Racial Disproportionality and Disparities in the Child Welfare System [1st ed.] 9783030543136, 9783030543143

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Child Maltreatment: Contemporary Issues in Research and Policy 11

Alan J. Dettlaff  Editor

Racial Disproportionality and Disparities in the Child Welfare System

Child Maltreatment Contemporary Issues in Research and Policy Volume 11

Series Editors Jill E. Korbin Schubert Center for Child Studies Cleveland, OH, USA Richard D. Krugman University of Colorado School of Medicine Aurora, CO, USA

This series provides a high-quality, cutting edge, and comprehensive source offering the current best knowledge on child maltreatment from multidisciplinary and multicultural perspectives. It consists of a core handbook that is followed by two or three edited volumes of original contributions per year. The core handbook will present a comprehensive view of the field. Each chapter will summarize current knowledge and suggest future directions in a specific area. It will also highlight controversial and contested issues in that area, thus moving the field forward. The handbook will be updated every five years. The edited volumes will focus on critical issues in the field from basic biology and neuroscience to practice and policy. Both the handbook and edited volumes will involve creative thinking about moving the field forward and will not be a recitation of past research. Both will also take multidisciplinary, multicultural and mixed methods approaches.

More information about this series at http://www.springer.com/series/8863

Alan J. Dettlaff Editor

Racial Disproportionality and Disparities in the Child Welfare System

Editor Alan J. Dettlaff Graduate College of Social Work University of Houston Houston, TX, USA

ISSN 2211-9701 ISSN 2211-971X (electronic) Child Maltreatment ISBN 978-3-030-54313-6 ISBN 978-3-030-54314-3 (eBook) https://doi.org/10.1007/978-3-030-54314-3 © Springer Nature Switzerland AG 2021 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors, and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Switzerland AG. The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland

Contents

Part I 1

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3

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5

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Understanding and Identifying Racial Disproportionality and Disparities

Introduction to Racial Disproportionality and Disparities in Child Welfare . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Alan J. Dettlaff

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The Evolving Understanding of Racial Disproportionality and Disparities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Alan J. Dettlaff

9

Measurement Issues in Identifying and Describing Racial Disproportionality and Disparity . . . . . . . . . . . . . . . . . . . . . . . . . . . Nancy Rolock, Qiana Cryer-Coupet, and Colleen Janczewski

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Racial Disproportionality and Disparities Among African American Children in the Child Welfare System . . . . . . . . . . . . . . . Jessica Pryce and Anna Yelick

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Racial Disproportionality and Disparities Among Latinx Children . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Michelle Johnson-Motoyama, Rebecca Phillips, and Oliver Beer

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Racial Disproportionality and Disparities Among American Indian and Alaska Native Populations . . . . . . . . . . . . . . . . . . . . . . . Terry L. Cross

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Underrepresented Populations in the Child Welfare System: Asian American and Native Hawaiian/Pacific Islander Populations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125 Rowena Fong and Georgina Petronella

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Contents

Part II

Explaining Disproportionality and Disparities

8

Racial Bias as an Explanatory Factor for Racial Disproportionality and Disparities in Child Welfare . . . . . . . . . . . . 141 Marian S. Harris

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Disproportionate Need as a Factor Explaining Racial Disproportionality in the CW System . . . . . . . . . . . . . . . . . . . . . . . 159 Brett Drake, Melissa Jonson-Reid, Hyunil Kim, Chien-Jen Chiang, and Daji Davalishvili

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Child Welfare System Issues as Explanatory Factors for Racial Disproportionality and Disparities . . . . . . . . . . . . . . . . . . . . 177 Michele D. Hanna

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How Place Matters in Child Maltreatment Disparities: Geographical Context as an Explanatory Factor for Racial Disproportionality and Disparities . . . . . . . . . . . . . . . . . . . . . . . . . . 199 Kathryn Maguire-Jack, Jill E. Korbin, Adam Perzynski, Claudia Coulton, Sarah A. Font, and James C. Spilsbury

Part III

Consequences of Disproportionality and Disparities

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Individual Consequences of Racial Disproportionality and Disparities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 215 Reiko Boyd

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The Community Impact of Racial Disproportionality: The Racial Geography of Child Welfare . . . . . . . . . . . . . . . . . . . . . 235 Dorothy Roberts

Part IV

Preventing and Reducing Disproportionality and Disparities

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Preventive Intervention: A Key Strategy for Addressing Child Welfare Disparities and Disproportionality for African American Families . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 255 Brenda Jones Harden, Laura Jimenez Parra, and Melissa Duchene-Kelly

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Workforce Development Strategies to Address Racial Disproportionality and Disparities in Child Welfare Systems . . . . . 285 Anita P. Barbee and Becky F. Antle

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Family Meetings as a System Reform to Address Racial Disproportionality and Disparities . . . . . . . . . . . . . . . . . . . . . . . . . . 309 Heather Allan, Mary Elizabeth Rauktis, Joan Pennell, Lisa Merkel-Holguin, and David Crampton

Contents

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Racial Disparities in Child Welfare: A Decision-Making Ecology View . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 339 John D. Fluke, Donald J. Baumann, Len I. Dalgleish, and Homer D. Kern

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Seeking Racial Equity in the Dependency Court . . . . . . . . . . . . . . . 353 Jesse Russell

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The Institutional Analysis: A Tool for Diagnosing Structural Contributors to Racial Disproportionality and Disparity in Child Welfare . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 375 Kristen Weber and Sarah Morrison

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Creating Comprehensive System Reform to Reduce Racial Disproportionality and Disparities: The Texas Community Engagement Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 397 Joyce James, Donald J. Baumann, Carolyne Rodriguez, Sheila Craig, and Stephanie Kathan

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Legislative Solutions to Address Racial Disproportionality and Disparities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 413 Jessica Dixon Weaver

Part V 22

Conclusion

Towards an Anti-Racist Child Welfare Future . . . . . . . . . . . . . . . . 441 Alan J. Dettlaff and Reiko Boyd

Part I

Understanding and Identifying Racial Disproportionality and Disparities

Chapter 1

Introduction to Racial Disproportionality and Disparities in Child Welfare Alan J. Dettlaff

1.1

Introduction

The overrepresentation of children of color in the child welfare system has long been identified as a concern in the field of child welfare. Commonly referred to as racial disproportionality, this phenomenon has most significantly impacted Black children, with national data indicating that Black children represent 23% of children in foster care, although they represent only 14% of children in the general population (KIDS Count Data Center, 2019; United States Department of Health and Human Services, 2019). This overrepresentation of Black children has been observed in the child welfare system for more than 50 years (Billingsley & Giovannoni, 1972), yet persists as a national problem. While the national dialogue has focused largely on the overrepresentation of Black children, racial disproportionality has also been observed among Native American and Latinx children, although to a lesser degree and with variations by state. Racial disproportionality among children in foster care results from racial disparities that occur along the child welfare service pathway. Beginning with the initial report of alleged maltreatment, children who are subjects of these reports become involved in a process in which multiple decisions are made that affect the likelihood of their entry into and exit from foster care. These decisions are made not only by child welfare caseworkers, but also by supervisors, agency administrators, family court judges, and other legal professionals, as well as professionals external to the child welfare system and the general public. At each of these decision-making points, there exists the potential for disparities to occur that differentially impact children of color. Ultimately, racial disparities that occur in both entries into the system and exits from the system produce racial disproportionality.

A. J. Dettlaff (*) University of Houston, Houston, TX, USA e-mail: [email protected] © Springer Nature Switzerland AG 2021 A. J. Dettlaff (ed.), Racial Disproportionality and Disparities in the Child Welfare System, Child Maltreatment 11, https://doi.org/10.1007/978-3-030-54314-3_1

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Defining and Identifying Racial Disproportionality and Disparities

The terms disproportionality and disparities have held numerous definitions in the child welfare literature devoted to this topic. The concept of disproportionality in child welfare grew from efforts in the juvenile justice system to measure and understand disproportionate minority contact and arose out of growing awareness and acknowledgement that children of different races were represented in the child welfare system at different rates. The initial identification and use of the term disproportionality was intended to document this phenomenon and to acknowledge the need to better understand why this was occurring. However, as the understanding of disproportionality evolved over time, and the identification of racial disparities emerged as a means of documenting differential outcomes experienced by children of color, the terms have often been confused or used interchangeably to denote the presence of racial inequities in the child welfare system. Yet understanding the meaning of these terms and what they mean for child welfare systems is an important component in developing an appropriate response to address them.

