In this article, I conduct a textual and contextual analysis of the empirical literature on Zipf's law for cities. Building on previous meta-analysis material openly available, I collect full texts and bibliographies of 66 scientific articles published in English and construct similarity networks of the terms they use as well as of the references and disciplines they cite. I use these networks as explanatory variables in a model of the similarity network of the distribution of Zipf estimates reported in the 66 articles. I find that the proximity in words frequently used by authors correlates positively with their tendency to report similar values and dispersion of Zipf estimates. The reference framework of articles also plays a role, as articles which cite similar references tend to report similar average values of Zipf estimates. As a complement to previous meta-analyses, the present approach sheds light on the scientific text and context mobilized to report on city size distributions. It allows to identified gaps in the corpus and potentially overlooked articles.
|Publication status||Published - 7 Aug 2020|