Developing Ethical Algorithms for Placement Stability in the Foster Care System

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Student: Charlie Repaci

Mentor: Dr. Shion Guha and Devansh Saxena


The goal of this project is to use a human-centered approach grounded in current social science theory and frameworks to add context to and further develop existing placement stability and risk assessment models that are used to aid overworked social workers in making, explaining, and standardizing their decisions.


Quoted from the project page:

This project aims to collaborate with the WI Department of Children and Families and SaintA (a private non-profit organization that actually provides foster care services in WI) by utilizing important, useful and contextual caseworkers judgment that are recorded as detailed case notes but never actually used to add norms, values, and context to existing algorithms that determine placement stability. Topic modeling will be used to extract latent themes from such text and incrementally added to existing placement stability models to test improvements in outcomes.
  • Perform a literature review of topic modeling usage in the social science domain.
  • Understand latent and human context from caseworker notes in Wisconsin foster care system using the data provided from the mentor.
  • Review algorithmic biases, fairness, and transparency in the foster care system.
  • Evaluate the latent themes from text and incrementally add to existing placement stability models to test improvement in outcomes.


Week Description
Week 1
  • Orientation
  • Data Science Bootcamp
  • Begin literature review -- algorithms in social work
Week 2
  • Continue literature review -- ethics and algorithms
  • Ethics training and CITI certification
  • Technical writing workshop
Week 3
  • Continue literature review -- bias in algorithms and policy
  • Begin reviewing data
  • Develop more specific questions and a plan of analysis
Week 4
  • Exploratory data visualization
  • TBD
Week 5
  • Data analysis and model development
  • Technical presentations workshop and informal presentations
  • TBD
Week 6
  • Data analysis and model development
  • Data ethics special lecture
  • Research posters workshop
  • TBD
Week 7
  • Data analysis and model development
  • TBD
Week 8
  • Data analysis and model development
  • TBD
Week 9
  • Industry guest panel (Northwestern Mutual Data Science Institute)
  • Begin the final paper
  • Start to create project poster
  • Consider future work
Week 10
  • Prepare and give the oral presentation
  • TBD: Present project to other REU sites and see their research in return
  • Finish and submit the final paper