1.2.1

Disproportionality

The term disproportionality refers to the state of being out of proportion. It describes a condition that exists when the proportion of individuals of a certain race in a target population differs from the proportion of individuals of the same group in a reference population. In the context of the child welfare system, disproportionality is most commonly used to describe a condition when the proportion of one group in the child welfare population (i.e., children in foster care) is either proportionately larger (overrepresented) or smaller (underrepresented) than the proportion of the same group in the general child population. As stated previously, national data from 2018 show that Black children represent 23% of children in foster care, although they represented only 14% of children in the general population, indicating overrepresentation with a disproportionality ratio of 1.6.1 This represents a decrease in disproportionality since 2000 when Black children represented 38% of children in foster care and 16% of the child population, a ratio of 2.5 (Summers, Wood, & Russell, 2012). In addition to overrepresentation at the national level, Black children are consistently overrepresented at the state level. In 2015, Black children were overrepresented in 46 of 50 states with disproportionality ratios ranging from 1.1 (Alabama, Arkansas, Maine, Montana, Tennessee) to 3.5 (Iowa) (National Council of Juvenile and Family Court Judges [NCJFCJ], 2017). 1

The disproportionality ratio is calculated by dividing the percentage of children in foster care for a given year from one racial group by the percentage of children in the child population (under 18) from the same racial group in the same year.

1 Introduction to Racial Disproportionality and Disparities in Child Welfare

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These patterns differ for children of other races. Native American children represent approximately 2% of children in foster care although they represent only 1% of children in the general population, indicating overrepresentation with a ratio of 2.0. Native American children are overrepresented in 20 states, with disproportionality ratios as high as 13.1 in Minnesota (NCJFCJ, 2017). Latinx children are underrepresented at the national level, as they represent 21% of children in foster care although they make up 25% of the general child population. However, they are overrepresented in 20 states with a disproportionality ratio as high as 9.0 in Maine (NCJFCJ, 2017). Asian American and Pacific Islander children are consistently underrepresented at both the national and state levels, although they are overrepresented in one state—Hawaii—with a disproportionality ratio of 1.4 (NCJFCJ, 2017).

1.2.2

Disparity

While disproportionality refers to the state of being out of proportion, disparity refers to a state of being unequal. In the child welfare system, disparity is used to describe unequal outcomes experienced by one racial group when compared to another racial group (in contrast, disproportionality compares the proportion of one racial group in the child welfare system to the same racial group in the population). Disparities can occur at every decision-making point in the child welfare system, including the initial report that brings children to the attention of the system, acceptance of reports for investigation, substantiation of maltreatment, entries into foster care, and exits from foster care. For example, if the rate of Black children being reported to the child welfare system in one state is considerably greater than the rate of White children being reported to the same system, this would denote a disparity. Over the past two decades, a considerable number of studies have identified disparities at various decision-making points along the child welfare service delivery pathway. These include the initial report of alleged maltreatment (Miller, 2008; Putnam-Hornstein, Needell, King, & Johnson-Motoyama, 2013), acceptance for investigation (Fluke, Yuan, Hedderson, & Curtis, 2003; Harris & Hackett, 2008), substantiation of alleged maltreatment (Font, Berger, & Slack, 2012; PutnamHornstein et al., 2013), placement into out-of-home care (Maguire-Jack, Font, & Dillard, 2020; Rivaux et al., 2008), and exits from care (Huggins-Hoyt, Briggs, Mowbray, & Allen, 2019; Miller, 2008). These racial disparities that impact both entries into foster care and exits from foster care produce and maintain the overrepresentation that is persistently observed in child welfare systems across the country. Thus, understanding where racial disparities exist and why they are occurring is essential to understanding disproportionality.

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Organization of This Volume

This text is designed as a comprehensive overview of our current understanding of racial disproportionality and disparities in the child welfare system, why they exist, the consequences of their existence, and strategies to address them. Foundational to this text is an understanding and acknowledgement of racism as the overarching contributing factor to the existence of racial disproportionality and disparities. This framework for understanding disproportionality and disparities is presented in Chap. 2, along with a historical examination of how our understanding of racial disproportionality and disparities has evolved over time. Chapter 3 presents the approaches that are used to identify the presence of racial disproportionality and disparities, as well as some of the challenges associated with measurement. Chapters 4–7 then review the existence of racial disproportionality and disparities as they are manifested across various populations of children and families. Part II presents the various explanations for why racial disproportionality and disparities exist organized around four primary contributing factors identified in the literature—racial bias, disproportionate need, child welfare system issues, and geographic context. Each of these chapters address the overarching role of racism as the underlying contributing factor to their focal issue. Each of these chapters should also be understood as complementary and related to each other, as disproportionality and disparities are complex phenomena that result from multiple and inter-related concerns. Part III presents a discussion of the consequences of racial disproportionality and disparities, at both the individual and community levels. The consequences of racial disproportionality and disparities are often neglected in child welfare literature, and as such, these chapters provide an important context for understanding what results from the continued existence of disproportionality and disparities and the harm that is caused to vulnerable children and families. Part IV presents various strategies that have been used by child welfare and related systems to address and reduce disproportionality and disparities, ranging from prevention to multiple forms of system-level interventions, to legislative solutions designed to enact change. These strategies are not exhaustive, yet they represent the types of large-scale efforts that are necessary to bring about meaningful change. Part IV concludes with a vision for an anti-racist future that examines what it will really take if we are to eliminate racial disproportionality and disparities in the child welfare system. After decades of efforts to address these concerns, we have seen improvements, yet debates that persist about the causes of disproportionality have largely stalled efforts to address this, and what has been known to be a problem in child welfare systems for decades is now viewed by some as an acceptable status quo. An anti-racist future begins with the acknowledgement that racial inequities in any social service system, as well as in society at large, are never an acceptable status quo. Eliminating the racial inequities that exist in child welfare will take bold steps that completely reimagine our understanding of what child welfare means.

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Ultimately, an anti-racist future envisions a child welfare agency that achieves racial equity by keeping families together rather than separating them. Only when this occurs, can real equity be achieved.

References Billingsley, A., & Giovannoni, J. M. (1972). Children of the storm: Black children and American child welfare. New York: Harcourt Brace Jovanivich. Fluke, J. D., Yuan, Y. T., Hedderson, J., & Curtis, P. A. (2003). Disproportionate representation of race and ethnicity in child maltreatment: Investigation and victimization. Children and Youth Services Review, 25, 359–373. Font, S. A., Berger, L. M., & Slack, K. S. (2012). Examining racial disproportionality in child protective services case decisions. Children and Youth Services Review, 34, 2188–2200. Harris, M. S., & Hackett, W. (2008). Decision points in child welfare: An action research model to address disproportionality. Children and Youth Services Review, 30(2), 199–215. Huggins-Hoyt, K. Y., Briggs, H. E., Mowbray, O., & Allen, J. L. (2019). Privatization, racial disproportionality and disparity in child welfare: Outcomes for foster children of color. Children and Youth Services Review, 99, 125–131. KIDS Count Data Center. (2019). Child population by race in the United States. Retrieved from https://datacenter.kidscount.org/data/tables/103-child-population-by-race#detailed/ Maguire-Jack, K., Font, S. A., & Dillard, R. (2020). Child protective services decision-making: The role of children’s race and county factors. American Journal of Orthopsychiatry, 90(1), 48–62. Miller, M. (2008). Racial disproportionality in Washington State’s child welfare system. Olympia, WA: Washington State Institute for Public Policy. National Council of Juvenile and Family Court Judges. (2017). Disproportionality rates for children in foster care: Fiscal year 2015. Retrieved from https://www.ncjfcj.org/wp-content/ uploads/2017/09/NCJFCJ-Disproportionality-TAB-2015_0.pdf Putnam-Hornstein, E., Needell, B., King, B., & Johnson-Motoyama, M. (2013). Racial and ethnic disparities: A population-based examination of risk factors for involvement with child protective services. Child Abuse & Neglect, 37, 33–46. Rivaux, S. L., James, J., Wittenstrom, K., Baumann, D., Sheets, J., Henry, J., et al. (2008). The intersection of race, poverty, and risk: Understanding the decision to provide services to clients and to remove children. Child Welfare, 87, 151–168. Summers, A., Wood, S., & Russell, J. (2012). Disproportionality rates for children of color in foster care. Reno, NV: National Council of Juvenile and Family Court Judges. U.S. Department of Health and Human Services, Administration for Children and Families, Administration on Children, Youth and Families, Children’s Bureau. (2019). The AFCARS report: Preliminary FY 2018 estimates as of August 22, 2019. Retrieved from https://www.acf. hhs.gov/sites/default/files/cb/afcarsreport26.pdf

