/mit-knowledge-oligarchies

Primary LanguageJupyter NotebookMIT LicenseMIT

The Medical Knowledge Oligarchies: Network Analysis of Medical Research Publication and Collaboration

Get the Data from Google Drive.

Abstract

Introduction

Healthcare policies and clinical decisions heavily rely on research publications from high-impact medical journals. A lack of author diversity in medical publications poses a risk to underrepresented groups. To promote equity in healthcare medical decisions, fostering collaborations within research groups is crucial. This study integrates scientometrics with network analysis to uncover intricate co-authorship networks and examine diversity and inclusion in scientific collaboration.

Methods

The authors' metadata from five high-impact medical journals were collected, and a weighted graph of co-authorships was constructed. The study addresses four research questions: identifying influential authors, exploring research output communities, analyzing collaboration patterns, and examining the evolution of collaboration over time.

Results

Central nodes are significantly more likely to be male or from high-income countries. Further, when evaluated over time, the graph reveals concerning trends in diversity where collaboration with authors from lower income countries is not growing. All code is publicly available on GitHub.

Discussion

The findings underscore the need to promote diversity within research niches and question the role of gatekeepers in facilitating inclusivity. Future studies should expand the scope of network analysis and explore additional factors such as funding sources and guidelines.

Conclusion

Overall, this study contributes a framework for auditing diversity and inclusion in scientific collaboration, aiming to promote transparency and a more equitable medical knowledge production system.