Measuring the gender discrimination: A machine learning approach

Hugo Alatrista-Salas, Bruno Esposito, Miguel Nunez-Del-Prado, Maria Valdivieso

Research output: Contribution to conferencePaper

Abstract

Gender discrimination is a widely analyzed problem, which seems to affect different countries and cultures over time. Nowadays, we are witnesses of the social inequality reflected by the salary difference between women and men for the same employment. Since the incorporation of women into the labor market in the 1980s, the wage gap between males and females has been a subject of study. One of the traditional arguments has been linked to the feminized occupations associated with sex stereotypes, as well as, low wage, birth, and discrimination in the labor categories. In the present work, we apply clustering algorithms to the PHOGUE dataset to analyze salary difference between males and females in Spain and England.
Original languageEnglish
Pages1-6
Number of pages6
DOIs
StatePublished - 7 Feb 2018
Event2017 IEEE Latin American Conference on Computational Intelligence, LA-CCI 2017 - Proceedings -
Duration: 7 Feb 2018 → …

Conference

Conference2017 IEEE Latin American Conference on Computational Intelligence, LA-CCI 2017 - Proceedings
Period7/02/18 → …

Keywords

  • Data Mining
  • Expectation Maximization
  • Optics
  • clustering
  • gender discrimination

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