Alan J. Dettlaff is Dean of the Graduate College of Social Work at the University of Houston and the inaugural Maconda Brown O’Connor Endowed Dean’s Chair. Prior to joining the University of Houston, Dean Dettlaff served on the faculty of the Jane Addams College of Social Work at the University of Illinois at Chicago. He received his bachelor’s degree in social work from TCU, and master’s in social work and PhD from the University of Texas at Arlington. Dean Dettlaff’s research focuses on improving outcomes for children and youth in the child welfare system by examining and addressing issues of structural and institutional racism that contribute to the disproportionate overrepresentation of children of color in this system.

Chapter 2

The Evolving Understanding of Racial Disproportionality and Disparities Alan J. Dettlaff

2.1

Introduction

As noted in Chap. 1, racial disproportionality has been observed in the child welfare system for more than 50 years. Yet although the existence of racial disproportionality is well documented, the factors that contribute to this problem have been the subject of debate in recent years. At issue is whether the observed levels of overrepresentation result from racial bias within child welfare systems or from differing levels of need among children and families of color. Recent critiques of efforts to address disproportionality have brought increased attention to this issue, particularly concerning observed disparities in the incidence of maltreatment and the subsequent need for intervention. Elizabeth Bartholet (2009), in her paper The Racial Disproportionality Movement in Child Welfare: False Facts and Dangerous Directions, contended that the observed differences in the representation of Black children in the child welfare system occur because Black children are in fact maltreated at higher rates than children of other races, and thus should be placed into foster care at higher rates than other children. She contended that higher rates of maltreatment in Black families are to be expected because Black children are more likely to be exposed to many of the risk factors associated with maltreatment, including poverty, substance abuse, and single parenting. These claims were initially met with resistance, as prior research, most notably the federally funded National Incidence Studies of Child Abuse and Neglect (NIS), conducted in 1980 (NIS-1), 1986 (NIS-2), and 1993 (NIS-3), had historically shown no significant differences in the actual incidence of maltreatment across children of different racial groups (Sedlak, 1991; Sedlak & Broadhurst, 1996; Sedlak & Schultz, 2005). However, findings from the NIS-4 (Sedlak et al., 2010), released in 2010,

A. J. Dettlaff (*) University of Houston, Houston, TX, USA e-mail: [email protected] © Springer Nature Switzerland AG 2021 A. J. Dettlaff (ed.), Racial Disproportionality and Disparities in the Child Welfare System, Child Maltreatment 11, https://doi.org/10.1007/978-3-030-54314-3_2

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found for the first time that rates of maltreatment for Black children were significantly higher than those for White or Hispanic children. In supplemental analyses of these race differences, the authors concluded that these observed differences were the result of greater precision of the NIS-4 estimates, as well as an increased disparity in income between Black and White families since the NIS-3 (Sedlak, McPherson, & Das, 2010). The discussion raised by Bartholet and the subsequent findings of the NIS-4 have led to calls to reevaluate efforts to address disproportionality, particularly those efforts that have focused on reducing bias within child welfare systems, with critics suggesting that it is not bias, but rather disproportionate need, that results in disproportionality (e.g., Drake et al., 2011). Yet others contend that racial bias still plays a role in contributing to disproportionality, despite differences in rates of maltreatment (e.g., Dettlaff et al., 2011; Rivaux et al., 2008). The body of research that has emerged over the past decade and the resulting critiques of efforts to address disproportionality have begun a debate within the child welfare field that has elicited strong feelings from many involved, with most scholars aligning themselves with one side or the other, while those in child welfare agencies and educational environments are left questioning the meaning of these research findings and how to proceed with efforts to address this issue. The result has been that many efforts to address disproportionality have stalled, and what has been known as a problem in child welfare for decades remains unresolved. Yet while findings from the NIS-4, as well as subsequent studies, have highlighted the role of poverty as a contributing factor, they do not completely explain the presence of disproportionality and disparities, nor do they sufficiently explain away the role of racial bias. Further, narratives that present explanations of racial bias and explanations of disproportionate need as opposing viewpoints lose sight of the larger problems of structural and institutional racism that contribute to both. This chapter will discuss how the understanding of disproportionality and disparities has evolved over time, and present a framework for understanding disproportionality and disparities that focuses on racism as the overarching cause of these problems. This understanding of racism as the overarching cause of disproportionality and disparities is essential to focus our attention on the real problem we must address in our efforts to achieve racial equity in child welfare systems.

2.2

Early Understandings of Disproportionality

The overrepresentation of Black children in the child welfare system was first brought to national attention by Billingsley and Giovannoni (1972) in their seminal publication, Children of the Storm: Black Children and American Child Welfare. Prior to the 1950s, Black children were largely excluded from child welfare systems, as the bulk of agencies providing child welfare services were created to serve poor White immigrants (Hogan & Siu, 1988). Yet as changes in migration patterns

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occurred among Blacks during the 1950s and 1960s, both from rural to urban areas and from the South to the North, along with an increased focus on integration and decreasing poverty rates among White children, the involvement of Black children in the child welfare system grew steadily (Billingsley & Giovannoni, 1972; Hogan & Siu, 1988). By the end of the 1970s, a number of studies had identified that Black children had emerged as the most overrepresented group in this system (e.g., Close, 1983; Shyne & Schroeder, 1978). As awareness of this overrepresentation grew throughout the 1980s and 1990s, this led to increasing calls for states to develop responses to address this issue, leading to several states passing legislation mandating system responses in the mid-2000s (e.g., Michigan Department of Human Services & Skillman Foundation, 2006; Texas Health and Human Services Commission, 2006), as well as national efforts to assist in these responses (e.g., Casey Family Programs, 2009). As awareness of racial disproportionality grew, early understandings of disproportionality were shaped largely by findings of the National Incidence Studies of Child Abuse and Neglect (NIS). The NIS is a mandated effort of the U.S. Department of Health and Human Services and has been conducted at varying intervals since 1978. The goal of the NIS is to provide estimates of the incidence of child abuse and neglect in the United States and to report changes in incidence over time. In contrast to official rates of maltreatment, which are determined by substantiated investigations of abuse or neglect conducted by child protective services (CPS) agencies, the NIS attempts to estimate the actual incidence of maltreatment by collecting data from community professionals in sentinel agencies, in addition to data from CPS. Thus, the NIS estimates include children in the official CPS statistics and those who are not. The NIS employs two standards in identifying maltreatment—the Harm Standard, which requires that an incident resulted in demonstrable harm to a child, and the Endangerment Standard, which includes children who have not yet been harmed but were believed to be endangered as a result of maltreatment (Sedlak, Mettenburg, et al., 2010). As indicated previously, prior to the release of NIS-4 in 2010, the NIS had been conducted on three occasions—NIS-1 in 1979 and 1980, NIS-2 in 1986, and NIS-3 in 1993. These prior studies had consistently found no significant differences in actual rates of maltreatment between Black children and children of other races. Specifically, NIS-3 reported: No significant or marginal racial differences in the incidence of maltreatment were found either within the NIS-3 data or in the comparison of changes since the NIS-2. This was true for both the Harm Standard and the Endangerment Standard findings. It is interesting to note that this is also the case in the NIS-2. That is, there were no significant race differences in any category for either standard, and none of the changes between the NIS-1 and the NIS-2 were modified by child’s race (Sedlak & Broadhurst, 1996, pp. 4.28–4.29).

