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How Child Welfare Workers Reduce Racial Disparities in Algorithmic Decisions

https://doi.org/10.1145/3491102.3501831
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1001/jamapediatrics.2020.2770openalex-snapshot
Hospital Injury Encounters of Children Identified by a Predictive Risk Model for Screening Child Maltreatment Referrals
inferredcites →https://doi.org/10.1007/978-3-319-93843-1_12openalex-snapshot
Student Learning Benefits of a Mixed-Reality Teacher Awareness Tool in AI-Enhanced Classrooms
inferredcites →https://doi.org/10.1016/j.childyouth.2011.04.005openalex-snapshot
Disentangling substantiation: The influence of race, income, and risk on the substantiation decision in child welfare
inferredcites →https://doi.org/10.1016/j.clsr.2022.105681openalex-snapshot
The flaws of policies requiring human oversight of government algorithms
inferredcites →https://doi.org/10.1016/s1470-2045(19)30333-xopenalex-snapshot
Comparison of the accuracy of human readers versus machine-learning algorithms for pigmented skin lesion classification: an open, web-based, international, diagnostic study
inferredcites →https://doi.org/10.1080/10999922.2018.1511671openalex-snapshot
Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor
inferredcites →https://doi.org/10.1109/icdmw.2009.83openalex-snapshot
Building Classifiers with Independency Constraints
inferredcites →https://doi.org/10.1109/rbme.2014.2340401openalex-snapshot
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inferredcites →https://doi.org/10.1145/2090236.2090255openalex-snapshot
Fairness through awareness
inferredcites →https://doi.org/10.1145/2783258.2783311openalex-snapshot
Certifying and Removing Disparate Impact
inferredcites →https://doi.org/10.1145/3097983.3098095openalex-snapshot
Algorithmic Decision Making and the Cost of Fairness
inferredcites →https://doi.org/10.1145/3274463openalex-snapshot
Value-Sensitive Algorithm Design
inferredcites →https://doi.org/10.1145/3287560.3287563openalex-snapshot
Disparate Interactions
inferredcites →https://doi.org/10.1145/3287560.3287590openalex-snapshot
On Human Predictions with Explanations and Predictions of Machine Learning Models
inferredcites →https://doi.org/10.1145/3290605.3300468openalex-snapshot
Unremarkable AI
inferredcites →https://doi.org/10.1145/3290605.3300760openalex-snapshot
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inferredcites →https://doi.org/10.1145/3301275.3302265openalex-snapshot
What can AI do for me?
inferredcites →https://doi.org/10.1145/3306618.3314244openalex-snapshot
Actionable Auditing
inferredcites →https://doi.org/10.1145/3313831.3376229openalex-snapshot
A Human-Centered Review of Algorithms used within the U.S. Child Welfare System
inferredcites →https://doi.org/10.1145/3313831.3376638openalex-snapshot
A Case for Humans-in-the-Loop: Decisions in the Presence of Erroneous Algorithmic Scores
inferredcites →https://doi.org/10.1145/3313831.3376873openalex-snapshot
"Why is 'Chicago' deceptive?" Towards Building Model-Driven Tutorials for Humans
inferredcites →https://doi.org/10.1145/3322640.3326705openalex-snapshot
Why Machine Learning May Lead to Unfairness
inferredcites →https://doi.org/10.1145/3351095.3372851openalex-snapshot
Counterfactual risk assessments, evaluation, and fairness
inferredcites →https://doi.org/10.1145/3351095.3372852openalex-snapshot
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inferredcites →https://doi.org/10.1145/3359152openalex-snapshot
The Principles and Limits of Algorithm-in-the-Loop Decision Making
inferredcites →https://doi.org/10.1145/3359206openalex-snapshot
"Hello AI": Uncovering the Onboarding Needs of Medical Practitioners for Human-AI Collaborative Decision-Making
inferredcites →https://doi.org/10.1145/3359280openalex-snapshot
Human Decision Making with Machine Assistance
inferredcites →https://doi.org/10.1145/3377325.3377498openalex-snapshot
Proxy tasks and subjective measures can be misleading in evaluating explainable AI systems
inferredcites →https://doi.org/10.1145/3411764.3445315openalex-snapshot
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inferredcites →https://doi.org/10.1145/3411764.3445432openalex-snapshot
“Brilliant AI Doctor” in Rural Clinics: Challenges in AI-Powered Clinical Decision Support System Deployment
inferredcites →https://doi.org/10.1145/3411764.3445717openalex-snapshot
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inferredcites →https://doi.org/10.1145/3419249.3420149openalex-snapshot
Shifting Concepts of Value
inferredcites →https://doi.org/10.1145/3476089openalex-snapshot
A Framework of High-Stakes Algorithmic Decision-Making for the Public Sector Developed through a Case Study of Child-Welfare
inferredcites →https://doi.org/10.1146/annurev-lawsocsci-041221-023808openalex-snapshot
Algorithms and Decision-Making in the Public Sector
inferredcites →https://doi.org/10.1177/0002716220980329openalex-snapshot
Racial Disproportionality and Disparities in the Child Welfare System: Why Do They Exist, and What Can Be Done to Address Them?
