Harvard Professor Under Scrutiny for Alleged Data Fraud

Harvard University professor Francesca Gino, whose research frequently focused on dishonesty, is under scrutiny for allegedly fabricating data in at least four studies. The news was first reported by Stephanie M. Lee in The Chronicle of Higher Education on Friday, June 16. 

A day after Lee’s report, a trio of scientists—Uri Simonsohn of the Esade Business School, Joseph Simmons of the University of Pennsylvania, and Leif Nelson of the University of California, Berkeley—published the first of four posts detailing alleged data fraud by Gino on their website Data Colada.

The news sent shockwaves through the behavioral science community. By all appearances Gino has been a successful scholar—winning awards for her research and teaching, serving on the editorial board for a handful of well-respected journals, writing two popular books, and consulting and speaking at a number of large companies. 

“There’s so many of us who were impacted by her scholarship, by her leadership in the field, and as a co-author, as a colleague, it’s deeply upsetting,” Maurice Schweitzer, a professor at the University of Pennsylvania and coauthor with Gino on eight papers, said in The Chronicle of the Higher Education.

Several of her coauthors told me over the phone and through email that they were shocked and devastated by the news. (They requested anonymity while they gather more information about the situation.) Syon Bhanot, who isn’t a coauthor, recalled the time and effort he spent a few years ago trying to replicate one of the studies, whose data integrity has now been called into question. (Disclosure: Bhanot is an advisor to Behavioral Scientist.) And one of Gino’s former advisees at Harvard called the allegations “disturbing,” but also said he “never experienced or suspected fraud.” 

While the news broke recently, it seems to be the culmination of a multiyear inquiry into Gino’s research by Harvard and other scientists in the field.

“In 2021, we and a team of anonymous researchers examined a number of studies coauthored by Gino, because we had concerns that they contained fraudulent data,” Simonsohn, Simmons, and Nelson wrote on Data Colada, the website where they write about research practices in behavioral science. The website, founded in 2013, has played a significant role in unearthing shoddy research practices, like p-hacking, and they’ve also revealed other instances of fake data.  

“In the Fall of 2021, we shared our concerns with Harvard Business School,” they said. “Specifically, we wrote a report about four studies for which we had accumulated the strongest evidence of fraud. We believe that many more Gino-authored papers contain fake data. Perhaps dozens.”

Gino is now on administrative leave from Harvard, according to the university’s website. A Harvard spokesperson declined to comment in response to my email.

When I reached out to Gino for comment, she directed me to a brief statement published on LinkedIn. “As I continue to evaluate these allegations and assess my options, I am limited into what I can say publicly. I want to assure you that I take them seriously and they will be addressed,” she wrote. “There will be more to come on all of this.” (Disclosure: Gino has served as an advisor to Behavioral Scientist.

None of Gino’s coauthors, who number 148 by Data Colada’s count, has been implicated in the alleged fraud. “To the best of our knowledge, none of Gino’s co-authors carried out or assisted with the data collection for the studies in question,” wrote Simonsohn, Simmons, and Nelson.

The response from her coauthors and others in the field has been remarkably swift, though many details remain unknown publicly. Within two weeks of the allegations surfacing, the papers in question are in the process of being retracted by their respective journals and her coauthors have organized an initiative to evaluate the research she was involved in (more on each below). These actions indicate that there may be merit to the allegations, but with Gino and Harvard yet to put out statements with any substance, a number of questions remain unanswered.

The studies in question

Data Colada reported evidence of suspected fraud in four individual studies, each a part of a different multistudy paper, which were published between 2012 and 2020.

The four studies in question are:

1. Study 1 in “Signing at the Beginning Makes Ethics Salient and Decreases Dishonest Self-Reports in Comparison to Signing at the End” by Lisa Shu, Nina Mazar, Francesca Gino, Dan Ariely, and Max Bazerman, published by the Proceedings of the National Academy of Sciences (PNAS) in 2012. 

This paper was already retracted in 2021 due to data anomalies discovered by an anonymous set of researchers (published by Data Colada), after a 2020 replication attempt failed and the original 2012 data was posted. The alleged fraud by Gino in Study 1 represents the second time this paper has had a study called into question for fabricated data.

2. Study 4 in “The Moral Virtue of Authenticity: How Inauthenticity Produces Feelings of Immorality and Impurity,” by Francesca Gino, Maryam Kouchaki, and Adam Galinsky, published by Psychological Science in 2015.

3. Study 4 in “Evil Genius? How Dishonesty Can Lead to Greater Creativity,” by Francesca Gino and Scott Wiltermuth, published by Psychological Science in 2014. 

4. Study 3a in “Why Connect? Moral Consequences of Networking with a Promotion or Prevention Focus,” by Francesca Gino, Maryam Kouchaki, and Tiziana Casciaro, published by Journal of Personality and Social Psychology in 2020.

The evidence

Data Colada investigated the data file from each study. In three cases, they retrieved the data from the Open Science Framework (an online science management tool developed by the Center for Open Science that emerged in response to the replication crisis), where researchers post materials related to their research, including data, code, analysis plans, and results. In one case, Gino provided Data Colada with the data directly. 

Across the four studies, Simonsohn, Simmons, and Nelson report anomalies that they say indicate fraud. This includes data sorted in an order only possible through manual editing, implausible responses, and a mismatch between participants’ survey and text-based responses. When they looked into each of these anomalies further, they report finding instances where participants’ experimental conditions or responses were changed to provide support for the authors’ hypothesis.

