What question did this study set out to answer?

The research aims to establish a framework that assesses the impact of resource scarcity on education through data science techniques.

March 30, 2026Open Access

A Causal Data Science Framework for Educational Displacement Under Extreme Resource Scarcity: Simulation-Based Evidence from Gaza (2023–2026)

Key Points

The research aims to establish a framework that assesses the impact of resource scarcity on education through data science techniques.
Developed a causal data science framework combining causal inference and machine learning.
Employed inverse probability weighting and double machine learning techniques.
Utilized optimal policy trees to create intervention strategies based on simulation data.
Identified significant effects of water and nutrition interventions on improving school attendance.
Demonstrated the feasibility of using openly available data for framework calibration.
Derived practical rules for interventions based on simulated outcomes.

Abstract

This repository contains the manuscript and supplementary materials for the paper "A Causal Data Science Framework for Educational Displacement Under Extreme Resource Scarcity: Simulation-Based Evidence from Gaza (2023–2026)". The study introduces a causal data science framework combining causal inference with machine learning to estimate the effect of water and nutrition interventions on school attendance in conflict-affected settings. All parameters are calibrated from publicly available secondary data (UN, WHO, World Bank). The framework uses inverse probability weighting, double machine learning, and optimal policy trees to derive actionable intervention rules. The synthetic population and all analysis code are available in the associated GitHub repository (see "Related works" or code repository link). The manuscript is licensed under Creative Commons Attribution 4.0 International.

A Causal Data Science Framework for Educational Displacement Under Extreme Resource Scarcity: Simulation-Based Evidence from Gaza (2023–2026)

Key Points

Abstract

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