- Instructor of record: Anjali Thapar
- Other editing teacher: Nia Cai
- Other editing teacher: Niki Davidis
- Other editing teacher: Hannah Fisher
- Other editing teacher: Vyoma Samant
- Instructor of record: Deepak Kumar
Intersectional Data Feminism
Data is often perceived as objective and impartial, but the processes of data collection, analysis, and visualization are deeply influenced by existing power structures. In this course, we will explore the intersection of data and these power structures through the lens of feminist theory. Examining the intersection of data with gender, race, class, and disability, we will question how data can both reinforce and challenge systems of oppression. Readings and discussions will center on the experiences of the affected communities as we explore methods to make data practices more inclusive and equitable. Through the combination of readings, class discussions, and hands-on activities, students will engage with key concepts in data feminism. We will apply these concepts to real-world examples, using Python for data analysis. No prior programming experience is required, as the course will provide the necessary foundational skills. By the end of the course, students will be equipped to critically analyze data practices and contribute to more just and ethical data-driven decision-making.
Data is often perceived as objective and impartial, but the processes of data collection, analysis, and visualization are deeply influenced by existing power structures. In this course, we will explore the intersection of data and these power structures through the lens of feminist theory. Examining the intersection of data with gender, race, class, and disability, we will question how data can both reinforce and challenge systems of oppression. Readings and discussions will center on the experiences of the affected communities as we explore methods to make data practices more inclusive and equitable. Through the combination of readings, class discussions, and hands-on activities, students will engage with key concepts in data feminism. We will apply these concepts to real-world examples, using Python for data analysis. No prior programming experience is required, as the course will provide the necessary foundational skills. By the end of the course, students will be equipped to critically analyze data practices and contribute to more just and ethical data-driven decision-making.
- Instructor of record: Dirk Kinsey