Linguistic analysis reveals the hidden details of research grant proposal peer review reports

Abstract

Despite peer review panels being the most common way of selecting applicants for research funding, little is known about how selections are made. New methods for large-scale text analysis allow for review panels' written reports to be analysed and studied for patterns. Peter van den Besselaar and Ulf Sandström show how the frequency of positive and negative evaluation words correlate with applicants’ final scores, and also reveal how panels’ apparent conservatism means that the potentially groundbreaking, high-risk/high-gain research is unlikely to advance through the process and be selected for funding

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