Probabilistic Agent-Based Modelling for Predicting School Attendance (PhD thesis), CY P06 24 02

A substantial body of research has demonstrated that young people facing social, economic and/or health disadvantages are at the greatest risk of disengaging from education and becoming NEET (not in education, employment or training), compared to their more advantaged peers. In turn, becoming NEET has been shown to compound the risk of future disadvantage and poor life outcomes. Whilst some studies have looked at a small number of risk factors from different domains in parallel, the Connected Bradford database presents an opportunity to look at comprehensive measures of vulnerability relating to young people’s education, health, family and economic circumstances. We will use the linked data for Bradford to explore the intersectionality of factors that influence a person’s risk of becoming NEET, and to expose the compounding vulnerability for families and individuals facing disadvantage across multiple domains.

25/07/2024

3 years