This article was published in Scientific American’s former blog network and reflects the views of the author, not necessarily those of Scientific American
Yudhijit Bhattacharjee has an excellent article in the most recent New York Times Magazine (published April 26, 2013) on disgraced Dutch social psychologist Diederik Stapel. Why is Stapel disgraced? At the last count at Retraction Watch,
5453 of his scientific publications have been retracted, owing to the fact that the results reported in those publications were made up. [Scroll in that Retraction Watch post for the update -- apparently one of the Stapel retractions was double-counted. This is the risk when you publish so much made-up stuff.]
There's not much to say about the badness of a scientist making results up. Science is supposed to be an activity in which people build a body of reliable knowledge about the world, grounding that knowledge in actual empirical observations of that world. Substituting the story you want to tell for those actual empirical observations undercuts that goal.
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But Bhattacharjee's article is fascinating because it goes some way to helping illuminate why Stapel abandoned the path of scientific discovery and went down the path of scientific fraud instead. It shows us some of the forces and habits that, while seemingly innocuous taken individually, can compound to reinforce scientific behavior that is not helpful to the project of knowledge-building. It reveals forces within scientific communities that make it hard for scientists to pursue suspicions of fraud to get formal determinations of whether their colleagues are actually cheating. And, the article exposes some of the harms Stapel committed beyond publishing lies as scientific findings.
It's an incredibly rich piece of reporting, one which I recommend you read in its entirety, maybe more than once. Given just how much there is to talk about here, I'll be taking at least a few posts to highlight bits of the article as nourishing food for thought.
Let's start with how Stapel describes his early motivation for fabricating results to Bhattacharjee. From the article:
Stapel did not deny that his deceit was driven by ambition. But it was more complicated than that, he told me. He insisted that he loved social psychology but had been frustrated by the messiness of experimental data, which rarely led to clear conclusions. His lifelong obsession with elegance and order, he said, led him to concoct sexy results that journals found attractive. “It was a quest for aesthetics, for beauty — instead of the truth,” he said. He described his behavior as an addiction that drove him to carry out acts of increasingly daring fraud, like a junkie seeking a bigger and better high.
(Bold emphasis added.)
It's worth noting here that other scientists -- plenty of scientists who were never cheaters, in fact -- have also pursued science as a quest for beauty, elegance, and order. For many, science is powerful because it is a way to find order in a messy universe, to discover simple natural laws that give rise to such an array of complex phenomena. We've discussed this here before, when looking at the tension between Platonist and Aristotelian strategies for getting to objective truths:
Plato’s view was that the stuff of our world consists largely of imperfect material instantiations of immaterial ideal forms -– and that science makes the observations it does of many examples of material stuff to get a handle on those ideal forms.
If you know the allegory of the cave, however, you know that Plato didn’t put much faith in feeble human sense organs as a route to grasping the forms. The very imperfection of those material instantiations that our sense organs apprehend would be bound to mislead us about the forms. Instead, Plato thought we’d need to use the mind to grasp the forms.
This is a crucial juncture where Aristotle parted ways with Plato. Aristotle still thought that there was something like the forms, but he rejected Plato’s full-strength rationalism in favor of an empirical approach to grasping them. If you wanted to get a handle on the form of “horse,” for example, Aristotle thought the thing to do was to examine lots of actual specimens of horse and to identify the essence they all have in common. The Aristotelian approach probably feels more sensible to modern scientists than the Platonist alternative, but note that we’re still talking about arriving at a description of “horse-ness” that transcends the observable features of any particular horse.
Honest scientists simultaneously reach for beautiful order and the truth. They use careful observations of the world to try to discern the actual structures and forces giving rise to what they are observing. They recognize that our observational powers are imperfect, that our measurements are not infinitely precise (and that they are often at least a little inaccurate), but those observations, those measurements, are what we have to work with in discerning the order underlying them.
This is why Ockham's razor -- to prefer simple explanations for phenomena over more complicated ones -- is a strategy but not a rule. Scientists go into their knowledge-building endeavor with the hunch that the world has more underlying order than is immediately apparent to us -- and that careful empirical study will help us discover that order -- but how things actually are provides a constraint on how much elegance there is to be found.
