Work

Intersectional Study of the Gender Gap in STEM through the Identification of Missing Datasets about Women: A Multisided Problem

Year: 2022

Type: article

Abstract: 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 women in STEM show that the first step to understanding gender imbalance in STEM is building women’s history by “completing” existing datasets.

Source: Applied Sciences

DOI: 10.3390/app12125813

Author: Genoveva Vargas-Solar

Institutions: Lyon 1 Université, École Centrale de Lyon, Centre National de la Recherche Scientifique, Laboratoire d'Informatique en Images et Systèmes d'Information, Institut National des Sciences Appliquées de Lyon

Language: English

Topic: Career Development and Diversity

Subfield: Safety Research

Field: Social Sciences

Domain: Social Sciences

SDGs: Reduced inequalities, Gender equality

Open Access status: gold

Estimated APC paid: $2,408