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Analyzing the Gender Wage-gap in Ontario's Public Sector

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dc.contributor.advisor Grewal, Gary
dc.contributor.advisor Luiza, Antonie
dc.contributor.author D'Angelo, Andrew
dc.date 2016-04-20
dc.date.accessioned 2016-05-11T14:13:43Z
dc.date.available 2016-05-11T14:13:43Z
dc.date.issued 2016-05-11
dc.identifier.uri http://hdl.handle.net/10214/9653
dc.description.abstract The disparity in wages between men and women is a well known fact; however, the contribution of each known factor is not fully understood. Leveraging the salary information provided by the Ontario Ministry of Finance could allow for a better understanding of the factors that contribute to gender wage disparity. The Ontario public salary data, also known as the 'Sunshine List', contains the salary information of individuals working in the public sector that earn $100,000 or more annually. Unfortunately, the Sunshine List data is not in a form that allows for direct analysis. The information must first be collected, cleaned, and standardized due to formatting inconsistencies within the Sunshine List data. Furthermore, although these salaries are publicly available, a key attribute is missing from the public data, the gender variable. A novel hybrid model is proposed to predict the gender based on an individual's given name, and the original database is augmented with the new gender variable. With the new database created, the wage-gap is analyzed and the results are presented and discussed. The findings of this research are being used by Ontario's provincial government to reassess and change current policies for pay equity. en_US
dc.language.iso en en_US
dc.subject gender wage-gap en_US
dc.subject data cleaning en_US
dc.subject data collection en_US
dc.subject machine learning en_US
dc.subject classification en_US
dc.title Analyzing the Gender Wage-gap in Ontario's Public Sector en_US
dc.type Thesis en_US
dc.degree.programme Computer Science en_US
dc.degree.name Master of Science en_US
dc.degree.department School of Computer Science en_US


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