Aggregating post-publication peer reviews and ratings

Frontiers in Computational Neuroscience, 6, 31 (2012) .


Abstract

Allocating funding for research often entails the review of the publications authored by a scientist or a group of scientists. For practical reasons, in many cases this review cannot be performed by a sufficient number of specialists in the core domain of the reviewed publications. In the meanwhile, each scientist reads thoroughly, on average, about 88 scientific articles per year, and the evaluative information that scientists can provide about these articles is currently lost. I suggest that aggregating in an online database reviews or ratings on the publications that scientists read anyhow can provide important information that can revolutionize the evaluation processes that support funding decisions. I also suggest that such aggregation of reviews can be encouraged by a system that would provide a publicly available review portfolio for each scientist, without prejudicing the anonymity of reviews. I provide some quantitative estimates on the number and distribution of reviews and ratings that can be obtained.



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