Imperial College London has developed an analytics tool that presents data on the diversity of countries and country income level of journal article authors cited on College reading lists.

There is currently data for over 13,000 articles cited by approximately 1,700 Imperial reading lists over different time periods.

It has been created to help staff or students access data that may inform broader discussions about representation in curricula. Supported by Imperial College London's President’s Excellence Fund for Learning and Teaching Innovation and  NIHR ARC NW London.

The image below shoes an example of data in the tool that shows cited authors by their country affiliation on a real Imperial reading list. Blue dots represent countries with affiliated authors with size in proportion to number of authors:

Cited authors by country affiliation

 

 

 

 

Access the tool

The tool is available on request to staff and students who would like to engage in meaningful exploration of their curricula.

Please request a consultation meeting if you are interested to learn more and gain access.

Events

Research

  • Price R, Skopec M. MacKensie S, Nijhoff C, Harrison R, Seabrook G, Harris M.  A novel data solution to analyse curriculum decolonisation–the 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

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