Harvard professor Francesca Gino was accused of faking data. Now her million-dollar empire is crumbling — and scholars are eyeing who’s next.

To be a true superstar in behavioral science, you need to achieve a few things.

A TED Talk, obviously. Best-selling books with bright covers filled with pop-science buzzwords like “predictable irrationality” or “expecting better.” Thousands upon thousands of followers on Twitter and LinkedIn. Tenure, ideally at a top business school such as Harvard or Wharton.

It’s not enough to just teach anymore. These professors want to build “an empire,” Syon Bhanot, an associate professor of economics at Swarthmore College, said.

Francesca Gino ranks among the elite few who tick all the boxes. From 2019 to 2020, Gino raked in more than $1 million as a professor at Harvard Business School, studying trendy topics such as political correctness and why people lie. One of her lectures was even repackaged as Alaska Airlines in-flight entertainment. 

But now, Gino’s empire is crumbling.

In mid-June, news broke that Harvard had placed Gino on administrative leave after an internal investigation into allegations that she falsified research data. The next day, Data Colada — a blog run by three professors and known for exposing shoddy research — published its first of four posts saying it had found evidence of fraud in Gino’s work. Data Colada reported that Harvard’s still unreleased internal report on Gino was roughly 1,200 pages.

“We believe that many more Gino-authored papers contain fake data,” the Data Colada professors wrote. “Perhaps dozens.”

The allegations could destroy years of research and damage dozens of careers, as Gino has coauthored papers with more than 100 people. Even as Gino’s peers condemn her, many say her actions aren’t all that surprising in an environment where professors are pitted against one another in a mad dash to publish the next “Freakonomics.” 

It’s possible “these people don’t care and never cared about the science,” Michael Sanders, a professor of public policy at King’s College London, said. “They talk about science, and they talk about experiments, and they sort of wrap themselves in the fabric of the scientific method — just as a way of selling stuff.”

Gino did not respond to requests for comment. On August 2 (two days after this article was first published), she filed a 100-page, $25 million defamation lawsuit against the Data Colada researchers and Harvard.

“I want to be very clear: I have never, ever falsified data or engaged in research misconduct of any kind,” Gino wrote on her LinkedIn page. “Today I had no choice but to file a lawsuit against Harvard University and members of the Data Colada group, who worked together to destroy my career and reputation despite admitting they have no evidence proving their allegations.”

Gino grew up in a tiny Italian mountain town of 3,000 called Tione di Trento. She attended college at the nearby University of Trento before earning her master’s and Ph.D. at the Sant’anna School of Advanced Studies in Pisa. While completing her Ph.D. in 2002, Gino went to Harvard as a visiting fellow. She was supposed to stay for six to nine months, but instead, as she wrote earlier this year on LinkedIn, “I never left.”

Gino conducted her postdoctoral research at Harvard and then went on to teaching gigs at Carnegie Mellon University and the University of North Carolina at Chapel Hill. Soon, she was receiving job offers from top universities across the US, including Harvard Business School. By the time she was 32, she was back at HBS as an associate professor and “already this superstar,” said a former collaborator who spoke on condition of anonymity to avoid professional repercussions.

Gino’s students at Harvard loved the motorcycle-obsessed mother of four. She was fun, a professor who made pasta from scratch and took improv classes with her husband, Greg Burd, an engineer. (She wrote about the classes in her book “Rebel Talent” as an example of embracing the unexpected.) Gino racked up honors including the HBS faculty award in 2015, a place on Poets&Quants’ list of the top 40 business professors under 40 the same year, and a spot on the Thinkers50 list — also known as the “Oscars of management thinking” — in 2017, 2019, and 2021. People who knew Gino were baffled by how she managed to fit everything into her schedule.

“She was a bit bionic,” her former collaborator said. “There’s no way I could have a research conversation if I haven’t slept the night. But she could.”

Gino is prolific. She specializes in intuitive but intriguing findings: Shaking hands makes people more likely to agree on deals; networking makes people feel so dirty that they develop a sudden interest in cleaning products. A 2012 study she coauthored that found signing honesty pledges at the top of documents reduced cheating earned write-ups in Wired and Forbes and persuaded governments from the US to Guatemala to update financial forms.

I didn’t think it was fraud, but I thought it was bullshit.

