The Value of Peer Review and the Reward to Reputation

Journals cannot referee every paper they receive. When submissions outrun the time reviewers can give, an editor must decide what to do with the papers no one reads: reject them, or check them with a faster but less accurate tool, of the kind artificial intelligence now supplies. A paper the tool passes carries the same public stamp as one an expert approved, and readers cannot tell a screened paper from a reviewed one. This paper asks which choice makes the stamp more valuable. Rejecting the unread papers keeps the approved pool cleaner, because the faster tool sometimes passes weak work. Yet rejection can make the stamp worth less: good papers turned away unread join the pool of unstamped papers and raise the quality against which a stamped paper is judged. Which effect wins depends on how common good work is, and the model gives the exact switching point when there is one. The choice also shifts how much a strong affiliation is worth; and once authors can run the screening tool themselves, wherever some game it and some do not, the stamp’s value is set by what getting past the screen costs, not by what the screen detects, while expert judgment allows no such gaming.