The report went on to state: The NIS findings suggest that the different races receive differential attention somewhere during the process of referral, investigation, and service allocation, and that the differential representation of minorities in the child welfare population does not derive from inherent differences in the rates at which they are abused or neglected (pp. 8–7).

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Thus, both the findings from the NIS data and the conclusions drawn in the NIS-3 final report suggest rather unequivocally that there are no racial differences in the incidence of maltreatment and that any differential rates of representation for children of color are not the result of differences in rates of maltreatment. The report even raises the issue of “differential attention” as a factor that can explain the overrepresentation of children of color. Following the release of this report in 1996, these findings were used to point to a problem of racial bias in child welfare systems. For example, using data from the National Data Archive on Child Abuse and Neglect (NCANDS), Morton (1999) found that Black children were involved in substantiated cases of maltreatment at a rate that was disproportionate to their percentage in the population in 40 states for which data were available. In his discussion of these findings, Morton cited the NIS-3, stating, “This. . .directly contradicts the apparent higher incidence rate suggested by founded allegations of child maltreatment. How could the reported incidence based on founded allegations be so significantly out of proportion, given the NIS-3 findings?” (p. 25). Given the lack of racial differences found in the NIS-3, he later states, “As a result, one could argue that there should be proportional racial representation throughout the system. If proportional representation does not exist, a strong argument is created for the existence of differential treatment by race” (p. 26). Similarly, in a paper published the same year, Yegidis and Morton (1999) wrote: All three National Incidence Studies (NIS) conducted by the Department of Health and Human Services concluded that there are no significant or marginal differences in the incidence of child maltreatment based on race. Since incidence is measured in rates per thousand, this means that all groups should be represented in the child welfare system consistent with their proportion of the population as a whole. If not, then a basis for the presumption of bias exists (p. 1).

This interpretation of the NIS-3 findings shaped the understanding of disproportionality throughout the next decade, with many additional studies comparing the lack of racial differences in rates of maltreatment as found in the NIS-3 with the consistent overrepresentation of Black children in the child welfare system as evidence of a growing problem.

2.2.1

Subsequent Theories Regarding Disproportionality

Despite being acknowledged since the 1970s, significant national attention concerning racial disproportionality did not occur until the early 2000s, following the publication of the NIS-3, which resulted in several prominent calls for action. This led to a considerable increase in studies examining disproportionality in attempts to explain this growing problem. By the mid-2000s, several scholars had proposed theories, based on available evidence, explaining the existence of racial disproportionality. Hines, Lemon, Wyatt, and Merdinger (2004) reviewed the existing literature and proposed four potential factors that were likely interrelated: (1) parent and family risk factors, (2) social factors including poverty and

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community risks, (3) race and class biases in the child welfare system, and (4) the impact of child welfare policies such as the Multi-Ethnic Placement Act (MEPA) and the Adoption and Safe Families Act (ASFA) on children of color. Barth (2005) also proposed four models for explaining disproportionality: (1) differential need resulting from differential risk (although it was acknowledged that this did not fit well with the NIS-3), (2) racial bias that affects decision-making in child welfare agencies, (3) placement dynamics, including the increasing use of kinship care, which may result in longer lengths of stay, and (4) the multiplicative model, which suggests that the three prior factors are all at play and interact to produce disproportionality. Similarly, findings from a Government Accountability Office (2007) study examining disproportionality concluded that there were three major contributing factors to this phenomenon: (1) higher rates of poverty among Black families and the resulting risks, (2) bias and cultural misunderstandings in child welfare systems, and (3) longer stays in foster care due to difficulty in recruiting adoptive parents and the greater reliance on kinship care in cases with Black children. Thus, in much of the literature, there was consistent awareness that disproportionality was a complex phenomenon that likely resulted from multiple factors, including those within families, within communities, and within the child welfare system.

2.3

Shifting Dialogue

While awareness of these complexities was emerging in the literature, the problem of racial bias remained the predominant concern among most within the child welfare field. This was evident in many of the state-level initiatives designed to respond to disproportionality in their systems. For example, following a legislative mandate to address disproportionality in the Texas child welfare system, a priority in the state’s response was the provision of Undoing Racism training for administrators, front-line staff, and community stakeholders (James, Green, Rodriguez, & Fong, 2008). Undoing Racism is a two-and-a-half-day workshop conducted by the People’s Institute for Survival and Beyond that is designed to educate and empower participants to undo the structures of racism that hinder racial equality and to become effective organizers for change (PISAB, 2006). As of 2010, over 2000 staff and external stakeholders had participated in the Undoing Racism workshop (Baumann et al., 2010). According to a policy report released by the Alliance for Racial Equity in Child Welfare (2009), at least seven other states—including California, Florida, Illinois, Indiana, Massachusetts, Minnesota, and Washington—have used either Undoing Racism or Knowing Who You Are, a curriculum developed by Casey Family Programs highlighting the importance of understanding and addressing racial identity, as key elements in their overall strategies to address disproportionality. Yet the dialogue concerning disproportionality shifted considerably following the publication of the previously mentioned paper by Elizabeth Bartholet in 2009. In this paper, Bartholet critiqued the assertion that disproportionality was caused by racial

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discrimination or systemic biases in decision-making, stating that those making this assertion were overly relying on statistics from the NIS, and ignoring evidence to the contrary. She presented multiple critiques of the NIS data, and stated that the commonly cited assertion that these data showed no evidence of racial differences in maltreatment had been effectively debunked. The paper drew upon multiple studies that documented the increased exposure among Black families to predictors of child maltreatment, including poverty, unemployment, single-parenting, substance abuse, and disadvantaged neighborhoods, to make the claim that Black children were overrepresented in the child welfare system not because of racial bias, but because maltreatment rates were higher among Black families. Thus, overrepresentation was not only to be expected but also appropriate. But in addition to presenting an argument that overrepresentation was the result of a higher incidence of maltreatment rather than bias or discrimination, Bartholet directly criticized the emphasis among child welfare systems that focused on addressing racial bias while ignoring other potential causes, stating, “Focus on the claimed racism of child welfare workers puts attention on a non-problem, while ignoring the real problems of the black community—the societal legacy of racial injustice and the miserable socio-economic conditions that characterize too many black lives” (p. 878). Of greatest concern, she further contended that this emphasis on racial bias and the goal of reducing the number of removals of Black children would ultimately result in harm to those children, stating, If black children are in fact subject to serious maltreatment by their parents at higher rates than white children, it is in their interest to be removed at higher rates than white children. If the child welfare system is wrongfully found discriminatory, and, as a result, stops removing black children at serious risk for ongoing maltreatment, the children will suffer immediate and dangerous consequences (p. 874).

