About the Study
Goal
Exploring how offline Natural Language Processing (NLP) could support fairer grant review
How?
Looking at patterns in the language of successful and unsuccessful grant applications
Targeted Insights
- What language patterns appear in successful and unsuccessful STEM grant applications
- Whether some wording, framing, or assessment criteria may reflect or reinforce bias in grant review
- How NLP tools could support fairer and more transparent review practices
Why Take Part?
Your contribution will help:
- Identify potential bias in peer review processes
- Improve fairness and inclusivity in funding decisions
- Strengthen future research assessment practices
Who?
UK-based academics who have led a STEM research grant application for a UK funding scheme
How?
Taking part involves uploading the PDF of the STEM research proposal(s) you would like to contribute to the study. We will also ask you to complete a short log form about the funding call(s) and application outcome(s), and a short demographic form. Find more information in the Participate tab.
How to Take Part?
Meet the Team
A group of diverse young researchers that represent three institutions in the UK
Gloria M. Castro
Project Lead
Assistant Professor
University of Birmingham
Jane Smith
Project Co-Lead
EDI Professional
Institute of Physics
Katie Nicoll Baines
Project Co-Lead
People, Culture & Environment Manager, Future Leaders Fellows Development Network
University of Edinburgh
