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Bayesian networks versus gender bias

Authors :
Mecatti, F
Vicard, P
Musella, F
Giammei, L
Mecatti, F
Vicard, P
Musella, F
Giammei, L
Publication Year :
2022

Abstract

Gender-sensitive statistics can highlight gender gaps, but current measurement tools have serious limitations Here, Fulvia Mecatti, Paola Vicard, Flaminia Musella and Lorenzo Giammei explore how Bayesian networks could help improve the measurement, monitoring and prediction of gender equality.

Details

Database :
OAIster
Notes :
ELETTRONICO, English
Publication Type :
Electronic Resource
Accession number :
edsoai.on1350081995
Document Type :
Electronic Resource