Indeed, very robust new research confirms that having a prominent figure in the scientific community helps your paper get published. Only 10% of reviewers of test papers recommended acceptance when the only listed author was unknown, but when the same manuscript contained the name of a Nobel Prize winner , 59% supported it.

The study, which recruited hundreds of researchers to review economics manuscripts, was “incredible,” said a postdoctoral fellow at Stanford University, Research Integrity and Peer Review, was not involved in the study. “This is the largest randomized controlled trial we have seen on publication bias.”

The Matthew effect is the 1968 study by sociologists Robert Merton and Harriet Zuckerman that high-ranking researchers (e.g., those who have already received many citations and grants) produce a disproportionate number of papers. It’s a term I coined to describe the tendency to acquire. same. (The name comes from a parable about abundance in the Gospel of Matthew in the Bible.)

Efforts to document such bias, however, have suffered from weaknesses, such as small sample sizes and lack of randomization. To get around these problems, a team led by Jürgen Huber at the University of Innsbruck emailed about 3,300 researchers asking if they would review economics research prepared for publication in a physical journal. rice field. The study had two authors, both of whom were at Chapman University. Vernon Smith is his 2002 Nobel Laureate in Economics, and last year Google Scholar had more than 54,000 citations of him. Inoua his Savio, one of Smith’s former PhDs. He was cited only 42 times last year. Potential reviewers were sent one of his three descriptions of the paper. Only one other person, Inoua. Third, there are no authors.

Ultimately, 821 researchers agreed to the review, the team reported last week at the International Conference on Peer Review and Scientific Publishing in Chicago. (The results also appeared in a preprint posted to the SSRN server last month.) Smith’s prowess seems to have swayed the reaction. Of those researchers who only mentioned his name, 38.5% accepted the review invitation. 30.7% were anonymous and 28.5% were only Inoue.

The team then took a second step to avoid bias in their own research. They focused on 313 aspiring reviewers who had not initially received the author’s name and randomly assigned him to review one of the three manuscripts. (The team also informed reviewers that their evaluation was part of an experiment involving a small number of invited reviewers, rather than the usual two or three, but the design of the study did not disclose.)

The Smith-credited manuscript received top marks from reviewers who praised it for including new information and conclusions supported by data. And her 24% of those who reviewed the authorless version recommended accepting it (completely or with minor modifications). (Smith and Inoua later revised the manuscript submitted as a preprint for publication in the journal.)

Many researchers may not be surprised by this large disparity. But it’s troubling, the authors of the new study told a peer-review conference. No. “It makes it particularly difficult for young, unknown researchers to step into the door of the academic process.”

The authors could not rule out that discrimination based on perceived race or geographical origin shaped the decisions of some reviewers. Smith’s name “sounds American” and he is white, Konig Kersting said, while Inoua is a citizen of Niger and has dark skin.

Researchers studying bias in publishing suggest that double-blind reading, which hides the identities of both authors and reviewers, may reduce the Matthew effect. But reviewers can often identify authors from preprints or presentations at conferences, so this tactic may not work, König-Kersting said at the conference.