The chemistry tubes have been abuzz lately with the ongoing saga of the Bengu Sezen misconduct investigation. For excellent coverage, go check out ChemBark’s posts. It is a disturbing tale of years of data fabrication, fraud, sabotage, evasion, and perjury on the part of a chemistry graduate student at Columbia University, resulting in the retraction of six papers from the laboratory of her adviser, Professor Dalibor Sames.
Early on, it became evident that Sezen’s chemistry was peculiarly ‘finicky’. Other students in the lab attempted to use the reactions she’d developed – without success. Soon other labs were contacting Sames with similar quandaries. What was the secret that everyone was missing? Eventually – after publication of six papers and Sezen’s dissertation defense – it became clear that there was no secret aside from an elaborate con.
It would perhaps be a relief to leave the blame solely at Sezen’s feet, to believe that Professor Sames was duped, to be able to say that Sames was but one victim of an incredible con game. Sadly it appears this is not the case. There is nothing to suggest that Sames was complicit in the data fabrication, but he created a situation that allowed it to continue and expand. In the face of overwhelming evidence, Sames continued to stand behind Sezen’s work – until a grad student set up a sting operation that left little doubt Sezen had sabotaged the experiment to cover her tracks. Among the documents recently released under Freedom of Information Act requests, the Office of Research Integrity investigation reveals that two graduate students were dismissed by Sames and a third switched labs. Although a redacted someone (I would guess Sames) claims other circumstances contributed to the dismissals, there is an obvious implication that they were due in large part to the students’ failures to reproduce Sezen’s results.
This is where some fault falls on Sames. Things rarely work exactly the same way every time, but there has to be some degree of reproducibility. From the description of what happened in the Sezen case, a dichotomy was established, in which a professor placed absolute faith in one person and viewed failure of others as utter incompetence. This breeds an environment of stress, fear, and contempt. Sezen’s actions are inexcusable, but it is perhaps not so difficult to understand the motivation to provide the expected results.
It is unreasonable to expect a lab head to review every piece of data, to keep watch over every experiment. Not only is it impractical, but also an environment where “Big Brother is watching” would be detrimental to morale and the creative process of science. Trust and integrity are central elements to the success of a laboratory. But trust between scientists, no matter the stage, must not be blind and should never come at the expense of skepticism and sensibility. We should welcome the attempts of others to repeat and build upon our work. And when they cannot, we should be willing to explore why, not with the expectation fraud at every turn, but in the hope of improving our research and advancing the field.
THanks for the good links! I hadn’t seen those ones, just the story itself.
I think that the “golden one” scenario, where one person is chosen as the “truth giver” and when others can’t reproduce the data is the dangerous one. Sure enough, there are times when the experienced one can get good results when an inexperienced (techincal) person can’t but there has to be some sort of “let other’s test and see if they can do it”. If noone else can reproduce it, I’d say it’s not a good assembled data – regardless of fraud or not. You should be able to get same results by someone else (even if it means you tell them the tricks and tweeks “blow up the lungs from the side and wash with just a little” etc…)
I agree completely with this post. Regarding verification of results, both advisors and students need to “give a little”. Advisors need to recognize that quality control is important and spend some time on it. Students need to recognize that they shouldn’t take it personally when the boss asks someone else to repeat a couple experiments.
I agree and have seen it IRL far too often. Senior muckity muck advisors making new grad students lives hell for not reproducing other data….others squashing students for not preproducing work for the PIs own ‘hands’ (dreams?). This, my friends, is why you want to reproducibe essential data during a rotation and then work on a project where ANYTHING you get will be interesting and novel. The best science questions lead you down a novel road where the opposite of what you were thinking always ends up happening. You just need a PI who is willing to go there, a student willing to think hard about interpretation and a happy lab where no one is killed for being the bearer of bad news. Oh, and all this needs to happen at a time where funding is at an all time low given the numbers of scientists we are cranking out.