Can machine-learning models predict gendered labor statistics using mobile phone and geospatial data?
High-quality data on rural women’s and men’s labor is imperative for tracking progress on gender equality and women’s empowerment, and for evaluating development interventions aimed at these outcomes. Yet, there remains a general lack of sex-disaggregated data on unpaid care and domestic work, earni...
| Main Authors: | , , , |
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| Format: | Artículo preliminar |
| Language: | Inglés |
| Published: |
CGIAR GENDER Impact Platform
2024
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10568/169433 |
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