Summer 2024 - GSWS 399 D100

Gender, Sex and Numbers (4)

Class Number: 3154

Delivery Method: In Person


  • Course Times + Location:

    May 6 – Jun 17, 2024: Tue, Thu, 1:30–5:20 p.m.

  • Prerequisites:

    30 units.



Through an examination of the social construction of numbers and other forms of quantitative data will provide an introduction to measurement and its use within social justice movements and policy circles. In analyzing such topics as the relationship between professional, state and community conceptualizations of quantitative evidence, students will make use of introductory statistical concepts, methods and argument. Quantitative.


In an era when “Big Data” rules, critically engaging with the production, collection, and analysis of data (of all kinds) is essential. This course examines the how and why of quantitative data from a feminist perspective. Students will be introduced to quantitative measurements and their uses, especially within social justice movements and policy circles. Students will learn to interpret and evaluate quantitative data through topics like smart cities, economic justice, and tools used to address urban liveability (safety, housing, transit).

The course focuses on critical quantitative methods, practiced independently and collaboratively, through three components: census data (how to gather and analyze it), survey data (how to design, conduct, and analyze it), and statistical concepts and methods.


COURSE FORMAT: This course is an in-person course. We will meet twice per week for six weeks. In-person attendance and participation are required.


For more detailed information please see the GSWS website:


  • Course engagement and participation 15%
  • Researcher reflections (Individual exercises, 25% in total) 25%
  • Survey research exercise (Collaborative exercise, 20%) 20%
  • Datawalk activity and analysis (Individual or collaborative exercise) 40%



Required content (journal articles, videos, etc.) will be available on Canvas, Statistics Canada, and SFU library databases.


The following texts are recommended and can be accessed through the SFU library website:

Kevin Guyan, 2022, Queer Data: Using Gender, Sex and Sexuality Data for Action. Bloomsbury Press.

Katherine McKittrick, 2021, Dear Science and Other Stories. Duke University Press.

Safiya Umoja Noble, 2018, Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press.

Caroline Criado Perez, 2019, Invisible Women: Data Bias in a World Designed for Men. Abrams Press.

Registrar Notes:


SFU’s Academic Integrity website is filled with information on what is meant by academic dishonesty, where you can find resources to help with your studies and the consequences of cheating. Check out the site for more information and videos that help explain the issues in plain English.

Each student is responsible for his or her conduct as it affects the university community. Academic dishonesty, in whatever form, is ultimately destructive of the values of the university. Furthermore, it is unfair and discouraging to the majority of students who pursue their studies honestly. Scholarly integrity is required of all members of the university.