Title :
Analyzing the Gender Wage Gap in Ontario´s Public Sector
Author :
Luiza Antonie;Andrew D´Angelo;Gary Grewal;Miana Plesca
Abstract :
In this paper, we analyze the gender wage gap in Ontario?s public sector. Our analysis is based on the salaries of high earners in the public sector. Although these salaries are publicly available from Ontario?s Sunshine List, a key attribute is missing from the public data, the gender variable. We propose a 2-stage model to predict the gender based on the person?s first name, and we augment the data with the new variable. With the new database created, we analyze, present and discuss results for the gender wage gap in Ontario. The findings of this research are being used by Ontario?s provincial government to reassess and change current policies for pay equity.
Keywords :
"Remuneration","Predictive models","Cleaning","Finance","Databases","Computer science","Economics"
Conference_Titel :
Machine Learning and Applications (ICMLA), 2015 IEEE 14th International Conference on
DOI :
10.1109/ICMLA.2015.171