Data Feminism: The Numbers Don’t Speak for Themselves
Chapter Written by Catherine D’Ignazio and Lauren Klein[1]
Learning Objectives
-
Understand the importance of context in data collection, analysis, and interpretation, recognizing how it can either reinforce or challenge existing power structures.
-
Explain the ethical considerations in data science, including the need to avoid deficit narratives and to be transparent about data limitations.
-
Gain insights into emerging practices for providing context to data, such as data biographies, datasheets for datasets, and data user guides.
- Excerpt from the book Data Feminism, Creative Commons Attribution 4.0 International License (CC-BY 4.0). It has been modified to include learning outcomes, key takeaways, and exercises. ↵
