Event Details

Innovations in Social Data Science: Tackling Inequality in Resource-Constrained Contexts with Novel Data and Methods

Understanding and addressing educational and economic inequalities requires rigorous quantitative analysis. This workshop focuses on how innovative data-driven approaches can uncover the drivers and consequences of inequality, particularly in resource-constrained settings such as low and middle-income countries. Despite the transformative impact of modern computational and statistical tools in other fields, their application to the noisy, fragmented, and context-specific data often encountered in the social sciences remains limited, as these challenges make the methods not directly transferable.

This workshop will explore the intersection of novel data sources, machine learning, and methodological advancements to better understand and address inequality. Bringing together statisticians, machine learning researchers, economists, and social scientists from Lancaster and beyond, the workshop aims to bridge theoretical advances and applied challenges. Ultimately, the discussions will focus on translating cutting-edge methods into tools that inform evidence-based policies for disadvantaged communities.

Speakers include:

Alan Sanchez – Young Lives, Department of International Development, University of Oxford

André Victor Ribeiro Amaral – School of Mathematical Sciences, Southampton University

Oliver Fiala – Save the Children UK

Sahoko Ishida – Department of Computer Science, University of Oxford