, time I used to do everything from surfing the World Book Encyclopedia to making animated films to getting together with friends in the woods to chuck dirt clods directly into one another’s eyes, all of which provided me with important skills and insights that remain valuable to this day. Those free hours became the model for how I wanted to live the rest of my life.

The present hysteria is not a necessary or inevitable condition of life; it’s something we’ve chosen, if only by our acquiescence to it. Not long ago I Skyped with a friend who was driven out of the city by high rent and now has an artist’s residency in a small town in the south of France. She described herself as happy and relaxed for the first time in years. She still gets her work done, but it doesn’t consume her entire day and brain. She says it feels like college—she has a big circle of friends who all go out to the café together every night. She has a boyfriend again. (She once ruefully summarized dating in New York: “Everyone’s too busy and everyone thinks they can do better.”) What she had mistakenly assumed was her personality—driven, cranky, anxious, and sad—turned out to be a deformative effect of her environment. It’s not as if any of us wants to live like this, any more than any one person wants to be part of a traffic jam or stadium trampling or the hierarchy of cruelty in high school—it’s something we collectively force one another to do.

The present hysteria is not a necessary or inevitable condition of life; it’s something we’ve chosen, if only by our acquiescence to it.

Busyness serves as a kind of existential reassurance, a hedge against emptiness; obviously your life cannot possibly be silly or trivial or meaningless if you are so busy, completely booked, in demand every hour of the day. I once knew a woman who interned at a magazine where she wasn’t allowed to take lunch hours out, lest she be urgently needed for some reason. This was an entertainment magazine whose raison d’être was obviated when “menu” buttons appeared on remotes, so it’s hard to see this pretense of indispensability as anything other than a form of institutional self-delusion. More and more people in this country no longer make or do anything tangible; if your job wasn’t performed by a cat or a boa constrictor in a Richard Scarry book I’m not sure I believe it’s necessary. I can’t help but wonder whether all this histrionic exhaustion isn’t a way of covering up the fact that most of what we do doesn’t matter.

I am not busy. I am the laziest ambitious person I know. Like most writers, I feel like a reprobate who does not deserve to live on any day that I do not write, but I also feel that four or five hours is enough to earn my stay on the planet for one more day. On the best ordinary days of my life, I write in the morning, go for a long bike ride and run errands in the afternoon, and in the evening I see friends, read or watch a movie. This, it seems to me, is a sane and pleasant pace for a day. And if you call me up and ask whether I won’t maybe blow off work and check out the new American Wing at the Met or ogle girls in Central Park or just drink chilled pink minty cocktails all day long, I will say, What time?

But just in the last few months, I’ve insidiously started, because of professional obligations, to become busy. For the first time I was able to tell people, with a straight face, that I was “too busy” to do this or that thing they wanted me to do. I could see why people enjoy this complaint; it makes you feel important, sought-after, and put-upon. Except that I hate actually being busy. Every morning my inbox was full of emails asking me to do things I did not want to do or presenting me with problems that I now had to solve. It got more and more intolerable until finally I fled town to the Undisclosed Location from which I’m writing this.

Here I am largely unmolested by obligations. There is no TV. To check email I have to drive to the library. I go a week at a time without seeing anyone I know. I’ve remembered about buttercups, stink bugs, and the stars. I read. And I’m finally getting some real writing done for the first time in months. It’s hard to find anything to say about life without immersing yourself in the world, but it’s also just about impossible to figure out what it might be, or how best to say it, without getting the hell out of it again.

An ideal human life lies somewhere between my own defiant indolence and the rest of the world’s endless frenetic hustle. My role is just to be a bad influence.

Idleness is not just a vacation, an indulgence or a vice; it is as indispensable to the brain as vitamin D is to the body, and deprived of it we suffer a mental affliction as disfiguring as rickets. The space and quiet that idleness provides is a necessary condition for standing back from life and seeing it whole, for making unexpected connections and waiting for the wild summer lightning strikes of inspiration—it is, paradoxically, necessary to getting any work done. “Idle dreaming is often of the essence of what we do,” wrote Thomas Pynchon in his essay on sloth. Archimedes’s “Eureka” in the bath, Newton’s apple, Jekyll and Hyde and the benzene ring: History is full of stories of inspirations that come in idle moments and dreams. It almost makes you wonder whether loafers, goldbricks, and no-accounts aren’t responsible for more of the world’s great ideas, inventions, and masterpieces than the hardworking.

“The goal of the future is full unemployment, so we can play. That’s why we have to destroy the present politico-economic system.” This may sound like the pronouncement of some bong-smoking anarchist, but it was actually Arthur C. Clarke, who found time between scuba diving and pinball games to write Childhood’s End and think up communications satellites. My old colleague Ted Rall recently wrote a column proposing that we divorce income from work and give each citizen a guaranteed paycheck, which sounds like the kind of lunatic notion that’ll be considered a basic human right in about a century, like abolition, universal suffrage, and eight-hour workdays. The Puritans turned work into a virtue, evidently forgetting that God invented it as a punishment.

Perhaps the world would soon slide to ruin if everyone behaved as I do. But I would suggest that an ideal human life lies somewhere between my own defiant indolence and the rest of the world’s endless frenetic hustle. My role is just to be a bad influence, the kid standing outside the classroom window making faces at you at your desk, urging you to just this once make some excuse and get out of there, come outside and play. My own resolute idleness has mostly been a luxury rather than a virtue, but I did make a conscious decision, a long time ago, to choose time over money, since I’ve always understood that the best investment of my limited time on earth was to spend it with people I love. I suppose it’s possible I’ll lie on my deathbed regretting that I didn’t work harder and say everything I had to say, but I think what I’ll really wish is that I could have one more beer with Chris, another long talk with Megan, one last good hard laugh with Boyd. Life is too short to be busy.

From The New York Times. © 2012. The New York Times Company. All rights reserved. Used under license.

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Landing the Perseverance rover on Mars, working in clean rooms to minimize the microbial bug count, and slogging through hundreds of engineering trade-offs with Swati Mohan, an aerospace engineer at NASA's Jet Propulsion Laboratory. What are the "seven minutes of terror"? And is there evidence of past life on Mars?

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About What It's Like to Be...
In each episode of What It's Like to Be..., bestselling author Dan Heath speaks with someone about what it's like to walk in their (work) shoes. Behavioral Scientist serves as a distribution partner with episodes released every other week. Learn more about the podcast's mission of "slow curiosity" here, and head here to get Dan's reflections on how the mission is going after a year of conversations.

The “Aerospace Engineer” episode of What It’s Like To Be… featured Swati Mohan. It was produced and edited by Matt Purdy. Copyright © 2026 by Dan Heath. All rights reserved.

The post What It’s Like to Be…an Aerospace Engineer appeared first on Behavioral Scientist.