However, as the article in the New York Times Magazine makes clear, Stapel was not alone in expecting the world he was trying to describe in his research to yield elegance:
In his early years of research — when he supposedly collected real experimental data — Stapel wrote papers laying out complicated and messy relationships between multiple variables. He soon realized that journal editors preferred simplicity. “They are actually telling you: ‘Leave out this stuff. Make it simpler,’” Stapel told me. Before long, he was striving to write elegant articles.
The journal editors' preference here connects to a fairly common notion of understanding. Understanding a system is being able to identify that components of that system that make a difference in producing the effects of interest -- and, by extension, recognizing which components of the system don't feature prominently in bringing about the behaviors you're studying. Again, the hunch is that there are likely to be simple mechanisms underlying apparently complex behavior. When you really understand the system, you can point out those mechanisms and explain what's going on while leaving all the other extraneous bits in the background.
Pushing to find this kind of underlying simplicity has been a fruitful scientific strategy, but it's a strategy that can run into trouble if the mechanisms giving rise to the behavior you're studying are in fact complicated. There's a phrase attributed to Einstein that captures this tension nicely: as simple as possible … but not simpler.
The journal editors, by expressing to Stapel that they liked simplicity more than messy relationships between multiple variables, were surely not telling Stapel to lie about his findings to create such simplicity. They were likely conveying their view that further study, or more careful analysis of data, might yield elegant relations that were really there but elusive. However, intentionally or not, they did communicate to Stapel that simple relationships fit better with journal editors' hunches about what the world is like than did messy ones -- and that results that seemed to reveal simple relations were thus more likely to pass through peer review without raising serious objections.
So, Stapel was aware that the gatekeepers of the literature in his field preferred elegant results. He also seemed to have felt the pressure that early-career academic scientists often feel to make all of his research time productive -- where the ultimate measure of productivity is a publishable result. Again, from the New York Times Magazine article:
The experiment — and others like it — didn’t give Stapel the desired results, he said. He had the choice of abandoning the work or redoing the experiment. But he had already spent a lot of time on the research and was convinced his hypothesis was valid. “I said — you know what, I am going to create the data set,” he told me.
(Bold emphasis added.)
The sunk time clearly struck Stapel as a problem. Making a careful study of the particular psychological phenomenon he was trying to understand hadn't yielded good results -- which is to say, results that would be recognized by scientific journal editors or peer reviewers as adding to the shared body of knowledge by revealing something about the mechanism at work in the phenomenon. This is not to say that experiments with negative results don't tell scientists something about how the world is. But what negative results tell us is usually that the available data don't support the hypothesis, or perhaps that the experimental design wasn't a great way to obtain data to let us evaluate that hypothesis.
Scientific journals have not generally been very interested in publishing negative results, however, so scientists tend to view them as failures. They may help us to reject appealing hypotheses or to refine experimental strategies, but they don't usually do much to help advance a scientist's career. If negative results don't help you get publications, without which it's harder to get grants to fund research that could find positive results, then the time and money spent doing all that research has been wasted.
And Stapel felt -- maybe because of his hunch that the piece of the world he was trying to describe had to have an underlying order, elegance, simplicity -- that his hypothesis was right. The messiness of actual data from the world got in the way of proving it, but it had to be so. And this expectation of elegance and simplicity fit perfectly with the feedback he had heard before from journal editors in his field (feedback that may well have fed Stapel's own conviction).
A career calculation paired with a strong metaphysical commitment to underlying simplicity seems, then, to have persuaded Diederik Stapel to let his hunch weigh more heavily than the data and then to commit the cardinal sin of falsifying data that could be presented to other scientists as "evidence" to support that hunch.
No one made Diederik Stapel cross that line. But it's probably worth thinking about the ways that commitments within scientific communities -- especially methodological commitments that start to take on the strength of metaphysical commitments -- could have made crossing it more tempting.