Gino easily translates her research for a nonacademic audience, offering personal stories alongside data and historical studies. A single chapter in “Rebel Talent” rattles off anecdotes from Napoleonic battles, a study of a tomato-processing company, and Gino’s decision to pair red Converse with a Hugo Boss suit because it made her students think she was more important. Her work spans disciplines, with Gino coauthoring research on subjects such as the dynamics of surgical teams and humblebragging. Gino has published more than 135 studies, and her citations exceed 32,000, according to Google Scholar. She is so productive, Swarthmore College’s Bhanot said, it seems as if everyone in the field personally knows 20 people who’ve written something with Gino.

Her coauthors were full of praise. “She was a bright, eager, hardworking collaborator,” Maurice Schweitzer, a behavioral-economics professor at Wharton who published eight studies with Gino, said.

But some felt Gino prioritized speed over substance. “I didn’t think it was fraud, but I thought it was bullshit,” said Simine Vazire, a professor of psychology, ethics, and well-being at the University of Melbourne. Sanders of King’s College London said Gino was highly respected but her findings tended to be “quite cute.” “They’re sort of designed to be turned into pop books or TED Talks,” he added.

“Cute” studies paid off for Gino. In the 2019-20 academic year, she was one of the highest-compensated employees at Harvard, earning more than $1 million. (Harvard professors on average make $274,900. The minimum salary for a research assistant at the university is $48,382, according to the school.) She developed a lucrative side gig giving speeches and leading corporate trainings for companies including Disney and Goldman Sachs. Gino’s speaking fees were in the tens of thousands of dollars, with clients paying for her to travel across 40 states and 30 countries, according to the Lavin Agency. In “Rebel Talent,” Gino recalls flying from Boston to New York at 6:36 a.m. to teach a class of 40 executives about decision-making — then returning on the 5 p.m. flight.

“We can look back and say, ‘Oh, I should have known,'” Schweitzer said. “I don’t think that there were obvious signs at the time.”

Schweitzer added: “She has, like, 150 collaborators. I think people were working in good faith, assuming things were right.”

The first cracks appeared in 2020.

Eight years after publishing her 2012 paper about honesty pledges, Gino and her coauthors published a follow-up saying they’d failed to replicate the results and no longer stood by the original study.

As part of the follow-up paper, the coauthors posted their 2012 data for the first time, and a group of researchers began digging through the spreadsheets. In August 2021, Data Colada reported that the researchers found “beyond any shadow of a doubt” that the 2012 data had been fabricated. Data Colada’s founders — the professors Uri Simonsohn, Joe Simmons, and Leif Nelson — published an analysis, based on the researchers’ work, focusing on one of the study’s three experiments: odometer readings from an auto-insurance company. Data Colada found that the raw data showed clear anomalies, such as a distribution infinitely more likely to be produced by a random-number generator than actual people.

Only one of the five coauthors had handled the odometer data: Dan Ariely, a Duke University professor who’s so well known that a coming NBC drama is partly inspired by his career. Ariely acknowledged the data was fake but denied fabricating it himself, implying in a 2021 interview with BuzzFeed News that the insurance company might have been responsible — an accusation the insurance company has vigorously denied. The other four coauthors said they played no part in collecting the data. All five, Ariely included, requested the paper be retracted in light of Data Colada’s analysis.

Dan Ariely, a Duke University professor who collaborated with Francesca Gino, has become so famous that a coming NBC drama is loosely based on his career. Chris Goodney/Bloomberg via Getty Images

Privately, the Data Colada professors had further concerns. A few months after dropping the Ariely bombshell, they reached out to Harvard. Gino, they said, appeared to have fabricated data in the 2012 paper, as well as in three additional studies. Harvard launched an internal investigation, and rumors about Gino began to spread. Anonymous posters on the forum Economics Job Market Rumors — a sort of 4chan for economists — began speculating about her experiments. “Lots of output, lots of it questionable,” one person wrote in 2022. “Anyone notice she never shares her data?” another wrote. “Wtf is going on in b-schools?” a third commented.

Harvard placed Gino on leave in June this year, The Chronicle of Higher Education first reported. (The university declined to comment on Gino, who remained on academic leave as of late July.) Soon after, Data Colada ran an article alleging that Gino tampered with data in at least one of her honesty-pledge experiments. Eight data points appear to be out of order on Gino’s spreadsheet, Data Colada said, adding that their placement could be explained only by someone editing the data to make the results appear significant. It said: “Two different people independently faked data for two different studies in a paper about dishonesty.”

