Predictive Risk Modeling to Identify Homeless Clients at Risk for Prioritizing Services using Routinely Collected Data

Author:

Kithulgoda Chamari I.1,Vaithianathan Rhema1,Culhane Dennis P.2

Affiliation:

1. Centre for Social Data Analytics, Auckland University of Technology, Auckland, New Zealand

2. School of Social Policy and Practice, University of Pennsylvania, Philadelphia, Pennsylvania

Publisher

Informa UK Limited

Subject

Computer Networks and Communications,General Social Sciences,Social Sciences (miscellaneous),Health (social science)

Reference41 articles.

1. The effect of combat exposure on veteran homelessness

2. Domestic violence, housing instability, and homelessness: A review of housing policies and program practices for meeting the needs of survivors

3. Burt, M. R., Pearson, C. L. & Montgomery, A. E. (2005). Strategies for preventing homelessness. http://webarchive.urban.org/UploadedPDF/1000874_preventing_homelessness.pdf.

4. Predictive modeling of housing instability and homelessness in the Veterans Health Administration

5. Couloute, L. (2018). Nowhere to go: Homelessness among formerly incarcerated people. Prison Policy Initiative. https://www.prisonpolicy.org/reports/housing.html.

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3. Multi-Target Multiplicity: Flexibility and Fairness in Target Specification under Resource Constraints;2023 ACM Conference on Fairness, Accountability, and Transparency;2023-06-12

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5. The Human Behind the Data: Reflections from an Ongoing Co-Design and Deployment of a Data-Navigation Interface for Front-Line Emergency Housing Shelter Staff;Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems;2023-04-19

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