May 28, 2013 | 2
This post continues my discussion of issues raised in the article by Yudhijit Bhattacharjee in the New York Times Magazine (published April 26, 2013) on social psychologist and scientific fraudster Diederik Stapel. Part 1 looked at how expecting to find a particular kind of order in the universe may leave a scientific community more vulnerable to a fraudster claiming to have found results that display just that kind of order. Part 2 looked at some of the ways Stapel’s conduct did harm to the students he was supposed to be training to be scientists. Here, I want to point out another way that Stapel failed his students — ironically, by shielding them from failure.
[I]n the spring of 2010, a graduate student noticed anomalies in three experiments Stapel had run for him. When asked for the raw data, Stapel initially said he no longer had it. Later that year, shortly after Stapel became dean, the student mentioned his concerns to a young professor at the university gym. Each of them spoke to me but requested anonymity because they worried their careers would be damaged if they were identified.
The professor, who had been hired recently, began attending Stapel’s lab meetings. He was struck by how great the data looked, no matter the experiment. “I don’t know that I ever saw that a study failed, which is highly unusual,” he told me. “Even the best people, in my experience, have studies that fail constantly. Usually, half don’t work.”
In the next post, we’ll look at how this other professor’s curiosity about Stapel’s too-good-to-be-true results led to the unraveling of Stapel’s fraud. But I think it’s worth pausing here to say a bit more on how very odd a training environment Stapel’s research group provided for his students.
None of his studies failed. Since, as we saw in the last post, Stapel was also conducting (or, more accurately, claiming to conduct) his students’ studies, that means none of his students’ studies failed.
This is pretty much the opposite of every graduate student experience in an empirical field that I have heard described. Most studies fail. Getting to a 50% success rate with your empirical studies is a significant achievement.
Graduate students who are also Trekkies usually come to recognize that the travails of empirical studies are like a version of the Kobayashi Maru.
Introduced in Star Trek II: The Wrath of Khan, the Kobayashi Maru is a training simulation in which Star Fleet cadets are presented with a civilian ship in distress. Saving the civilians requires the cadet to violate treaty by entering the Neutral Zone (and in the simulation, this choice results in a Klingon attack and the boarding of the cadet’s ship). Honoring the treaty, on the other hand, means abandoning the civilians and their disabled ship in the Neutral Zone. The Kobayashi Maru is designed as a “no-win” scenario. The intent of the test is to discover how trainees face such a situation. Owing to James T. Kirk’s performance on the test, Wikipedia notes that some Trekkies also view the Kobayashi Maru as a problem whose solution depends on redefining the problem.
Scientific knowledge-building turns out to be packed with particular plans that cannot succeed at yielding the particular pieces of knowledge the scientists hope to discover. This is because scientists are formulating plans on the basis of what is already known to try to reveal what isn’t yet known — so knowing where to look, or what tools to use to do the looking, or what other features of the world are there to confound your ability to get clear information with those tools, is pretty hard.
Failed attempts happen. If they’re the sort of thing that will crush your spirit and leave you unable to shake it off and try it again, or to come up with a new strategy to try, then the life of a scientist will be a pretty hard life for you.
Grown-up scientists have studies fail all the time. Graduate students training to be scientists do, too. But graduate students also have mentors who are supposed to help them bounce back from failure — to figure out the most likely sources of failure, whether it’s worth trying the study again, whether a new approach would be better, whether some crucial piece of knowledge has been learned despite the failure of what was planned. Mentors give scientific trainees a set of strategies for responding to particular failures, and they also give reassurance that even good scientists fail.
Scientific knowledge is built by actual humans who don’t have perfect foresight about the features of the world as yet undiscovered, humans who don’t have perfectly precise instruments (or hands and eyes using those instruments), humans who sometimes mess up in executing their protocols. Yet the knowledge is built, and it frequently works pretty well.
In the context of scientific training, it strikes me as malpractice to send new scientists out into the world with the expectation that all of their studies should work, and without any experience grappling with studies that don’t work. Shielding his students from their Kobayashi Maru is just one more way Diederik Stapel cheated them out of a good scientific training.
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