inferredcites →https://doi.org/10.1191/1478088706qp063oaopenalex-snapshot
Using thematic analysis in psychology
inferredcites →https://doi.org/10.1542/peds.2010-1710openalex-snapshot
Racial Bias in Child Protection? A Comparison of Competing Explanations Using National Data
inferredcites →https://doi.org/10.2105/ajph.2016.303545openalex-snapshot
Lifetime Prevalence of Investigating Child Maltreatment Among US Children
inferredcites →https://doi.org/10.24963/ijcai.2020/212openalex-snapshot
Learning to Complement Humans
inferredcites →https://doi.org/10.52214/cjrl.v11i4.8741openalex-snapshot
Calculating the Souls of Black Folk
inferredcites →https://doi.org/10.5860/choice.39-6752openalex-snapshot
Shattered bonds: the color of child welfare
inferredcites →https://doi.org/10.7249/rr233openalex-snapshot
Predictive Policing: The Role of Crime Forecasting in Law Enforcement Operations

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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Black–White differences in Child Protective Services involvement: Evidence on the role of differential ‘risk’
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Algorithms, Humans, and Racial Disparities in Child Protection Systems: Evidence From the Allegheny Family Screening Tool
inferred← citeshttps://doi.org/10.1007/978-3-032-18443-6_21openalex-snapshot
AI in Social Work Research
inferred← citeshttps://doi.org/10.1007/978-3-032-18443-6_4openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.chiabu.2025.107646openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.childyouth.2024.107454openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.childyouth.2024.107891openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.childyouth.2024.107930openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.childyouth.2026.108974openalex-snapshot
Predicting child welfare involvement in Ontario children and youth accessing mental health services: development of the Child and Youth Protection Risk Algorithm (CYPRA)
inferred← citeshttps://doi.org/10.1073/pnas.2421111122openalex-snapshot
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inferred← citeshttps://doi.org/10.1080/0144929x.2024.2448719openalex-snapshot
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inferred← citeshttps://doi.org/10.1080/10999922.2023.2264413openalex-snapshot
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inferred← citeshttps://doi.org/10.1080/1369118x.2023.2234987openalex-snapshot
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inferred← citeshttps://doi.org/10.1080/15228835.2024.2402982openalex-snapshot
Implementing Algorithmic Decision-Making Tools in Child Welfare Systems: Practitioner Perspectives on Use and Usefulness
inferred← citeshttps://doi.org/10.1080/15548732.2024.2312846openalex-snapshot
Qualitative exploration of child welfare workers’ decision-making experiences and perspectives on fairness
inferred← citeshttps://doi.org/10.1080/15548732.2026.2689958openalex-snapshot
Evaluating disability bias in the Allegheny Family Screening Tool: implications for child welfare decisions
inferred← citeshttps://doi.org/10.1145/3500868.3560484openalex-snapshot
Who Has an Interest in “Public Interest Technology”?: Critical Questions for Working with Local Governments & Impacted Communities
inferred← citeshttps://doi.org/10.1145/3531146.3533177openalex-snapshot
Imagining new futures beyond predictive systems in child welfare: A qualitative study with impacted stakeholders
inferred← citeshttps://doi.org/10.1145/3532106.3533556openalex-snapshot
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inferred← citeshttps://doi.org/10.1145/3544548.3580959openalex-snapshot
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inferred← citeshttps://doi.org/10.1145/3544548.3581131openalex-snapshot
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inferred← citeshttps://doi.org/10.1145/3544548.3581253openalex-snapshot
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inferred← citeshttps://doi.org/10.1145/3544548.3581308openalex-snapshot
Rethinking "Risk" in Algorithmic Systems Through A Computational Narrative Analysis of Casenotes in Child-Welfare
inferred← citeshttps://doi.org/10.1145/3555101openalex-snapshot
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inferred← citeshttps://doi.org/10.1145/3579628openalex-snapshot
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inferred← citeshttps://doi.org/10.1145/3593013.3594081openalex-snapshot
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inferred← citeshttps://doi.org/10.1145/3593013.3594094openalex-snapshot
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inferred← citeshttps://doi.org/10.1145/3593013.3594111openalex-snapshot
Capturing Humans’ Mental Models of AI: An Item Response Theory Approach
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inferred← citeshttps://doi.org/10.1145/3613904.3642247openalex-snapshot
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inferred← citeshttps://doi.org/10.1145/3613904.3642392openalex-snapshot
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inferred← citeshttps://doi.org/10.1145/3613904.3642627openalex-snapshot
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inferred← citeshttps://doi.org/10.1145/3617694.3623259openalex-snapshot
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inferred← citeshttps://doi.org/10.1145/3630106.3658910openalex-snapshot
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inferred← citeshttps://doi.org/10.1515/9783839469057openalex-snapshot
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Protecting the vulnerable, or automating harm? AI’s double-edged role in spotting abuse
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