Jonathan Berkheim and Ofir Kuperman published an article on The Dark Side of Research: Research Fraud in which they ask “Why do scientists sometimes falsify experimental results?” The authors quote Elisabeth Bik, who suggests: “Most research misconduct is done by researchers who feel a large pressure to publish, and it is easier to publish nice, positive findings, than complicated stories or negative findings. So if the results are not quite what one had hoped for, it is very tempting to change the results a bit to make them look better.” The authors go on to suggest that the checks and balances that are part of the peer-review system are inadequate to catch problems, because peer review is not really designed to catch fraud. Again Bik: “Most peer reviewers will assume the data they are reviewing is real, and might not think of fraud”.
Bik also notes that high-impact journals tend to have less fraud, but she adds: “I sometimes wonder if the authors who publish in high-impact journals are just more experienced and better cheaters. Most misconduct is not visible by just looking at the paper; you have to be sitting in the lab next to the person cheating to be able to catch them.”
One standard way to combat some forms of research fraud is for journals to encourage replication experiments. Replications are not popular with authors, because a positive result does little to enhance the author’s reputation. Replications tend to be unpopular with editors because the news value is low. Nonetheless science, especially natural science, builds on the expectation that results are replicable, and the fact of a successful replication should matter in the long run. Unfortunately replication is not simple, especially in the social sciences, where nuances of treatment can affect results without implying fraud.
As Bik and the authors suggest, there are no easy solutions, but there are steps that the academic community can take to address the problem, including reducing the pressure on scholars to publish. That would take a structural change in how universities evaluate faculty, and (in some countries) a structural change in how governments distribute university funding. Such changes will take time and pressure by respectable external organisations.
1: Wood, Matt. 2022. ‘Algorithm Predicts Crime a Week in Advance, but Reveals Bias in Police Response | Biological Sciences Division | The University of Chicago’. 30 June 2022. https://biologicalsciences.uchicago.edu/news/algorithm-predicts-crime-police-bias. Photo by Josh Nuttall on Unsplash.