Whether through grant application forms, interviews, metrics, internal reviews, external reviews or lotteries, funders want their proposal selection processes to do one thing: select the proposals most likely to meet their objectives, such as the creation of new knowledge or the application of research to societal challenges. Increasingly, funders recognise the importance of including a diversity of individuals and approaches in order to meet these objectives. Despite recognition of the importance of diversity, persistent inequalities in research funding are observed across many settings. Inequalities have been frequently reported for gender, but also exist across ethnicities and different fields.
Research examining gender inequalities has suggested various possible explanatory factors. Unconscious bias on the part of reviewers may play a role, as may differences between scientific fields, in applicant track records and in how applicants describe their own work. The selection process a funder uses may mitigate or exacerbate these factors.
The CRITERIA project will use data from many funders who each use a variety of different selection processes in different contexts. We will use the Funder Data Platform to: a) examine where funding inequalities do and do not exist for gender and scientific field and b) test different explanations for the presence or absence of these inequalities using a mixture of qualitative and quantitative data. This may include data from funder selection processes such as their review criteria, characteristics of applicants such as their gender, and characteristics of their applications such as the scientific field or patterns of language use. The outputs of CRITERIA will help funders understand the potential drivers of inequalities in research funding, and identify where mitigation is possible through changes to their selection processes.