  Here we show a novel technique for comparing subject categories, where the
prestige of academic journals in each category is represented statistically by
an impact-factor histogram. For each subject category we compute the
probability of occurrence of scholarly journals with impact factor in different
intervals. Here impact factor is measured with Thomson Reuters Impact Factor,
Eigenfactor Score, and Immediacy Index. Assuming the probabilities associated
with a pair of subject categories our objective is to measure the degree of
dissimilarity between them. To do so, we use an axiomatic characterization for
predicting dissimilarity between subject categories. The scientific subject
categories of Web of Science in 2010 were used to test the proposed approach
for benchmarking Cell Biology and Computer Science Information Systems with the
rest as two case studies. The former is best-in-class benchmarking that
involves studying the leading competitor category; the latter is strategic
benchmarking that involves observing how other scientific subject categories
compete.