In one case, participants with extreme responses to an honesty task appear to have had their experimental conditions changed to artificially lend support to the authors’ hypothesis that signing at the top of a document produces more honest responses than signing at the bottom.

In another case, the data file listed 20 participants’ class year as “Harvard,” rather than “junior,” “third year,” or “2016,” which gave the Data Colada group pause. When they looked into these responses, they found all but one of the responses were at the extreme end of a scale and in a direction that supported the authors’ hypothesis. 

In a study on creativity, Data Colada’s analysis suggests that the number of creative ideas generated by several participants who cheated on a coin-toss earlier in the study was artificially increased to support the authors’ hypothesis that cheaters were more likely to be creative. 

For a full look into Data Colada’s analysis, please see the series of posts, which correspond to the four studies above, respectively: post 109, post 110, post 111, and post 112

An additional indication of fraud comes from Lee’s first story. She reported that Max Bazerman, a professor at Harvard Business School, and a coauthor on the original 2012 paper and 2020 replication, received “a 14-page document with what he described as ‘compelling evidence’ of data alterations” in the 2012 paper. 

“According to Bazerman, Harvard is recommending to the Proceedings of the National Academy of Sciences that it update the study’s retraction notice to reflect its new concerns,” Lee reported. 

Lee also said in a tweet that Psychological Science plans to retract both articles in question, which the editor-in-chief of the journal, Patricia Bauer, confirmed to me in an email. 

Update July 6, 2023: Psychological Science has retracted both articles: “The Moral Virtue of Authenticity: How Inauthenticity Produces Feelings of Immorality and Impurity” (read the retraction note) and “Evil Genius? How Dishonesty Can Lead to Greater Creativity” (read the retraction note). In both cases, the retraction reads that the Harvard University’s Research Integrity Office reached out to the journal editor after finding anomalies in the data, which the respective retraction notes explain further. The authors for each paper agreed to retract the article.

Each retraction ends with the same statement from Gino’s counsel: “Counsel for the first author informed the journal that whereas Dr. Gino viewed the retraction as necessary, she disagreed with references to original data, stating that ‘there is no original data available’ pertaining to the research reported in the article.”

In the case of the fourth study, “A retraction is slated to be published in the September issue of the Journal of Personality and Social Psychology,” read a statement emailed to me from the American Psychological Association’s publisher, Rose Sokol. “At this time, we believe this to be an isolated incident. However, we continue to be in touch with the institution and if we have reason to consider retracting other articles, we will take appropriate steps.”

How Gino’s coauthors are responding

A number of Gino’s coauthors have come together in an initiative called the Many Co-authors Project to collectively reevaluate the studies in which she was involved. 

Several of Gino’s coauthors told me the project will assess whether there are other instances of potential data fraud, where coauthors no longer have confidence in a finding and may need to issue a retraction, and where authors stand by the research.

Not only is this effort potentially necessary to correct the scientific record, they told me, it’s also crucial for mitigating potential damage to graduate students and professors earlier in their careers who are not implicated, yet associated with the allegedly fraudulent work. 

What studies will stand up to review by the Many Co-Authors Project? The answers are likely to come in months, rather than weeks or days, one coauthor told me.

Open questions

This case of alleged fraud has launched a range of conversations among scientists: some about the case itself, others broader in scope, including how to improve research methods, potential issues with “data policing,” and preventing future fraud.

With regard to the case itself: Will charges of fraud stand up to further scrutiny? Are there alternative explanations? Will Harvard make any of its inquiries publicly available? How will Gino respond? 

When it comes to improving research methods, the conversations have ranged from specific suggestions to more philosophical thoughts about how science is conducted. For instance, some have suggested that data collection platforms, like Qualtrics, should validate raw data. Could that become a new standard for behavioral science research? And more broadly, do researchers change the processes and norms for how they structure their joint projects? How do they balance the trust necessary for collaboration with the skepticism necessary for rigorous science?

Others have surfaced potential issues with “data policing.” Who decides whose work is scrutinized? How are claims of fraud validated? “We need to be as critical and skeptical of the critiques as we are of the literature itself,” Joe Bak-Coleman, an associate research scientist at the Columbia School of Journalism, commented on his website.

Katy Milkman, a professor at the Wharton School of business, told the Financial Times: “I’ve had more conversations in the last week about how we can make our science more robust and fraud-proof than I’d had in the past year. So I anticipate very positive side effects of these revelations.” (Disclosure: Katy Milkman directs Behavioral Change for Good, which has provided financial support to Behavioral Scientist.)

But how much good could come from this situation rests in part on knowing more about what happened, and how and why. And that requires transparency from those who might be reluctant to provide it, namely Gino and Harvard. 

It’s uncommon for U.S.-based institutions to make their reports public, Brian Nosek, the cofounder and executive director for the Center for Open Science, told me over the phone. But when there has been transparency from institutions in the past it’s been helpful.

“I’ve been more impressed over the years by the European institutions being more transparent and making their reports publicly available,” he said. “I think that has been a service to the field and to all of those that were swept up into these events.”

“It’s my disposition to favor transparency,” Nosek said, “in part for fairness of all of those that are involved, and also as a learning opportunity for how it is that these things occur.”