Gender Disparity Signals: Analyzing Gender Disparities with Mobile Phone Metadata

Topic: Big Data
Type: Report
Author: Muhammad Raza Khan Date: November 2019

Getting accurate data about gender disparities can be challenging, but big data sources, like data from mobile phones and social networks, can help fill this gap.

This report explores how mobile phone data — specifically call detail records (CDRs) — can predict net primary enrollment rates of children in Pakistan, and thus highlight gendered educational inequalities and redirect policy attention to address them.

The report also finds that this method could be applied to other countries where call detail records with gender information are available, which would reduce the cost and difficulty of gathering high-resolution educational data.

Read this report.

Read the knowledge brief.

Stay in touch. Sign up for gender data updates.