Linkpost: A Post Mortem on the Gino Case

Link post

As a followup to my previous linkpost to the New Yorker article covering the Ariely and Gino scandals, I’m linking this statement by Zoe Ziani, the grad student who first discovered inconsistencies in Gino’s papers. Here she gives a blow-by-blow retelling of her experience attempting to uncover fraud, as well as telling a fairly harrowing story about how higher-ups in her organization attempted to silence her.

I find this story instructive both on the object-level, and as a case study both for a) how informal corrupt channels tries to cover up fraud and corruption, and b) for how active participation is needed to make the long arc of history bend towards truth.

In her own words:

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Disclaimer: None of the opinions expressed in this letter should be construed as statements of fact. They only reflect my experience with the research process, and my opinion regarding Francesca Gino’s work. I am also not claiming that Francesca Gino committed fraud: Only that there is overwhelming evidence of data fabrication in multiple papers for which she was responsible for the data.

On September 30th, 2023, the New Yorker published a long piece on “L’affaire Ariely/​Gino”, and the role I played in it. I am grateful for the messages of support I received over the past few weeks. In this post, I wanted to share more about how I came to discover the anomalies in Francesca Gino’s work, and what I think we can learn from this unfortunate story.

What is The Story?

How it all began

I started having doubts about one of Francesca Gino’s paper (Casciaro, Gino, and Kouchaki, “The Contaminating Effect of Building Instrumental Ties: How Networking Can Make Us Feel Dirty”, ASQ, 2014; hereafter abbreviated as “CGK 2014” ) during my PhD. At the time, I was working on the topic of networking behaviors, and this paper is a cornerstone of the literature.

I formed the opinion that I shouldn’t use this paper as a building block in my research. Indeed, the idea that people would feel “physically dirty” when networking did not seem very plausible, and I knew that many results in Management and Psychology published around this time had been obtained through researchers’ degrees of freedom. However, my advisor had a different view: The paper had been published in a top management journal by three prominent scholars… To her, it was inconceivable to simply disregard this paper.

I felt trapped: She kept insisting, for more than a year, that I had to build upon the paper… but I had serious doubts about the trustworthiness of the results. I didn’t suspect fraud: I simply thought that the results had been “cherry picked”. At the end of my third year into the program (i.e., in 2018), I finally decided to openly share with her my concerns about the paper. I also insisted that given how little we knew about networking discomfort, and given my doubts about the soundness of CGK 2014, it would be better to start from scratch and launch an exploratory study on the topic.

Her reaction was to vehemently dismiss my concerns, and to imply that I was making very serious accusations. I was stunned: Either she was unaware of the “replication crisis” in psychology (showing how easy it is to obtain false-positive results from questionable research practices), or she was aware of it but decided to ignore it. In both cases, it was a clear signal that it was time for me to distance myself from this supervisor.

I kept digging into the paper, and arrived at three conclusions:

The paper presents serious methodological and theoretical issues, the most severe being that it is based on a psychological mechanism (the “Macbeth Effect”) that has repeatedly failed to replicate.

The strength of evidence against the null presented in study 1 of the paper made it extremely unlikely that the result was p-hacked: It is statistically implausible to obtain such a low p-value under the null, even when using researchers’ degrees of freedom.

Francesca Gino had many other papers that appeared equally implausible (i.e., untrustworthy psychological mechanisms leading to large effects with very low p-values).

It was at this point that I started suspecting that part of the evidence presented in CGK 2014 was not just p-hacked but based on fabricated data[...]

See more at: https://​​www.theorgplumber.com/​​posts/​​statement/​​