Effectiveness of Anonymization in Double-Blind Review

5 Sep 2017  ·  Claire Le Goues, Yuriy Brun, Sven Apel, Emery Berger, Sarfraz Khurshid, Yannis Smaragdakis ·

Double-blind review relies on the authors' ability and willingness to effectively anonymize their submissions. We explore anonymization effectiveness at ASE 2016, OOPSLA 2016, and PLDI 2016 by asking reviewers if they can guess author identities. We find that 74%-90% of reviews contain no correct guess and that reviewers who self-identify as experts on a paper's topic are more likely to attempt to guess, but no more likely to guess correctly. We present our findings, summarize the PC chairs' comments about administering double-blind review, discuss the advantages and disadvantages of revealing author identities part of the way through the process, and conclude by advocating for the continued use of double-blind review.

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Digital Libraries General Literature Software Engineering


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