A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
Intersectional Study of the Gender Gap in STEM through the Identification of Missing Datasets about Women: A Multisided Problem
2022
Applied Sciences
Preserved Fulltext
This paper discusses the problem of missing datasets for analysing and exhibiting the role of women in STEM with a particular focus on computer science (CS), artificial intelligence (AI) and data science (DS). It discusses the problem in a concrete case of a global south country (i.e., Mexico). Our study aims to point out missing datasets to identify invisible information regarding women and the implications when studying the gender gap in different STEM disciplines. Missing datasets about
doi:10.3390/app12125813
fatcat:wevykhh5tfcijp2raxjq46wgjq