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This article presents the Data Science Ethos Lifecycle, a tool for engaging responsible workflow developed by an interdisciplinary team of social scientists and data scientists working with the Academic Data Science Alliance. The tool uses a data science lifecycle framework to engage data science students and practitioners with the ethical dimensions of their practice. The lifecycle supports practitioners to increase awareness of how their practice shapes and is shaped by the social world and to articulate their responsibility to public stakeholders. We discuss the theoretical foundations from the fields of Science, Technology and Society, feminist theory, and critical race theory that animate the Ethos Lifecycle and show how these orient the tool toward a normative commitment to justice and what we call the “world-making” view of data science. We introduce four conceptual lenses—positionality, power, sociotechnical systems, and narratives—that are at work in the Ethos Lifecycle and show how they can bring to light ethical and human issues in a real-world data science project.
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Stored only when both papers are in the corpus — 17 citations exist upstream.
Papers that cite the same references — the relational fallback while embeddings are still backfilling.
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