July 04, 2023, #45
In the blog “Data Colada: Thinking about Evidence and Vice Versa” blog authors Uri Simonsohn, Leif Nelson, and Joe Simmons wrote an “introduction to a four-part series of posts detailing evidence of fraud in four academic papers co-authored by Harvard Business School Professor Francesca Gino. […] In the Fall of 2021, we shared our concerns with Harvard Business School (HBS). Specifically, we wrote a report about four studies for which we had accumulated the strongest evidence of fraud.”¹ The authors do not believe that Gino’s authors were involved in collecting the data.
One of the studies with fake data was itself a study on dishonesty. The problem was not with the data collection, but involved tampering afterwards. One goal of the study was to find out whether signing a reporting form at the top or at the bottom made a difference in the honesty of the results. A problem signal was that the data were not sorted correctly. Simonsohn et al. write “There is no way, to our knowledge, to sort the data to achieve this order.”¹ Someone had apparently changed eight observations so that they now gave a very strong result in the predicted direction.
“A little known fact about Excel files is that they are literal zip files, bundles of smaller files that Excel combines to produce a single spreadsheet” and a “calcChain” tells Excel what order to use when processing the data.¹ The authors used the “calcChain to go back and see what this spreadsheet may have looked like back in 2010, before it was tampered with”.¹ The Data Colada blog gives an example of how the manipulation took place. The manipulation was technically clever and not difficult to do.
One result is that “Gino has gone on ‘administrative leave’, and the name of her chaired position at HBS [Harvard Business School] is no longer listed.”¹ The blog also “heard from some HBS faculty that Harvard’s internal report was ~1,200 pages long…”¹ Assuming all the evidence is true, key questions remain: why would a person with a safe job and good reputation falsify data, and what in our academic incentive structure makes the temptation worthwhile?
NOTE: Data Colada has three other articles about data falsification involving Francesca Gino:
1: Lief Nelson, Uri Simonsohn, and Joe Simmons, ‘[109] Data Falsificada (Part 1): “Clusterfake”’, Data Colada, 17 June 2023, http://datacolada.org/109.