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:
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
- EDU workshop Examining geographic bias in our curricula for staff with teaching responsibility
- Bespoke workshop or seminar for research groups or departments wishing to explore geographic bias and use the tool. Available on request, please contact Georgina Wildman g.wildman@imperial.ac.uk
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
Networks and communities
- Decolonise the Library working group for Library Services. To join the working group please email Coco Nijhoff a.nijhoff@imperial.ac.uk
- Imperial as One network for staff and postgraduate students who identify as Black, Asian and Minority Ethnicity and allies
- Equality, Diversity and Inclusion
- Imperial College Union Liberation & Community networks