The diversity of analysis frameworks used in different fields of quantitative research is understudied. Using bibliometric data from the Web of Science (WoS), we conduct a large-scale and cross-disciplinary assessment of the proportion of articles that use linear models in comparison to other analysis frameworks from 1990 to 2022 and investigate the spatial and citation patterns. We found that, in absolute terms, linear models are widely used across all fields of science. In relative terms, three patterns suggest that linear-model-based research is a dominant analysis framework in Social Sciences. First, almost two-thirds of research articles reporting a statistical analysis framework reported linear models. Second, research articles from underrepresented countries in the WoS data displayed the highest proportions of articles reporting linear models. Third, there was a citation premium to articles reporting linear models in terms of being cited at least once for the entire period, and for the average number of citations until 2012. The confluence of these patterns may not be beneficial to the Social Sciences, as it could marginalize theories incompatible with the linear models’ framework. Our results have implications for quantitative research practices, including teaching and education of the next generations of scholars.

This paper examines the structure of scientific collaborations in Berlin as a specific case with a unique history of division and reunification. It aims to identify strategic organizational coalitions in a context with high sectoral diversity. We use publications data with at least one organization located in Berlin from 1996–2017 and their collaborators worldwide. We further investigate four members of the Berlin University Alliance (BUA), as a formerly established coalition in the region, through their self-represented research profiles compared with empirical results. Using a bipartite network modeling framework, we move beyond the uncontested trend towards team science and increasing internationalization. Our results show that BUA members shape the structure of scientific collaborations in the region. However, they are not collaborating cohesively in all fields and there are many smaller scientific actors involved in more internationalized collaborations in the region. Larger divides exist in some fields. Only Medical and Health Sciences have cohesive intraregional collaborations, which signals the success of the regional cooperation established in 2003. We explain possible underlying factors shaping the intraregional groupings and potential implications for regions worldwide. A major methodological contribution of this paper is evaluating the coverage and accuracy of different organization name disambiguation techniques.