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13: Data Feminism- The Numbers Don’t Speak for Themselves

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    113315

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    XIII

    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.

     

    1. 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. ↵

    This page titled 13: Data Feminism- The Numbers Don’t Speak for Themselves is shared under a CC BY-NC-SA 4.0 license and was authored, remixed, and/or curated by J.J. Sylvia IV (Remixing Open Textbooks with an Equity Lens (ROTEL)) .