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“Most new publications, upon their launch, seek to promote their content as novel, surprising, exciting.

A new journal that began publishing this week does … the opposite of that.

Start with the name: Series of Unsurprising Results in Economics (SURE). The journal publishes papers with findings that are, well, really boring — so boring that other journals rejected them just for being boring. Its first paper, published Tuesday, is about an education intervention that was found to have no effects at all on anything.

But before you close this [article], hear me out. SURE is actually far from boring, even if the papers it publishes are guaranteed to be, as the name implies, unsurprising. In fact, it’s a pretty big deal, and a significant step toward fixing a major problem with scientific research.

SURE exists to fight “publication bias,” which affects every research field out there. Publication bias works like this: Let’s say hundreds of scientists are studying a topic. The ones who find counterintuitive, surprising results in their data will publish those surprising results as papers.

The ones who find extremely standard, unsurprising results — say, “This intervention does not have any effects,” or, “There doesn’t seem to be a strong relationship between any of these variables” — will usually get rejected from journals, if they bother turning their disappointing results into a paper at all.

That’s because journals like to publish novel results that change our understanding of the field. Null results (where the researchers didn’t find anything) or boring results (where they confirm something we already know) are much less likely to be published. And efforts to replicate other people’s papers often aren’t published, either, because journals want something new and different.

That makes sense — but it’s terrible for science. This tendency leads researchers to waste time on analyses that other researchers may have already pursued but not publicized; to twist their data for results so they can publish when they initially don’t find anything; and to look for surprising outliers instead of the often mundane reality.

But awareness about this problem is growing. And in response, scientists are trying to build better processes. SURE is one step toward that goal.”