Fake attributions: a persistent and evolving research integrity problem

In the 1980s, Robert Slutsky and John Darsee were two of the most prolific authors in medical research. At the University of California San Diego, Slutsky was publishing one article every ten days. On the other side of the US, at Harvard Medical School, Darsee was still in his early 30s but had already published more than 100 articles. These rates were unusual, but in Darsee’s case, he was reported to work more than 90 hours a week researching the effects of cardiac drugs on dogs.

The real explanation for their productivity was not dedication and hard work, it was fraud. Both Slutsky and Darsee were caught fabricating data and much of their work was retracted. 

The New York Times article, June 14, 1983

Both of these researchers became pioneers of a particular type of misconduct. To boost the credibility of their articles, they fraudulently attributed co-authorship to influential researchers without their knowledge, which helped to bypass editorial scrutiny. 

Today, that same tactic is still in use and has evolved. Fraudulent authorship and affiliations are now used not just to boost article credibility, but also the credibility of authors, journals, and institutions. Here are a few examples:

Journals: 

Tove Godskesen, a researcher at Uppsala University, recently discovered that he and his colleagues were listed as authors of a paper they had never seen, which included fabricated data. Godskesen suspects that journal owners or editors created the article and used the names of established researchers to lend legitimacy and attract submissions.

Authors: 

We’ve spoken to several institutions who regularly find articles listing authors with no affiliation or tenuous connection to the institution. In many cases, this appears to be an attempt to increase the author’s credibility. In others, it may be a fraudulent way to get an unsuspecting institution to pay a journal’s article processing charge.

Institutions: 

Some institutions will go to great lengths to increase their publication output and standing in global rankings, a recent article reported that a Saudi Arabian institution was paying foreign researchers up to €70,000 to falsely declare the Saudi institution as their primary affiliation. 

Articles: 

Just as Darsee and Slutsky did decades ago, researchers today still add reputable names to their work without consent. Recently, Sikandar Akbar ambitiously included Turing Award winners Yann LeCun and Yoshua Bengio as co-authors on a publication. LeCun discovered the fraud when the article appeared on his Google Scholar profile.

Yann LeCun’s Linkedin post about the fake attribution

Fake authorships and affiliations can do real harm. As LeCun found, fraudulent works can automatically be added to a researcher’s profile, which could damage a researcher’s career if not corrected. Publishers that fail to detect fraud may face lengthy retraction processes, reputational damage, and delisting from key indexes. And researchers may be misled into reading and citing fraudulent works, slowing scientific progress.

Part of the problem is that the current system doesn’t yet have the safeguards in place. Journals don’t verify author identities. Institutions lack simple ways to monitor potential issues in their attributed output. And many platforms automatically add publications to researcher profiles, often without their approval or any alert when suspicious authorships appear.

What we need is a platform that helps researchers discover and report false authorship, and that detects and alerts institutions and publishers when these issues occur. That kind of visibility can stop problems early and help protect reputations. 

Signals is supporting researchers, institutions and publishers to solve these issues.

Researchers who discover they’ve been falsely listed as an author can add an Expert Contribution to Signals. This helps other researchers recognise issues and alerts publishers to resolve the issue quickly.

An expert contribution flagging the fake authorship of Yoshua Benigo and Yann LeCun

Institutions can use Signals to get real-time visibility into their publication output and receive alerts for issues, including fake affiliation, reducing administrative burden and reputational risk.

We’re also working closely with publishers to identify patterns of fraudulent authorship and affiliation across submissions and publications. 

These insights from Signals support best-in-class research integrity processes and help ensure that researcher, institution and publisher reputations are protected.