Report: Fujii faked data in at least 172 papers

A Japanese web site is reporting that Yoshitaka Fujii, a Japanese anesthesiologist suspected of widespread data fabrication, did indeed fake his results in at least 172 published studies.

According to the article, on a site called Jiji Press:

   Tokyo, June 29 (Jiji Press)–A Japanese anesthesiologist made up a total of 172 fictitious research papers between 1993 and 2011, an academic society said Friday.
Yoshitaka Fujii, a 52-year-old former associate professor at Toho University, has denied fabricating research, according to the Japanese Society of Anesthesiologists.
The number of papers that he allegedly faked is the largest ever for any medical researcher, both in Japan and overseas, according to sources familiar with the field.
The society surveyed 212 articles written by Fujii that were published in a total of 41 Japanese and international journals. Of them, it found 172 fake research reports and three articles backed by real research. It was unable to assess 37 articles due to lack of scientific evidence.
Coauthors of Fujii’s articles were not sure of the content of his research, the society said.

Some of Fujii’s papers already have been retracted, but we’re guessing this opens the floodgates. We’ll update as we learn more.

Please see an update on this post, with a more complete report.

12 thoughts on “Report: Fujii faked data in at least 172 papers”

  1. Coauthors were not sure of the content of his research? What could this mean? Coauthors suspected he was faking his data? Or something else?

    1. Probably something got lost in translation from Japanese just like in a sign in a Tokyo hotel advising its customers to “please leave [your] values at the front desk”.
      BTW, the title of this post, “Report: Fujii faked data in at least 172 papers”, is very biased. Why not “Report: Fujii did not fake data in at least 3 papers”? Sounds much better.

      1. The title accurately states the astonishing fact that he faked data in this many papers. Not faking data is not newsworthy, at least it shouldn’t have to be.

      1. Thanks Ivan. I know that Science is robust, but still beyond the direct issue of bad papers, this issue of contagion to other work always bother me to no end. Especially when we are talking about such a large scale.

        Thanks for the great blog!


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