Posted on 4 November 2021
In recent years, the essential need for better evidence on judicial review decision-making has become stark, particularly given an increasing amount of policy initiatives and statements that make claims about how such cases are being decided.
To respond to this challenge, a team from York Law School (led by Dr Joe Tomlinson) and Mishcon de Reya’s data science team (led by Daniel Hoadley) have formed a partnership to explore the use of machine learning to improve the availability of evidence relating to judicial review decision-making. The project is also exploring the wider logistical and ethical challenges of using these techniques.
This exploratory project is funded by an Economic and Social Research Council Impact Acceleration Award and investment from Mishcon de Reya, and the underlying dataset being used for the project was made available by vLex Justis.
A blog post, explaining the context and objectives of the project in more detail, is available here. Full findings of the first phase of exploratory research will be published in 2022