Developing a predictive model of editor selectivity in a current awareness service of a large digital library

“NEP: New Economics Papers”, the current awareness service for the Research Papers in Economics (RePEc) digital library, is made possible by volunteer editors who filter new additions to RePEc into subject-specific reports. The official purpose of current awareness service is to filter working papers by subject matter without any judgment of its academic quality. In this article, binary logistic regression analysis (BLRA) estimates the probability of a paper being included in any of the subject reports as a function of a range of observable values. The analysis suggests that, contrary to their claims, editors use quality criteria: the series the paper is coming from and the reputation of the authors. The findings suggest that a current awareness service can issue quality signals.