Two weeks ago, Pamela Roland from UC Davis retracted a Science paper originally published in 2009. She gave her perspective on the events leading to the retraction in a Scientific American blog post. Here a post-doc in her lab gives his side of the story, emphasising the importance of teamwork, honesty, and willingness to speak up at every level of the academic hierarchy.
Benjamin Schwessinger obtained his PhD at The Sainsbury Laboratory, under GARNet Advisory Committee member Cyril Zipfel. He joined Pamela Roland’s UC Davis group in 2011. This post is an edited version of DO mind the scientific skeletons in the closet, originally published on the blog he co-hosts with Ksenia Krasileva, a postdoctoral fellow in Jorge Dubcovskey’s lab.
Yet another Science paper retracted today. Nothing much new unfortunately – except that for me and my colleagues this was not just another example of non-reproducible work. We planned our research projects around it. So here are my thoughts about this, and just in time for Halloween.
There has been much talk about the problem of reproducibility of data and the rise in retractions. The discourse is mostly centered around the perpetrators and the negative impact this sloppy or knowingly flawed science has on the industry and the perception of scientific endeavor in society: Who did this awful study? What reviewer did not catch this missing control, the sloppy stats? Why don’t they admit their mistake? What’s wrong with peer-review? Well, much is wrong with the industry, and many people have great ideas about how to tackle some of these issues.
What is usually missed from the discussion is the impact such dubious science can have on young, early career scientists. What do you do if you come to a famous (or not so famous) lab, you get a project, which is based on fantastic data and high impact publications, but you cannot reproduce it? How do you approach this issue? What does it mean for you and your career if your project goes to shreds because it’s based on bad data? Do you get another chance? Will you be forever associated with this flawed data and your reputation damaged? Will you get so disillusioned with science to the point that you leave academia? Do you try to fix the problem or silently move on? Do you tell the boss and explain your situation? Or is it you? Can you just not get it to work? Can it really be that this is all wrong? Why cannot I reproduce this data? And the questions go on and on … I think everyone can appreciate the complexity of the issue. Many people I talked to had their own experience to share.
Here is what’s frightening: sloppy science and misconduct, I thought, is something you read about in journals and not something I would experience myself. This would never affect me or close friends in other labs, who are all great scientists in my eyes. I was wrong. (more…)
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