Spatiotemporal Evolution of Primary School Teacher Resource Allocation in China and Its Driving Forces Analysis
This study employs spatiotemporal and machine learning models to analyze China's primary teacher resource allocation over two decades, revealing a shift in inequality from inter-regional to intra-provincial disparities driven by urbanization and demographic changes, while identifying distinct regional drivers for teacher ratios and qualifications to inform targeted fiscal and policy reforms.