Hauser deftly concedes chagrin for errors made within his lab "whether responsible for them or not," implying that the same students bullied into committing academic fraud were somehow responsible for the car veering off the cliff. Stapel faults a noxious combination of publication pressures, addictive tendencies, and assorted personality issues for his downfall. And while publication pressure was among those issues, he caps off his mea culpa with a plug for his new book -- Derailment, a collection of his therapeutic diaries.

The Slippery Slope

It's easy to revel in the high drama surrounding the downfall of a Hauser or Stapel, but what about the journals that published these scholars? Stapel was a widely cited and highly revered figure. His fraud went undetected for decades in spite of eerily perfect data sets and improbable statistical values. According to Tilburg University's final report, Flawed Science, "There was a general neglect of fundamental scientific standards and methodological requirements from top to bottom."

Scientists fought back, noting that it is rare for reviewers in any field to detect fraud and demanding an apology for the 'slanderous conclusions' drawn in the report. Social psychologist Kate Ratliff, teaching at Tilburg when the scandal broke noted, " It's a small community and people considered Diederik a friend and mentor...No one understands why these young researchers didn't realize that it was weird that Diederik was giving them datasets. But you learn from watching others. And if there are no others, how would you know what's weird or not? I think that people started out being really sympathetic toward them and have gotten more and more punitive as time passes and hindsight bias kicks in. I think that's really, really unfair."

Almost more alarming than the few individuals committing academic fraud are the high percentage of researchers who admitted to more common questionable research practices, like post-hoc theorizing and data-fishing (sometimes referred to as p-hacking), in a recent study led by Leslie John.

For the uninitiated: post-hoc theorizing involves creating or revising a hypothesis after you've collected the data; data-fishing entails running a study, continually checking the data after each participant, and stopping as soon as you see a significant result. These practices are eschewed by some, but plenty of others embrace them. Joseph Simmons and colleagues ran a simulation showing how unacceptably easy it was to attain statistical significance using these 'degrees of researcher freedom.' By employing four of these questionable practices at once, they managed to find statistically significant evidence for the absurd hypothesis that listening to a Beatles song could make you 1.5 years younger.

"Clearer identification of the problems associated with some research practices is incredibly helpful," writes Linda Skitka, who sits on numerous journal editorial boards. "Because I'm guessing at least some scholars who engaged in questionable practices did not recognize the full implications of doing so. Given the intense attention these issues are now getting in the field, they certainly know better now."