Date of Award

Fall 2024

Document Type

Dissertation

Degree Name

Doctor of Public Administration (DPA)

Department

Public Policy and Administration

Committee Chairperson

Angela Kline, Ph.D.

Committee Member

Francis Atuahene, Ph.D.

Committee Member

Mark Davis, Ph.D.

Abstract

Anti-Black racial bias in child welfare systems was explored in this qualitative study employing an anonymous online survey and virtual interviews with child welfare professionals from around the U.S. This applied research re-examined the persistent problem of racial disproportionality in child welfare intervention rates for Black children from underrepresented perspectives of social workers in the field. The research questions asked for participants’ observations of the mechanisms through which racial bias impacts families involved with child welfare systems, and what roles individual professionals take when striving to promote equity as street-level bureaucrats. Interpretive description methods were used to develop a conceptual framework of 12 social workers’ intersubjective appraisals of the organizational cultures and hierarchical power structures that reinforce racial bias in child welfare settings. Findings indicate that systemic racism functions through implicit and explicit bias reinforced by hegemonic norms in the organizational culture. Social and structural hierarchies resist attempts to promote change at the direct services level. Biased risk assessment continually leads to oppressive treatment toward low-income Black families, facilitated by collective denial, and often misguided by an inequitable goal to save Black children from their families’ poor fates. Recommendations to address these deep-seated, intersubjective dynamics include staff development interventions to dislodge implicit bias by healing racialized trauma, and to inform cultural competence toward empowerment of oppressed populations. Participants’ collective insights will inform the development of strategies to promote anti-racist child welfare practice by targeting bias at its roots, in everyday interactions and decision-making.

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