Machine-supported decision-making to improve agricultural training participation and gender inclusivity.
Women comprise a significant portion of the agricultural workforce in developing countries but are often less likely to attend government sponsored training events. The objective of this study was to assess the feasibility of using machine-supported decision-making to increase overall training turno...
Main Authors: | Norman Peter Reeves, Ahmed Ramadan, Victor Giancarlo Sal Y Rosas Celi, John William Medendorp, Harun Ar-Rashid, Timothy Joseph Krupnik, Anne Namatsi Lutomia, Julia Maria Bello-Bravo, Barry Robert Pittendrigh |
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Format: | Article |
Language: | English |
Published: |
Public Library of Science (PLoS)
2023-01-01
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Series: | PLoS ONE |
Online Access: | https://doi.org/10.1371/journal.pone.0281428 |
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