Over the next two weeks, Data Colada released an analysis of three additional studies. It said Gino appeared to have falsified data as recently as 2020. For people like Nick Brown, a British data vigilante of sorts, the revelations were exciting. It helped that Brown knew the exposé was overdue, he said — two separate people had reached out to him with concerns about Gino in the past year.

“I just kind of got out a big box of popcorn,” Brown said.

But for many, the allegations against Gino were upsetting. “It feels like a violation of a lot of the things we all hold dear,” Jeff Lees, one of Gino’s former advisees at HBS, said.

Worse, Lees said, “it’s sad because it’s not hard to imagine why someone does it.”

To get tenure — a lifetime appointment at a university, which is the ultimate goal — you need as much research as you can get published in A-level journals. Journals want studies that break ground and earn breathless media coverage. So imagine the stress when a researcher has committed a year or two of work and spent tens or hundreds of thousands of dollars on a project only for the results to come back as insignificant.

It’s easy, said Lees, to picture someone like Gino saying, “Let me just hit a few buttons and make it look true and we can all be happy.”

Gino conducted her honesty-pledge study at the University of North Carolina at Chapel Hill in 2010. At the time, she was up for a job at HBS.

Throughout her career, Gino set a bar for productivity. Many researchers publish two to three papers a year; Gino published 16 articles in 2015 alone. Scholars battled to ascend to what Lees called the “1% of academia”: tenure, the best-selling books, the corporate talks. Meanwhile, Gino barely seemed to break a sweat.

“Who doesn’t want to get paid to just give a speech? Who doesn’t want the public to see their work?” Lees said. “When you think about ascending the prestige hierarchy, that is one of the incentives to potentially commit fraud.”

Gino is far from the first behavioral-science professor to be accused of less-than-ethical data practices. There’s Ariely, who shrugged off the 2020 scandal (among others) and continued teaching at Duke. Brian Wansink’s food-psychology studies into obesity and weight loss were so influential that he developed the US Department of Agriculture’s 2010 Dietary Guidelines for Americans; in 2018, he was fired from Cornell University after dozens of inconsistencies were found in his studies. HBS’s Amy Cuddy’s power-pose paper persuaded millions of women to adopt a Wonder Woman-esque stance before stressful meetings; Cuddy left academia in 2017 after other researchers, including Data Colada, accused her of massaging her data.

Amy Cuddy’s research became so well known that she spoke at Marie Claire’s “Power Women Lunch” in 2013, where attendees included the actor Allison Williams. Astrid Stawiarz/Getty Images for Marie Claire

Simonsohn, Simmons, and Nelson founded Data Colada in 2012 out of their shared conviction that common research techniques allowed for journals to publish countless false-positive studies. It was accepted at the time that academics tinkered with their data, adjusting their controls or cherry-picking outliers. Top professors published papers that skeptics saw as immaterial or downright absurd, including a study that supposedly proved extrasensory perception was real. For data detectives, the only way to bring objectivity back into science is to call out shoddy papers and demand more data transparency. 

“There are no police, and there’s no prosecutors, so we are kind of the vigilantes,” Brown said.

Data vigilantes’ efforts have brought a new level of rigor to data collection and analysis. Despite their contributions to the field, however, some remain skeptical. A post on Data Colada or a tweet from Brown is like a bomb going off in the behavioral-science world. When Data Colada published its criticism of Cuddy, “people were sending me emails like I was dying of cancer,” she told The New York Times in 2017. Many researchers are privately terrified of being falsely accused by the “data cops,” one scientist said. But no one wants to criticize them because no one wants a target on their own back — including this individual, who was granted anonymity for this reason.

“Batman is a vigilante,” the scientist said. “So is the Joker.”

The terror arises, in part, because there are no clear guidelines about what, exactly, merits a takedown. Discussing the allegations that Gino falsified data is seen almost unanimously as fair game, especially in light of Harvard putting her on leave. People expressed more mixed feelings toward disgraced researchers such as Cuddy, who failed to replicate her findings but did not fake her data. Some see the mockery of Cuddy, in particular, as representative of a bigger problem: Women and people of color in academia are held to a different standard than white men. Cuddy, who continues to work with corporate clients, is writing a book about bullies based on her experience.

