This research uses descriptive multivariate data-analytic techniques—in particular, multidimensional scaling and hierarchical
cluster analysis—to explore and visualize the structure of the pharmacy literature as refracted through the editorial policies
of theInternational Pharmaceutical Abstracts (IPA) database. Specifically, the co-occurrence of the section headings/codes, used to exhaustively categorize publications
in the IPA database, are clustered and mapped to evaluate the usefulness of two methods of section heading assignment. A secondary
purpose of this research is to evaluate the use of descriptive multivariate data-analytic techniques and co-classification
analysis to explore and depict the structure of an inherently heterogeneous and multidisciplinary professional literature,
such as pharmacy.