The distinction machine: Physics journals from the perspective of the Kolmogorov–Smirnov statistic
An informal notion of distinction between scholarly journals is deeply embedded in bibliometric practice. Distinctions can be viewed as an operationalization of statistical relationships between journals. Bibliometric distinction can be regarded as a relative concept parameterized by the Kolmogorov--Smirnov statistic used as a basis for determining similarity or difference of journals. Within this framework, a systematic study of the probability distribution of distinctions makes it easier to understand the structure of the current scholarly communication. Using the Wakeby distribution, we propose a statistical description of the ``distinction machine'' at the core of the journals' diversity. In this paper, empirical research is based on a dataset of 230 physics journals indexed in Scopus in 2010 to 2015. The ranking of physics journals is obtained by computing the stationary probabilities in terms of Markov chain using transition probabilities derived from the distinction distribution. We perform a clustering of the physics journals according to a similarity that represents the statistical indistinguishability between the journals. This study could help practitioners to make decisions based on a deep understanding of the structure of scholarly communication.