Rather than focusing their efforts on addressing racial bias, Bartholet suggested that child welfare systems’ efforts should be directed toward reducing maltreatment rates among Black children by expanding prevention programs, and through greater attention, both among child welfare systems and the larger society, to reducing the underlying social problems experienced by many Black families that increase their risk exposure. Although this paper served to raise the dialogue and challenge some previously held beliefs, many continued to point to the consistent NIS findings of no racial differences in maltreatment. This changed in 2010, following the long-awaited publication of the NIS-4 (Sedlak, Mettenburg, et al., 2010). NIS-4 collected data in 2005 and 2006, and sampled many more counties, as well as more CPS and sentinel agencies, than in previous versions of the study, which resulted in more precise estimates than in prior versions. Specifically, NIS-4 sampled 122 counties, in contrast to 42 counties sampled in NIS-3, and 29 counties sampled in NIS-2 (Sedlak, 1991; Sedlak & Broadhurst, 1996; Sedlak, Mettenburg, et al. 2010). For the first time, findings from the NIS-4 showed that rates of maltreatment for Black children were significantly higher than those for White or Hispanic children in several maltreatment categories. While there were differences according to maltreatment

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type, results of the NIS-4 found that Black children experienced significantly higher rates of overall maltreatment, overall abuse, physical abuse, and serious harm from their maltreatment (Sedlak, Mettenburg, et al., 2010). This was found under both the Harm Standard and the Endangerment Standard used by the NIS-4. The authors also noted that although the NIS-4 found a general decline in rates of maltreatment since the NIS-3, that decline was not consistent across racial groups. Rather, maltreatment rates for White children decreased more or increased less than maltreatment rates for Black children across several maltreatment categories (Sedlak, Mettenburg, et al., 2010). In supplemental analyses of these observed race differences, the authors concluded that these differences were partly the result of the greater precision of the NIS-4 estimates, as well as an increased gap in income between Black and White families since the NIS-3 (Sedlak, McPherson, & Das, 2010). While these findings were initially a surprise to some, Drake and Jonson-Reid (2011) pointed out that racial differences in maltreatment were in fact present in both the NIS-2 and NIS-3. In their review of the prior findings, they stated, “Although not significantly different, the NIS-2 and NIS-3 race point estimates were consistent with each other and with the NIS-4, both in general magnitude and valence. Black children were 87% more likely than White children to be victims of maltreatment in the NIS-2, 51% more likely in the NIS-3, and 73% more likely in the NIS-4” (p. 17). They point out that the failure to achieve statistical significance in the prior versions of the NIS was not evidence of a lack of racial differences. Rather, large confidence intervals in both the NIS-2 and NIS-3 prevented the differences that were present in the race estimates from achieving statistical significance. The combination of the Bartholet paper, which rejected the claims of the prior NIS findings, along with data from the NIS-4 which documented significant racial differences in rates of child maltreatment, substantively changed the discourse concerning racial disproportionality and disparities in the United States. The logic that had previously been used to support the notion that the overrepresentation of Black children was an indicator of bias in the child welfare system could no longer be applied, as the most current evidence now indicated that Black children experienced maltreatment at rates greater than children of other races. The Bartholet paper and the NIS-4 also brought renewed focus to the relationship between poverty and maltreatment, and the likelihood that greater exposure to poverty among Black families was a significant contributor to their overrepresentation in the child welfare system. Since then, several additional studies have shown a relationship between poverty and maltreatment among Black families, and have found that when controlling for the effects of poverty, race is not a significant factor in the observed racial differences (e.g., Laskey et al., 2012; Putnam-Hornstein, Needell, King, & JohnsonMotoyama, 2013). Combined with the NIS-4 findings on racial differences in maltreatment, many have called for a shift in both the discourse on disproportionality and in the ways in which child welfare systems respond to disproportionality (e.g., Bartholet, 2011; Bartholet, Wulczyn, Barth, & Lederman, 2011; Drake et al., 2011). These calls have advocated for responses that emphasize the role of poverty in contributing to disproportionality and a focus on prevention programs targeted to

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disadvantaged Black communities as well as broader responses that address the underlying social conditions that contribute to disproportionately negative outcomes among Black families.

2.4

Poverty and Evidence of Racial Bias

Although poverty does not cause maltreatment, a large body of research developed over the past several decades has documented that maltreatment occurs disproportionately among poor families (e.g., Drake, Lee, & Jonson-Reid, 2009; Drake & Pandey, 1996; Freisthler, Bruce, & Needell, 2007). This was confirmed in the most recent NIS-4, which found that children in low socioeconomic status households experienced some form of maltreatment at a rate more than five times the rate of other children (Sedlak, Mettenburg, et al., 2010). However, because of the absence of racial differences in maltreatment in prior versions of the NIS, the relationship between poverty and the overrepresentation of Black children in the child welfare system had often been overlooked. Yet while findings from the NIS-4, as well as subsequent studies, have supported the role of poverty as a contributing factor, they do not completely explain the presence of disproportionality and disparities, nor do they provide evidence that racial bias doesn’t further contribute to this problem. In fact, an emerging body of research has begun to examine various child welfare decision points, while controlling for family income as well as risk of maltreatment, in attempts to isolate the effects of race and its contribution to racial disparities. Using data from the Texas child welfare system, Rivaux et al. (2008) examined two related decision points—the decision to provide services to families, and among those in need of services, the decision to remove a child from home in lieu of providing in-home services. To control for poverty, the authors used measures of family household income gathered by caseworkers as part of the maltreatment investigation, and to control for risk of maltreatment, the authors used a risk score constructed by summing the scores of risk scales completed by caseworkers as part of their assessment. Additional covariates included family and child characteristics, region of the state, type of reporter, and type of maltreatment. After controlling for both poverty and risk, results indicated that race was a significant predictor of both the decision to provide services and the decision to remove children from the home. Specifically, Black children were 20% more likely to be involved in cases in which services were provided compared to White children. Among those in need of services, Black children were 77% more likely to be removed and placed into foster care in lieu of receiving services in their home when compared to White children. The inclusion of risk in this study, in addition to family income, allowed for an important interpretation to be made regarding the role of race as a factor contributing to these outcomes. In the child welfare system, decisions to remove children and place them in foster care are primarily based on the assessment of risk of future maltreatment. When risk is too great to warrant the provision of services within the

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home, removal is deemed necessary. Thus by holding both risk and income constant, the emergence of race as a significant predictor of removal indicates that the race of the child influenced the decisions made regarding that child, suggesting that racial bias in decision-making remains an important factor in contributing to racial disparities. The authors of this study also identified an interesting relationship between race, income, and risk. As would be expected, results of this study found that lower income was associated with higher perceptions of risk. However, among cases opened for services and in which children were removed, Black families were assessed as having lower risk than White families. The authors suggested that rather than race directly influencing the assessment of risk, the observed disparities may be better explained by differences in the decision threshold caseworkers use when making decisions to remove a child or provide services, with the threshold higher for White children than for Black children. Building from the prior work of Dagleish (2003), who used a signal detection framework (Tanner & Swets, 1954) to develop a model of assessment and decision-making, the authors argued that while individuals’ assessments of risk can be similar, their decision thresholds might differ. Factors influencing the assessment are those associated with the current situation or case (e.g., income), while factors influencing the decision threshold are those from the decision makers’ history or experience. In other words, the authors suggested that although income is a factor that influences risk assessment, it is not a factor that influences the decision threshold. Rather, the threshold is influenced by factors associated with the decision-maker, such as their perceptions of race. Thus, their findings suggested that although Black families were assessed as having lower risk, there was a different threshold for taking action (i.e., removal or service provision) for Black children than for White children, with Black children removed at a lower risk threshold than White children. Following this study, Dettlaff et al. (2011) used the same data to examine the substantiation decision. However, to further examine the relationship between race, risk, and income, two separate logistic regression models were analyzed. The first model controlled for income in testing the relationship between race and substantiation, while the second model controlled for both income and risk. In the first model, controlling for income and other covariates, race was not a significant predictor of the substantiation decision. Rather, income was the stronger explanatory factor with the lowest income category (less than $10,150) nearly twice as likely as the highest income category ($40,550 and greater) to predict substantiation. This finding added support to the theory that it is the disproportionately high number of Black children living in poverty and the associated risks, rather than their race itself, which contributes to the observed disparities. However, when caseworkers’ assessment of risk was included in the second model, the role of income and race as explanatory factors changed considerably. When controlling for both income and risk, race significantly predicted the substantiation decision, with Black children 15% more likely to be involved in a substantiated report compared to White children. These results provided further support to the theory developed by Rivaux et al. (2008) of differences in decision-making thresholds. Similar to the prior study, lower

