In the United States, a significant population is facing an uphill battle trying to thrive in an industry that has seen exponential growth in recent years. Women, who account for approximately 50.8% of the U.S. population are statistically underpaid and underrepresented in science, technology, engineering, and mathematics (STEM). Despite women-led technology teams establishing a 21% greater return on investment than teams who don’t, and young women largely outperforming men in math according to a 2015 study, there are only three fortune 500 companies led by women, and they comprise only 10% of internet entrepreneurs. Research generates hundreds of articles, infographics, and reports showing that women are capable of, yet not thriving in technology occupations. Brent Ozar Unlimited and PayScale have provided data from the past seven years on top tech companies demographics and salaries. I have analyzed this data using various statistical methods and created Envision Equality. Using this platform, I’ve visualized and displayed data from these sources in the form of charts and infographics. The intention of this project is to start a dialogue surrounding the issue of gender discrimination in technology occupations, and begin to address it.
","abstract_html":"<p>In the United States, a significant population is facing an uphill battle trying to thrive in an industry that has seen exponential growth in recent years. Women, who account for approximately 50.8% of the U.S. population are statistically underpaid and underrepresented in science, technology, engineering, and mathematics (STEM). Despite women-led technology teams establishing a 21% greater return on investment than teams who don’t, and young women largely outperforming men in math according to a 2015 study, there are only three fortune 500 companies led by women, and they comprise only 10% of internet entrepreneurs. Research generates hundreds of articles, infographics, and reports showing that women are capable of, yet not thriving in technology occupations. <em>Brent Ozar Unlimited </em>and <em>PayScale </em>have provided data from the past seven years on top tech companies demographics and salaries. I have analyzed this data using various statistical methods and created <em>Envision Equality</em>. Using this platform, I’ve visualized and displayed data from these sources in the form of charts and infographics. The intention of this project is to start a dialogue surrounding the issue of gender discrimination in technology occupations, and begin to address it.</p>","abstract_has_math":false,"creators":["Bolewicki, Quinn"],"institution":"The Graduate School and University Center of The City University of New York","degree_name":"Master of Science","degree_level":"Master","degree_discipline":"Data Analysis & Visualization","degree_department":null,"school":null,"contributors":[],"advisors":["Aucher Serr"],"committee_chairs":[],"committee_members":[],"year":2021,"date_issued":"2021-06-01T07:00:00Z","date_published":"2021-06-01T07:00:00Z","updated_at":"2026-07-24T01:59:54Z","subjects":["Applied Statistics","Categorical Data Analysis","Digital Humanities","Feminist, Gender, and Sexuality Studies","Women's Studies","gender","pay gap","statistics","website","data","technology"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://academicworks.cuny.edu/gc_etds/4418","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Aucher Serr"]},{"key":"dc:creator","label":"Author","values":["Bolewicki, Quinn"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.available","label":"Dc Date Available","values":["2021-05-14T07:00:00Z"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Data Analysis & Visualization"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Master"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master of Science"]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["The Graduate School and University Center of The City University of New York"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Applied Statistics","Categorical Data Analysis","Digital Humanities","Feminist, Gender, and Sexuality Studies","Women's Studies","gender","pay gap","statistics","website","data","technology"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://academicworks.cuny.edu/gc_etds/4418"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["In the United States, a significant population is facing an uphill battle trying to thrive in an industry that has seen exponential growth in recent years. Women, who account for approximately 50.8% of the U.S. population are statistically underpaid and underrepresented in science, technology, engineering, and mathematics (STEM). Despite women-led technology teams establishing a 21% greater return on investment than teams who don’t, and young women largely outperforming men in math according to a 2015 study, there are only three fortune 500 companies led by women, and they comprise only 10% of internet entrepreneurs. Research generates hundreds of articles, infographics, and reports showing that women are capable of, yet not thriving in technology occupations. Brent Ozar Unlimited and PayScale have provided data from the past seven years on top tech companies demographics and salaries. I have analyzed this data using various statistical methods and created Envision Equality. Using this platform, I’ve visualized and displayed data from these sources in the form of charts and infographics. The intention of this project is to start a dialogue surrounding the issue of gender discrimination in technology occupations, and begin to address it.
"]},{"key":"dc:title","label":"Title","values":["Data Analysis and Visualization to Dismantle Gender Discrimination in the Field of Technology"]}]}],"canonical_facts":{"dc:contributor.advisor":["Aucher Serr"],"dc:creator":["Bolewicki, Quinn"],"dc:date.available":["2021-05-14T07:00:00Z"],"dc:description.abstract":["In the United States, a significant population is facing an uphill battle trying to thrive in an industry that has seen exponential growth in recent years. Women, who account for approximately 50.8% of the U.S. population are statistically underpaid and underrepresented in science, technology, engineering, and mathematics (STEM). Despite women-led technology teams establishing a 21% greater return on investment than teams who don’t, and young women largely outperforming men in math according to a 2015 study, there are only three fortune 500 companies led by women, and they comprise only 10% of internet entrepreneurs. Research generates hundreds of articles, infographics, and reports showing that women are capable of, yet not thriving in technology occupations. Brent Ozar Unlimited and PayScale have provided data from the past seven years on top tech companies demographics and salaries. I have analyzed this data using various statistical methods and created Envision Equality. Using this platform, I’ve visualized and displayed data from these sources in the form of charts and infographics. The intention of this project is to start a dialogue surrounding the issue of gender discrimination in technology occupations, and begin to address it.
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