  This paper introduces a statistical and other analysis of peer reviewers in
order to approach their "quality" through some quantification measure, thereby
leading to some quality metrics. Peer reviewer reports for the Journal of the
Serbian Chemical Society are examined. The text of each report has first to be
adapted to word counting software in order to avoid jargon inducing confusion
when searching for the word frequency: e.g. C must be distinguished, depending
if it means Carbon or Celsius, etc. Thus, every report has to be carefully
"rewritten". Thereafter, the quantity, variety and distribution of words are
examined in each report and compared to the whole set. Two separate months,
according when reports came in, are distinguished to observe any possible
hidden spurious effects. Coherence is found. An empirical distribution is
searched for through a Zipf-Pareto rank-size law. It is observed that peer
review reports are very far from usual texts in this respect. Deviations from
the usual (first) Zipf's law are discussed. A theoretical suggestion for the
"best (or worst) report" and by extension "good (or bad) reviewer", within this
context, is provided from an entropy argument, through the concept of "distance
to average" behavior. Another entropy-based measure also allows to measure the
journal reviews (whence reviewers) for further comparison with other journals
through their own reviewer reports.
