Imperial has developed an analytics tool that presents data on the geographic distribution of the institutional affiliations of authors cited on Imperial’s reading lists. It also includes information on the country income level of  the countries in which those institutions are located.

There is currently data for close to 13,000 articles from approximately 3,300 Imperial reading lists published on Leganto between 2016 and 2025. Our analysis using the tool shows that out of 78,000 authors of published articles, 96% are affiliated with universities in high-income countries. The same data shows that more than 4,600 articles on reading lists are published by authors from the UK, and 6,400 by authors from the US.

The tool has been created to help staff or students access data that may inform broader discussions about representation on reading lists and in curricula. Creation of the tool has been supported by Imperial’s President’sExcellence Fund for Learning and Teaching Innovationand  NIHR ARC NW London.

The resources on this page were developed in collaboration with Imperial students as part of a StudentShapers project.

 

Further resources and links

Events:

To learn more about the tool and how to use it in your practice, you may wish to attend any of the following events:

Networks and communities:

Research publications:

  • Price R, Skopec M. MacKenzie S, Nijhoff C, Harrison R, Seabrook G, Harris M. A novel data solution to analyse curriculum decolonisationthe case of Imperial College London Masters in Public Health. Scientometrics 2022, 127;1021-1037
  • Skopec, M., Fyfe, M., Issa, H., Ippolito, K., Anderson, M. and Harris, M. (2021) ‘Decolonization in a higher education STEMM institution – is “epistemic fragility” a barrier?’ London Review of Education, 19 (1), 1–21. https://doi.org/10.14324/LRE.19.1.18
  • Skopec M, Issa H, Reed J, Harris M. The role of geographic bias in knowledge diffusion: a systematic review. Research Integrity and Peer Review 2020 5(2)
  • Harris M, Marti J, Bhatti Y, Watt H, Macinko J, Darzi A. Explicit bias towards high-income country research: a randomized, blinded crossover trial of decision-making by English clinicians. Health Affairs 2017: 36(11); 1994-2007
  • Harris M, Macinko J, Jimenez G and Mulacherry P. Measuring the bias against low-income country research: an Implicit Association Test. Globalization and Health 2017; 13:80
  • Harris M, Weisberger E, Silver D, Macinko J. ‘They hear “Africa” and think there are no good services there’ - perceived context in cross-national learning: a qualitative study. Globalization and Health 2015: 11;45