Readersourcing—a manifesto by Stefano Mizzaro. (Mizzaro, S. (2012), Readersourcing—a manifesto. J. Am. Soc. Inf. Sci.. doi: 10.1002/asi.22668)
This position paper analyzes the current situation in scholarly publishing and peer review practices and presents three theses: (a) we are going to run out of peer reviewers; (b) it is possible to replace referees with readers, an approach that I have named “Readersourcing”; and (c) it is possible to avoid potential weaknesses in the Readersourcing model by adopting an appropriate quality control mechanism. The readersourcing.org system is then presented as an independent, third-party, nonprofit, and academic/scientific endeavor aimed at quality rating of scholarly literature and scholars, and some possible criticisms are discussed.
Mizzaro touches a number of issues that have speculative answers in his call for “readersourcing” of research. There is a website in progress, www.readersourcing.org.
I am interested in the approach as an aspect of crowdsourcing the creation of topic maps.
FYI, his statement that:
Readersourcing is a solution to a problem, but it immediately raises another problem, for which we need a solution: how to distinguish good readers from bad readers. If 200 undergraduate students say that a paper is good, but five experts (by reputation) in the field say that it is not, then it seems obvious that the latter should be given more importance when calculating the paper’s quality.
Seems problematic to me. Particularly for graduate students. If professors at their school rate research high or low, that should be calculated into a rating for that particular reader.
If that seems pessimistic, read: Fish, Stanley, “Transmuting the Lump: Paradise Lost, 1942-1979,” in Doing What Comes Naturally. Fish, Stanley (ed.), Duke University Press, 1989), which treats changing “expert” opinions on the closing chapters of Paradise Lost. So far as I know, the text did not change between 1942 and 1979 but “expert” opinion certainly did.
I offer that as a caution that all of our judgements are a matter of social consensus that changes over time. On some issues more quickly than others. Our information systems should reflect the ebb and flow of that semantic renegotiation.