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income was associated with higher risk, while Black families in both substantiated and unsubstantiated cases were assessed by caseworkers as having lower risk than White families. Yet when controlling for risk, it was not poverty that significantly predicted substantiation, but rather race that emerged as the significant predictor. Again, this suggested that although income may influence the assessment of risk, it is not a factor that influences the decision to act. Rather, the findings suggested that there are racial differences in the threshold used by caseworkers in making the substantiation decision. Specifically, the decision threshold for substantiation is higher for White children than it is for Black children. While the results of these studies have provided important evidence concerning the potential for racial bias to impact decision-making in child welfare, and thus the overrepresentation of Black children, it is important to note that other studies using different sources of data have not found a relationship between race and observed disparities after controlling for measures of poverty (e.g., Laskey et al., 2012; Putnam-Hornstein et al., 2013). However, this line of research has highlighted the need for continued research that includes measures of income and risk in attempts to understand the explanatory factors contributing to disproportionality and disparities. In addition to studies that have used statistical analyses to demonstrate the role of racial bias, a large body of qualitative studies have documented the experiences of Black families as the recipients of bias in their interactions with child welfare systems. These studies have consistently documented Black families’ experiences of differential treatment and standards, lack of cultural sensitivity, cultural misunderstandings, negative perceptions of differing parenting styles, lack of engagement, lack of culturally appropriate services, and judgments against a White parenting standard (e.g., Dettlaff & Rycraft, 2008; Harris & Hackett, 2008; Miller, Cahn, Anderson-Nathe, Cause, & Bender, 2013; Miller, Cahn, & Orellana, 2012). In studies that have included the voices of child welfare and legal professionals, these professionals have consistently affirmed the experiences of Black families, acknowledging the role of racial biases in their own decision making (Dettlaff & Rycraft, 2010; Miller et al., 2012; Miller et al., 2013). In each of these studies, professionals consistently point to a problem of racial bias among the child welfare workforce as a significant factor contributing to disproportionality, which includes not only their decision-making, but also racial biases in assessment measures, licensing standards, interventions used to assist families, and the inconsistent implementation and enforcement of child welfare policies.

2.5

Current Understandings of Disproportionality and Disparities

In their review and analysis of the body of research on racial disproportionality and disparities in child welfare, Fluke, Harden, Jenkins, and Ruehrdanz (2011) provided four explanations of these phenomena based on the most current available evidence:

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(1) disproportionate need resulting from differential risk that exists due to the disproportionate number of children and families of color living in poverty, as well as other risk factors associated with child maltreatment; (2) racial bias and discrimination, which may be present at the individual level among child welfare staff and community and mandated reporters, as well as institutional racism which may be inherent in the policies and practices of child welfare agencies; (3) child welfare system factors, including a lack of resources to adequately address the needs of children and families of color, as well as the characteristics of child welfare agency staff, and (4) geographical context, including neighborhood effects such as concentrated poverty on maltreatment rates, as well as other community contextual factors that may contribute to differential rates of maltreatment or placement outcomes. The similarity of these explanatory factors to those that had been posited prior to the shifting dialogue resulting from the Bartholet article and the findings of the NIS-4 suggests that, despite acknowledgement of racial differences in maltreatment and the role of poverty, racial disproportionality and disparities are complex problems that are caused by multiple factors that each warrant attention and consideration by child welfare systems. While it can be debated which factors contribute most to the resulting disproportionality and disparities, a more holistic approach would be to acknowledge the contribution of each and to support the continued exploration and understanding of these problems. Further, despite acknowledgement of multiple contributing factors, the debate that has occurred over the past decade has focused almost solely on the competing causes of racial bias and disproportionate need, and has largely framed these as opposing viewpoints. This has occurred despite the fact that much evidence exists in support of both explanatory factors. The result of this debate has only served to slow efforts to address disproportionality and what was once viewed as a prominent concern for child welfare systems is now viewed by many as an acceptable status quo. Narratives that frame disproportionate need as the predominant contributing factor have led some child welfare systems to believe disproportionality is something that occurs beyond their control, and as a result, believe there is nothing they can do to address it. These narratives are typically coupled with critiques of efforts to address disproportionality through anti-racism or cultural competence training, which have led some child welfare systems to no longer feel a responsibility to address issues of racial bias and in some cases, to deny it even exists. As stated previously, the result of this debate has been that attention to disproportionality and the allocation of resources to address disproportionality have largely stalled in many states and jurisdictions. Yet, as documented throughout this chapter, racial disproportionality and disparities continue to exist in child welfare systems across the country. The result of this failure to act to address this ongoing problem is the perpetuation of harm against children and families of color.

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Racism as the Underlying Cause of Racial Disproportionality and Disparities

In addition to hindering efforts to address disproportionality, the current debate in child welfare on whether disproportionality and disparities are the result of racial bias or disproportionate need distracts from the larger societal problem that contributes to both of these issues—racism. Whether disproportionality and disparities result from racial bias, disproportionate need, or both, racism is the root cause of each of these issues, as well as every other causal factor that has been identified in the literature. As has been presented within this chapter, a consistent body of research has documented the influence of racial bias on decision-making in child welfare systems. This occurs not only in the form of explicit and implicit biases among decision makers, but also through the implementation and enforcement of child welfare policies that are based largely on White standards of parenting. External to the child welfare system, poverty and disproportionate need are the result of centuries of structural and institutional racism that have created the conditions of risk that exist within children and families of color that lead to maltreatment. Beginning with the forced enslavement and dehumanization of Black people in the United States, the history of this country was founded on the gradual and continual development of laws and policies designed to maintain the supremacy of White people. The enduring consequences of these racist laws and policies include racial residential segregation, the increasing wealth gap, unequal access to quality education, and implicit and explicit biases in housing and employment that each act to perpetuate and maintain the disproportionate need experienced by Black families that contributes to their involvement in child welfare systems. Thus, the debate that exists in the child welfare field about the causes of racial disproportionality only serves to perpetuate harm against the children and families who are impacted by this, as it allows for this inequity to continue. Failure to acknowledge racism as the underlying cause of the racial disproportionality and disparities we continue to observe among children and families of color only serves to facilitate their oppression. The over-surveillance and over-removal of children of color by the child welfare system not only separates parents from children, but also contributes to feelings of anger, hostility, and distrust of government systems (Dettlaff & Rycraft, 2008; Roberts, 2002). Overrepresentation of children of color also serves to perpetuate many of the oppressive conditions and negative stereotypes that have historically and continue to affect them. In addition to the trauma caused by the involuntary forced separation of children from parents, multiple studies document the harmful effects of placement into foster care, which include low educational attainment, homelessness, unemployment, economic hardship, unplanned pregnancies, mental health disorders, and involvement in the criminal justice system (Courtney et al., 2011; Pecora et al., 2005). For children of color who spend time in foster care, these risks serve as sources of compound disadvantage in a society where they are already at risk of harmful outcomes due to societal racism and inequality.

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This harm to children and families of color by the child welfare system will continue to occur as long as racial disproportionality and disparities are allowed to exist. Racial inequities that cause disproportionate harm to one or more groups of children cannot be acceptable in any social service system. Although improvements have been made and reductions in the involvement of children of color have been observed, racial disproportionality and disparities persist in child welfare systems across the country. Decades of research have documented not only the existence of racial disproportionality and disparities, but also the harmful effects of disproportionality and disparities to children and families of color. Yet attention to these problems has waned in recent years, and this harm continues. Child welfare systems have a responsibility to act to minimize the impact of this harm and to work towards the achievement of racial equity. Until this is done, they will continue to be complicit in perpetuating a harmful and oppressive system.

