Bradford ranking conventions and their application to a growing literature

Abstract

Bradford distributions describe the relationship between ‘journal productivities’ and ‘journal rankings by productivity’. However, different ranking conventions exist, implying some ambiguity as to what the Bradford distribution ‘is’. A need accordingly arises for a standard ranking convention to assist comparisons between empirical data, and also comparisons between empirical data and theoretical models. Five ranking conventions are described including the one used originally by Bradford, along with suggested distinctions between ‘Bradford data set’, ‘Bradford distribution’, ‘Bradford graph’, ‘Bradford log graph’, ‘Bradford model’ and ‘Bradford’s Law‘. Constructions such as the Lotka distribution, Groos droop (generalised to accommodate growth as well as fall‐off in the Bradford log graph), Brookes hooks, and the slope and intercept of the Bradford log graph are clarified on this basis. Concepts or procedures questioned include: (1) ‘core journal’, from the Bradfordian viewpoint; (2) the use of traditional statistical inferential procedures applied to Bradford data; and (3) R(n) as a maximum (rather than median or mean) value at tied‐rank values.