Bayesian networks versus gender bias. Issue 5 (26th September 2022)

• Record Type: Journal Article
• Authors: Mecatti, Fulvia; Vicard, Paola; Musella, Flaminia; Giammei, Lorenzo
• Is Part Of: Significance. Volume 19:Issue 5(2022)
• Page Start: 16
• Page End: 20
• Publication Date: 2022-09-26
• Subjects: Statistics -- Periodicals; Social sciences -- Periodicals; 001.422
• DOI: 10.1111/1740-9713.01684
• Languages: English
• ISSNs: 1740-9705

Abstract

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 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