‘Structural poverty’ maps could steer help to world’s neediest

Leveraging national surveys, big-data advances and machine learning, Cornell researchers have piloted a new approach to mapping poverty that could help policymakers identify the neediest people in poor countries and target resources more effectively.

This article was originally published here

LawyersLookup.ca - Find a lawyer who speaks your language