The tool scans through reading lists uploaded onto Leganto, Imperial’s reading list management platform, then identifies the journal articles using their DOIs. Using this information, it cross-references the authors of these articles with Scopus using an article’s DOI to find the author affiliations. This is what is displayed as the country of origin of the article on a map. The World Bank income levels are used to group the countries and to calculate an overall number of how varied the reading list is by giving a Citation Source Index (CSI). When this number is close to one, it means that a lot of the authors in the reading list have institutional affiliations in high-income countries and if it is close to zero it means the authors of the articles in the reading lists have affiliations in low-income countries. 

Frequently asked questions

Using the tool

The Geographic bias tool is an interactive dashboard to help you analyse which parts of the world the research on reading lists comes from. It is designed to help assess the global diversity of the sources that are assigned on reading lists, as well as to identify any sources of unintentional geographical bias. Watch the overview video to learn more:

Understanding the results
This tool is designed to give you an overview of your reading list and start to consider the prevalence of geographic bias. It’s not telling you what to do but more getting you to think about questions like:
 
  • Is the research I assign concentrated to a few countries?
  • Do students get exposed to  knowledge generated in  the Global South?
  • Are there important voices in a specific area of research that are not being heard?
  • Could I include contextually relevant work from diverse geographical regions in my reading list?
Do note that this tool right now only works for items with a DOI. This means that any reading list items that are textbooks or reports may not be included. Hence it should not be looked as a score of your reading list but more as a guiding tool to reflect.
It’s important to recognize that when you only look at evidence through a Western lens, you miss a significant part of the world Senior Teaching Fellow Module Lead – School of Public Health
Accessing the tool
Two versions of the tool exist. The main version of the tool is hosted on Power BI. This version incorporates reading list data from Leganto. It gathers article metadata from Scopus and integrates this with country income data from the World Bank.
 
The image below shows the Power BI dashboard with information on all reading lists at Imperial published on Leganto since 2016. Dots on the map represent countries with affiliated authors, with the size of each dot in proportion to the number of authors affiliated with an institution in that country.

The tool is available to all staff here. Please note you will need to be given permission to access Power BI if you do not already have it. You can also request a consultation meeting if you need assistance navigating the platform and wish to learn more about how to engage in meaningful exploration of your reading list or curriculum using the Power BI platform.

A “lite” version of the tool also exists. This version allows users to input a DOI, or a list of DOIs, rather than obtaining data automatically from Leganto. Article metadata for this version comes from OpenAlex. The lite version is intended for staff or students who may wish to interrogate the geographic distribution of author institutional affiliations of articles they are citing on a research paper or an assessment.