A successful grant application is a crucial component in the development of a researcher. Multiple studies have found biases in grant reviews that favour certain groups of researchers. These attitudes reduce the quality of research outcomes and contribute to a cyclic disadvantage to underrepresented groups, particularly in STEM.

Current efforts to overcome this issue have proven insufficient as bias in our judgement seems deeply ingrained in human behaviour. NLP is a promising interdisciplinary field with successful applications in analysing text strings without introducing bias.

This project proposes to evaluate the feasibility and effectiveness of NLP algorithms in assessing grant applications by detecting text-based criteria that define the success of an application and identifies bias-related trends.

By developing a proof of concept on the use of NLP to assess grant applications, this project outsets the foundation for the development of a tool that assists founding entities in having a more inclusive and fair review system.

Flexible funding: FA2 round 1 2023

Watch Dr Gloria Castro Quintero's presentation about the project at the IGNITE Annual Event 2024: https://youtu.be/ObKzVbiUTxY?si=hBxhUD4KqP951FaZ 

View the project web page: nlpstem.bham.ac.uk

�� Call for participants: Help us improve fairness in STEM research funding

Could the way we write grant applications influence how they are reviewed?

As part of an IGNITE+ funded project, we’re looking for UK-based STEM academics who have led a research grant application (successful or unsuccessful) to contribute to a study on language, funding outcomes and fairness in research assessment.

Your experience could help support more inclusive and transparent funding review practices.

Find out more: nlpstem.bham.ac.uk