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Critical Data Studies: Ethics and Human Contexts of Data Science I
Sat, September 1, 9:00 to 10:30am, ICC, E3.3Session Submission Type: Open Panel
Abstract
This session is the first in a series of three that will explore the ethics and human contexts of data science. The papers in this panel address questions of affect in data science practice, including investigations in fieldsites such as fintech and academic data science.
Sub Unit
Individual Presentations
Locating ethic in different human contexts: just another integration problem? - Charlotte Mazel-Cabasse, UC Berkeley
Text Mining as Creative Différance - Patrick Herron, Duke University
The passions and the p-values: overwhelming openness and the affective labor of radically public scholarship - R. Stuart Geiger, UC-Berkeley Institute for Data Science; Laura Noren, Obsidian Security
The stakes of defining data science - Laura Noren, Obsidian Security; R. Stuart Geiger, UC-Berkeley Institute for Data Science
Defining the Informatic Person: Exploring How Data Relationships Are Created and Negotiated in Informatic Contexts - Ashlin Lee, CSIRO/Australian National University
Seeing Like a Supply Chain: Understanding Data in Logistics - Miriam Posner, University of California, Los Angeles