Even Data Colada’s biggest supporters don’t want a blog to be the primary stopgap for bad data. Vazire, the University of Melbourne professor, said that data detectives’ efforts should be compensated and backed by institutional support. Academics have called for journals to dedicate more space to replicating studies or to make it mandatory for researchers to include their data.

Some changes are in the works. Journals have adopted policies such as result-blind peer reviews, allowing for more null results to be published. It’s becoming more common for researchers to share their datasets. There’s no way that the falsified data from the 2012 honesty-pledge study would have been exposed if it hadn’t been logged publicly for the first time when the 2020 follow-up was published.

Even with new safeguards, the pressure to publish clicky, media-friendly studies remains.

“The honest researchers just get kind of pushed out because they’re not willing to manipulate or do studies on a specific subtopic that hits,” Swarthmore College’s Bhanot said. “To get a lot of Twitter followers, to get a public-facing book that sells a lot, to get a bunch of TED Talks — you have to have buzzy insights that distill nicely into a 60-second sound bite.”

Perhaps the best way to understand why someone would fake data is to turn to Gino’s own research. While people outside academia have relished the irony of a “dishonesty expert” being accused of fraud, Gino’s peers tend to think her field of study makes perfect sense. When discussing Gino with Insider, multiple people brought up the idea of “me-search” — that researchers gravitate to topics that are of personal interest to them. “We’re our own therapists, in a sense,” Gordon Pennycook, a behavioral-science professor, said.

In a study about “contagious dishonesty” that Gino coauthored with Ariely, the researchers found that students were more likely to cheat if they saw someone they believed to also attend their university cheating. A 2008 paper found people cheated more in the presence of abundant wealth, provoked by feelings of envy. A 2014 study found that dishonesty led to greater creativity, saying liars felt unconstrained by rules. (Harvard asked the journal to redact the study in June, citing discrepancies between the published datasets and the earliest-known versions of the data. Gino’s counsel told the journal that the retraction was necessary but that “there is no original data available.”)

“You might think that somebody who researches dishonesty is obsessed with the truth,” Pennycook added. “But in this case, maybe it’s the other way.”

You change a couple rows of a spreadsheet, and then for the next 10 years, people are chasing ghosts.

The allegations against Gino have already cast a long shadow over the field. An effort is underway to audit each of Gino’s papers, called the “Many Co-authors” project, which hopes to identify a standardized process to deal with any studies found to be fraudulent. Since June, journals have announced plans to retract three of Gino’s papers, in addition to the honesty-pledge paper. Sanders said the only thing left to discover was how many times she forged data — just the four times exposed by Data Colada or in “20, 50, 100 cases.”

For collaborators, it’s a stressful and infuriating time. When a paper is retracted, the research is erased, and all related citations are lost. For junior scholars, this can mean a significant chunk of their professional achievements evaporating overnight. The anger extends to those whose studies are left unscathed. The collaborator who spoke on condition of anonymity said she was frustrated for years trying to keep up with Gino. Then, when she heard that Gino had been accused of “cheating,” she was furious. “You’re like, excuse me?”

Others who attempted to build on Gino’s studies are grappling with having wasted time, money, and energy. Both Sanders and Bhanot attempted to apply the honesty-pledge study on a much larger scale: Bhanot surveying people borrowing money online and Sanders studying Guatemalan taxpayers. Neither found any influence in having participants sign the pledge. In Sanders’ case, the Guatemalan government spent a quarter of a million dollars conducting the study in an experiment that spanned 627,242 people.

“You change a couple rows of a spreadsheet, and then for the next 10 years, people are chasing ghosts,” Bhanot said. 

Some researchers see Harvard putting Gino on leave as evidence of science prevailing: Researchers raised concerns based on public data, and the university took action. Others see her story as a message of how broken the system is. Gino thrived for well over a decade. But her mistakes were too easy to spot, and her profile was too high for her to go unpunished. Few think she’ll be the last one to go down. Sanders said it could be like clockwork waiting to see whom the data detectives brought in next.

“It’s hard to know how big the iceberg is underneath the surface of water,” Bhanot said. “You just see the few cases of the sloppiest folks, or the biggest names, or the most famous people fall the hardest.”

“But how many people,” he added, simply “hide their tracks better?”

August 3, 2023: This story was updated with news of Gino’s lawsuit against Harvard and Data Colada.