In this post, I’m continuing my discussion of the excellent article by Yudhijit Bhattacharjee in the New York Times Magazine (published April 26, 2013) on social psychologist and scientific fraudster Diederik Stapel. The last post considered how being disposed to expect order in the universe might have made other scientists in Stapel’s community less critical of his (fabricated) results than they could have been. Here, I want to shift my focus to some of the harm Stapel did beyond introducing lies to the scientific literature — specifically, the harm he did to the students he was supposed to be training to become good scientists.
I suppose it’s logically possible for a scientist to commit misconduct in a limited domain — say, to make up the results of his own research projects but to make every effort to train his students to be honest scientists. This doesn’t strike me as a likely scenario, though. Publishing fraudulent results as if they were factual is lying to one’s fellow scientists — including the generation of scientists one is training. Moreover, most research groups pursue interlocking questions, meaning that the questions the grad students are working to answer generally build on pieces of knowledge the boss has built — or, in Stapel’s case “built”. This means that at minimum, a fabricating PI is probably wasting his trainees’ time by letting them base their own research efforts on claims that there’s no good scientific reason to trust.
And as Bhattacharjee describes the situation for Stapel’s trainees, things for them were even worse:
He [Stapel] published more than two dozen studies while at Groningen, many of them written with his doctoral students. They don’t appear to have questioned why their supervisor was running many of the experiments for them. Nor did his colleagues inquire about this unusual practice.
(Bold emphasis added.)
I’d have thought that one of the things a scientist-in-training hopes to learn in the course of her graduate studies is not just how to design a good experiment, but how to implement it. Making your experimental design work in the real world is often much harder than it seems like it will be, but you learn from these difficulties — about the parameters you ignored in the design that turn out to be important, about the limitations of your measurement strategies, about ways the system you’re studying frustrates the expectations you had about it before you were actually interacting with it.
I’ll even go out on a limb and say that some experience doing experiments can make a significant difference in a scientist’s skill conceiving of experimental approaches to problems.
That Stapel cut his students out of doing the experiments was downright weird.
Now, scientific trainees probably don’t have the most realistic picture of precisely what competencies they need to master to become successful grown-up scientists in a field. They trust that the grown-up scientists training them know what these competencies are, and that these grown-up scientists will make sure that they encounter them in their training. Stapel’s trainees likely trusted him to guide them. Maybe they thought that he would have them conducting experiments if that were a skill that would require a significant amount of time or effort to master. Maybe they assumed that implementing the experiments they had designed was just so straightforward that Stapel thought they were better served working to learn other competencies instead.
(For that to be the case, though, Stapel would have to be the world’s most reassuring graduate advisor. I know my impostor complex was strong enough that I wouldn’t have believed I could do an experiment my boss or my fellow grad students viewed as totally easy until I had actually done it successfully three times. If I had to bet money, it would be that some of Stapel’s trainees wanted to learn how to do the experiments, but they were too scared to ask.)
There’s no reason, however, that Stapel’s colleagues should have thought it was OK that his trainees were not learning how to do experiments by taking charge of doing their own. If they did know and they did nothing, they were complicit in a failure to provide adequate scientific training to trainees in their program. If they didn’t know, that’s an argument that departments ought to take more responsibility for their trainees and to exercise more oversight rather than leaving each trainee to the mercies of his or her advisor.
And, as becomes clear from the New York Times Magazine article, doing experiments wasn’t the only piece of standard scientific training of which Stapel’s trainees were deprived. Bhattacharjee describes the revelation when a colleague collaborated with Stapel on a piece of research:
Stapel and [Ad] Vingerhoets [a colleague of his at Tilburg] worked together with a research assistant to prepare the coloring pages and the questionnaires. Stapel told Vingerhoets that he would collect the data from a school where he had contacts. A few weeks later, he called Vingerhoets to his office and showed him the results, scribbled on a sheet of paper. Vingerhoets was delighted to see a significant difference between the two conditions, indicating that children exposed to a teary-eyed picture were much more willing to share candy. It was sure to result in a high-profile publication. “I said, ‘This is so fantastic, so incredible,’ ” Vingerhoets told me.
He began writing the paper, but then he wondered if the data had shown any difference between girls and boys. “What about gender differences?” he asked Stapel, requesting to see the data. Stapel told him the data hadn’t been entered into a computer yet.
Vingerhoets was stumped. Stapel had shown him means and standard deviations and even a statistical index attesting to the reliability of the questionnaire, which would have seemed to require a computer to produce. Vingerhoets wondered if Stapel, as dean, was somehow testing him. Suspecting fraud, he consulted a retired professor to figure out what to do. “Do you really believe that someone with [Stapel’s] status faked data?” the professor asked him.
“At that moment,” Vingerhoets told me, “I decided that I would not report it to the rector.”
Stapel’s modus operandi was to make up his results out of whole cloth — to produce “findings” that looked statistically plausible without the muss and fuss of conducting actual experiments or collecting actual data. Indeed, since the thing he was creating that needed to look plausible enough to be accepted by his fellow scientists was the analyzed data, he didn’t bother making up raw data from which such an analysis could be generated.
Connecting the dots here, this surely means that Stapel’s trainees must not have gotten any experience dealing with raw data or learning how to apply methods of analysis to actual data sets. This left another gaping hole in the scientific training they deserved.
It would seem that those being trained by other scientists in Stapel’s program were getting some experience in conducting experiments, collecting data, and analyzing their data — since that experimentation, data collection, and data analysis became fodder for discussion in the ethics training that Stapel led. From the article:
And yet as part of a graduate seminar he taught on research ethics, Stapel would ask his students to dig back into their own research and look for things that might have been unethical. “They got back with terrible lapses,” he told me. “No informed consent, no debriefing of subjects, then of course in data analysis, looking only at some data and not all the data.” He didn’t see the same problems in his own work, he said, because there were no real data to contend with.
I would love to know the process by which Stapel’s program decided that he was the best one to teach the graduate seminar on research ethics. I wonder if this particular teaching assignment was one of those burdens that his colleagues tried to dodge, or if research ethics was viewed as a teaching assignment requiring no special expertise. I wonder how it’s sitting with them that they let a now-famous cheater teach their grad students how to be ethical scientists.
The whole “those who can’t do, teach” adage rings hollow here.
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