References Alliance for Racial Equity in Child Welfare. (2009). Policy actions to reduce racial disproportionality and disparities in child welfare: A scan of eleven states. Washington, DC: Author. Barth, R. (2005). Child welfare and race: Models of disproportionality. In D. Derezotes, J. Poertner, & M. Testa (Eds.), Race matters in child welfare: The overrepresentation of Black children in the system (pp. 25–46). Washington, DC: CWLA Press. Bartholet, E. (2009). The racial disproportionality movement in child welfare: False facts and dangerous directions. Arizona Law Review, 51, 871–932. Bartholet, E. (2011). Race and child welfare: Disproportionality, disparity, discrimination: Re-assessing the facts, re-thinking the policy options. Retrieved from http://www.law.harvard. edu/programs/about/cap/cap-conferences/rd-conference/rd-conference-papers/rdconceptpaper %2D%2D-final.pdf Bartholet, E., Wulczyn, F., Barth, R. P., & Lederman, C. (2011). Race and child welfare. Chicago, IL: Chapin Hall at the University of Chicago. Baumann, D. J., Fluke, J., Graham, J. C., Wittenstrom, K., Hedderson, J., Rivaux, S., et al. (2010). Disproportionality in child protective services: The preliminary results of statewide reform efforts in Texas. Austin, TX: Texas Department of Family and Protective Services. Billingsley, A., & Giovannoni, J. M. (1972). Children of the storm: Black children and American child welfare. New York, NY: Harcourt Brace Jovanivich. Casey Family Programs. (2009). Breakthrough series collaborative: Reducing racial disproportionality and disparate outcomes for children and families of color in the child welfare system. Washington, DC: Author. Close, M. M. (1983). Child welfare and people of color: Denial of equal access. Social Work Research & Abstracts, 19(4), 13–20. Courtney, M. E., Dworsky, A., Brown, A., Cary, C., Love, K., & Vorhies, K. (2011). Midwest evaluation of the adult functioning of former foster youth: Outcomes at ages 26. Chicago, IL: Chapin Hall at the University of Chicago. Dagleish, L. I. (2003). Risk, needs and consequences. In M. C. Calder (Ed.), Assessments in child care: A comprehensive guide to frameworks and their use (pp. 86–99). Dorset: Russell House Publishing.

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Dettlaff, A. J., Rivaux, S. R., Baumann, D. J., Fluke, J. D., Rycraft, J. R., & James, J. (2011). Disentangling substantiation: The influence of race, income, and risk on the substantiation decision in child welfare. Children and Youth Services Review, 33, 1630–1637. Dettlaff, A. J., & Rycraft, J. R. (2008). Deconstructing disproportionality: Views from multiple community stakeholders. Child Welfare, 87(2), 37–58. Dettlaff, A. J., & Rycraft, J. R. (2010). Factors contributing to disproportionality in the child welfare system: Views from the legal community. Social Work, 55, 213–224. Drake, B., Jolley, J. M., Lanier, P., Fluke, J., Barth, R. P., & Jonson-Reid, M. (2011). Racial bias in child protection? A comparison of competing explanations using national data. Pediatrics, 127, 471–478. Drake, B., & Jonson-Reid, M. (2011). NIS interpretations: Race and national incidence studies of child abuse and neglect. Children and Youth Services Review, 33, 16–20. Drake, B., Lee, S. M., & Jonson-Reid, M. (2009). Race and child maltreatment reporting: Are Blacks overrepresented? Children and Youth Services Review, 31, 309–316. Drake, B., & Pandey, S. (1996). Understanding the relationship between neighborhood poverty and specific types of child maltreatment. Child Abuse and Neglect, 20, 1003–1018. Fluke, J. D., Harden, B. J., Jenkins, M., & Ruehrdanz, A. (2011). A research synthesis on child welfare disproportionality and disparities. In Disparities and disproportionality in child welfare: Analysis of the research (pp. 1–93). Washington, DC: Center for the Study of Social Policy. Freisthler, B., Bruce, E., & Needell, B. (2007). Understanding the geospatial relationship of neighborhood characteristics and rates of maltreatment for Black, hispanic, and White children. Social Work, 52, 7–16. Harris, M. S., & Hackett, W. (2008). Decision points in child welfare: An action research model to address disproportionality. Children and Youth Services Review, 30(2), 199–215. Hines, A. M., Lemon, K., Wyatt, P., & Merdinger, J. (2004). Factors related to the disproportionate involvement of children of color in the child welfare system: A review and emerging themes. Children and Youth Services Review, 26, 507–527. Hogan, P. T., & Siu, S. (1988). Minority children and the child welfare system: An historical perspective. Social Work, 33, 493–498. James, J., Green, D., Rodriguez, C., & Fong, R. (2008). Addressing disproportionality through undoing racism, leadership development, and community engagement. Child Welfare, 87, 279–296. Laskey, A. L., Stump, T. E., Perkins, S. M., Zimet, G. D., Sherman, S. J., & Downs, S. M. (2012). Influence of race and socioeconomic status on the diagnosis of child abuse: A randomized study. The Journal of Pediatrics, 160, 1003–1008. Michigan Department of Human Services & Skillman Foundation. (2006). Equity: Moving toward better outcomes for all of Michigan’s children. Lansing, MI: Michigan Department of Human Services. Miller, K., Cahn, K., Anderson-Nathe, B., Cause, A. G., & Bender, R. (2013). Individual and systemic/structural bias in child welfare decision making: Implications for children and families of color. Children and Youth Services Review, 35, 1634–1642. Miller, K., Cahn, K., & Orellana, E. R. (2012). Dynamics that contribute to racial disproportionality and disparity: Perspectives from child welfare professionals, community partners, and families. Children and Youth Services Review, 34, 2201–2207. Morton, T. D. (1999). The increasing colorization of America’s child welfare system: The overrepresentation of Black children. Policy and Practice, 57(4), 23–30. Pecora, P. J., Kessler, R. C., Williams, J., O’Brien, K., Downs, A. C., English, D., et al. (2005). Improving family foster care: Findings from the northwest foster care alumni study. Seattle, WA: Casey Family Programs. People’s Institute for Survival and Beyond. (2006). Anti-racist principles for effective organizing and social change. Retrieved from http://www.pisab.org

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Putnam-Hornstein, E., Needell, B., King, B., & Johnson-Motoyama, M. (2013). Racial and ethnic disparities: A population-based examination of risk factors for involvement with child protective services. Child Abuse & Neglect, 37, 33–46. Rivaux, S. L., James, J., Wittenstrom, K., Baumann, D., Sheets, J., Henry, J., & Jeffries, V. (2008). The intersection of race, poverty, and risk: Understanding the decision to provide services to clients and to remove children. Child Welfare, 87, 151–168. Roberts, D. (2002). Shattered bonds: The color of child welfare. New York: Civitas. Sedlak, A. (1991). National incidence and prevalence of child abuse and neglect 1988: Revised report. Washington, DC: U.S. Department of Health and Human Services. Sedlak, A. J., & Broadhurst, D. (1996). Third National Incidence Study of child abuse and neglect: Final report. Washington, DC: U.S. Department of Health and Human Services. Sedlak, A. J., McPherson, K., & Das, B. (2010). Supplementary analyses of race differences in child maltreatment rates in the NIS-4. Washington, DC: U.S. Department of Health and Human Services, Administration for Children and Families. Sedlak, A. J., Mettenburg, J., Basena, M., Petta, I., McPherson, K., Greene, A., et al. (2010). Fourth national incidence study of child abuse and neglect (NIS–4): Report to congress. Washington, DC: U.S. Department of Health and Human Services, Administration for Children and Families. Sedlak, A. J., & Schultz, D. (2005). Racial differences in child protective services investigation of abused and neglected children. In D. Derezotes et al. (Eds.), Race matters in child welfare: The overrepresentation of Black children in the system (pp. 97–118). Washington, DC: CWLA Press. Shyne, A. W., & Schroeder, A. G. (1978). National study of social services to children and their families: An overview. Rockville, MD: Westat. Tanner, W. P., & Swets, J. A. (1954). A decision-making theory of visual detection. Psychological Review, 61, 401–409. Texas Health and Human Services Commission. (2006). Disproportionality in child protective services: Statewide reform effort begins with examination of the problem. Austin, TX: Texas Health and Human Services Commission. U.S. Government Accountability Office. (2007). Black children in foster care: Additional HHS assistance needed to help states reduce the proportion in care (GAO Publication No. GAO-07816). Washington, DC: U.S. Government Accountability Office. Yegidis, B., & Morton, T. D. (1999). Ideas in action: Item bias and CPS assessments. Atlanta, GA: Child Welfare Institute.

