In this article, I conduct a textual and contextual meta-analysis of the empirical literature on Zipf's law for cities. Combining citation network analysis and bibliometrics, this meta-analysis explores the link between publication bias and reporting bias in the multidisciplinary field of quantitative urban studies. To complement a set of metadata already available, I collect the full-texts and reference lists 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. It confirms the relationship between publication and reporting biases.
|Number of pages||25|
|Journal||Scientometrics: an international journal for all quantitative aspects of the science of science, communication in science and science policy|
|Publication status||Published - 2022|