A feeling for the data: How government and nonprofit stakeholders negotiate value conflicts in data science approaches to ending homelessness

Stephen C. Slota, Kenneth R. Fleischmann, Min Kyung Lee, Sherri R. Greenberg, Ishan Nigam, Tara Zimmerman, Sarah Rodriguez and James Snow

Journal of the Association for Information Science & Technology, 2023, vol. 74, issue 6, 727-741

Abstract: Governmental and organizational policy increasingly claims to be data‐driven, data‐informed, or knowledge‐driven. We explore the data practices of local governments and nonprofits a seeking to end homelessness in the City of Austin. Drawing on 31 interviews with stakeholders, alongside the reflections and experiences of our interdisciplinary, cross‐sector collaborative team, we consider the role of data in guiding and informing interventions and policy regarding homelessness. Ending homelessness is a particularly challenging scenario for intervention, with increasing politicization, changing circumstances, and needing rapid intervention to reduce harm. In exploring some implications of data science “in the wild” as it is deployed, understood, and supported within the Travis County Continuum of Care (CoC), we analyze how data‐intensive work connects and engages across disciplinary boundaries. Furthermore, we consider how data science and the iField can collaborate in addressing complex, social problems as advisors and partners with invested organizations.

Date: 2023
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