Alan J. Dettlaff is Dean of the Graduate College of Social Work at the University of Houston and the inaugural Maconda Brown O’Connor Endowed Dean’s Chair. Prior to joining the University of Houston, Dean Dettlaff served on the faculty of the Jane Addams College of Social Work at the University of Illinois at Chicago. He received his bachelor’s degree in social work from TCU, and master’s in social work and PhD from the University of Texas at Arlington. Dean Dettlaff’s research focuses on improving outcomes for children and youth in the child welfare system by examining and addressing issues of structural and institutional racism that contribute to the disproportionate overrepresentation of children of color in this system.

Chapter 3

Measurement Issues in Identifying and Describing Racial Disproportionality and Disparity Nancy Rolock, Qiana Cryer-Coupet, and Colleen Janczewski

3.1

Definitions: Disproportionality Versus Disparity

In very basic terms, disproportionality refers to being out of proportion, and disparity refers to inequality or difference. A more comprehensive definition of disproportionality and disparity is discussed in Chap. 1. Child welfare research has placed a particular emphasis on how children of color are disproportionally represented in the system, and to explore disparity in access to and receipt of services and supports (Derezotes, Poertner, & Testa, 2004; Hill, 2007; McRoy, 2005; Miller & Esenstad, 2015; Wells, 2011). Disproportionality occurs when the percent of persons of a certain race or ethnicity in an identified population differ from the percentage of persons of the same group in a reference (or base) population. An examination of disproportionality can bring attention to the fact that an experience— such as involvement in the child welfare system—is more or less prevalent within a racial or ethnic group compared to another group. Once we understand that disproportionality exists for certain racial and ethnic groups, we can begin to explore the reasons for these differences.

N. Rolock (*) Jack, Joseph and Morton Mandel School of Applied Social Sciences, Case Western Reserve University, Cleveland, OH, USA e-mail: [email protected] Q. Cryer-Coupet Department of Social Work, North Carolina State University, Raleigh, NC, USA C. Janczewski Helen Bader School of Social Welfare, University of Wisconsin-Milwaukee, Milwaukee, WI, USA © Springer Nature Switzerland AG 2021 A. J. Dettlaff (ed.), Racial Disproportionality and Disparities in the Child Welfare System, Child Maltreatment 11, https://doi.org/10.1007/978-3-030-54314-3_3

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Box 3.1 Black and African American The terms Black and African American are used interchangeably in this chapter. This is in alignment with the U.S. Office of Management and Budget’s Classification on Federal Data on Race and Ethnicity. For the 2010 Census, Black or African American were defined as any person having origins in any of the Black racial groups of Africa. As such, this definition does not distinguish between people who may identify as African American, Sub-Saharan African such as Kenyan and Nigerian and Afro-Caribbean such as Haitian and Jamaican (Rastogi, Johnson, Hoeffel, & Drewery, 2011). This lack of disaggregation may have cultural implications for differential experiences and interpretation of outcomes across child welfare decision points. Disparity occurs when there are unequal outcomes for one racial or ethnic group when compared to a different racial or ethnic group. An example of disparity in child welfare is the differences by race or ethnicity for children who enter foster care. Disparities can occur at every decision-making point, including initial reports of alleged maltreatment, acceptance of reports for investigation, substantiation of maltreatment allegations, entries into substitute care, and exits from care. One of the challenges in disparity analysis resides in the choice of decision points. This will be discussed in more detail later in this chapter. Figure 3.1 illustrates the racial or ethnic makeup of children in the U.S., and those involved with the child welfare system. The first column of Fig. 3.1 presents data on the proportion of racial and ethnic groups within the general population of children in the U.S., regardless of their child welfare status; this information was gathered by the U.S. Census Bureau. The second column depicts the percentage of the same racial and ethnic groups who are victims of maltreatment. The third column is the percentage of children, by race or ethnicity, who entered foster care in the U.S. in 2016. The fourth column is the proportion of children in substitute care in the U.S. at the end of the Federal Fiscal Year 2016 (U.S. Department of Health and Human Services, 2018). It should be noted that the race or ethnicity codes were calculated so that all children of Hispanic ethnicity were coded as Hispanic, regardless of their race. Using the first two columns of data presented in Fig. 3.1, Fig. 3.2 is used to show how disproportionality and disparity are calculated. As will be discussed later in the chapter, a decision about a comparison group needs to occur first. However, for purpose of this illustration, a disproportionality rate is calculated by dividing the percent of a specific race from the ‘Victims of Maltreatment’ column by the percent of that same race in the ‘US Child Population’ column. For example, if we divide the percent of African American children who are victims of maltreatment (21%) by the percent of African American children in the U.S. population (14%) we arrive at a disproportionality rate (21/14 ¼ 1.53). Because our answer, 1.53, is higher than one, we know that African American children are over-represented as victims of maltreatment compared to their representation in the general population. Likewise, for

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100% 90% 80%

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Unknown Two or more races Native Hawaiian or Other Pacific Islander (Not HS) Asian (Not HS) American Indian (Not HS) Hispanic White (Not HS) African American (non HS)

Fig. 3.1 Percentage of children living in the United States, by race or ethnicity compared to the percentage of children involved with the foster care system in the United States in 2016. Data Sources: US Child Population: U.S. Census Bureau: Population Division, U.S. Census Bureau (2017) https://www.census.gov/data/datasets/2016/demo/popest/nation-detail.html; Victims of Maltreatment: U.S. Department of Health & Human Services (2018). Child maltreatment 2016; Substitute Care: U.S. Department of Health and Human Services, AFCARS data, report #24 (2017)

White children, the percent of White (non-Hispanic) children who are victims of maltreatment (45%) is divided by the percent of White children in the U.S. population (51%) to arrive at a disproportionality rate (45/51 ¼ 0.88). Our answer, 0.88, is lower than one, which shows that White children are underrepresented as maltreatment victims compared to their representation in the general population. In sum, in the U.S., African American children are disproportionately overrepresented in being victims of reported maltreatment, at a rate of almost twice

Fig. 3.2 Calculating disproportionality and disparity

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(1.53 times) their proportion in the general population. Although it is easy to interpret the ratio when the result is larger than one, it can be less intuitive to understand indices that are less than one. One way to present these findings is to subtract the ratio from one (1–0.88 ¼ 0.12). We can then report the underrepresentation of White children in this way: White children are 12% less likely to be reported as victims of maltreatment relative to their proportion in the U.S. population. To calculate a disparity index, we need to select a comparison group. For instance, we can compare the involvement of African American children to that of another group. For ease of illustration, we will again compare African American children to White children, but we could select any other comparison group. A disparity index is calculated by dividing the disproportionality rate for African American children (circled in blue in Fig. 3.2) by the disproportionality rate for White children (also circled in blue in Fig. 3.2) (1.53/0.88 ¼ 1.75). This is the Disparity Index. This disparity index is interpreted as: African American children are 75% more likely to be reported as victims of maltreatment than White children. Disproportionality and disparities have become value laden terms that imply inequities. In this chapter we do not discuss inequities, rather our focus is on how to measure disproportionality and disparities, and the challenges associated with different approaches. There is much research documenting the presence of disproportionality and disparities, but much less research has examined the factors explaining their presence. Box 3.2 Local Variation in Racial Makeup Data from two large U. S. States are displayed below. These data show some of the variation observed when data is examined at a more local level—here at the State level, but it could also be examined at the county or regional level. The names of states are not provided because the intention is not to highlight or draw attention to these individual states, rather to use these as examples of the variation observed by state. These data show that in State A, compared to White children, African American children are: • • • •

47% more likely to be victims of maltreatment 9% more likely to enter foster care 14% more likely to be in foster care 11% less likely to exit foster care

These data also show that, compared to White children, children of Hispanic ethnicity are: • 13% less likely to be victims of maltreatment • 7% less likely to enter foster care • 5% more likely to be in foster care (continued)

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Box 3.2 (continued) • 1% more likely to exit foster care For State B we find that, compared to White children, African American children are: • • • •

124% more likely to be victims of maltreatment 22% more likely to enter foster care 50% more likely to be in foster care 27% less likely to exit foster care

These data also show that, compared to White children, children of Hispanic ethnicity are: • • • •

21% less likely to be victims of maltreatment 48% less likely to enter foster care 18% more likely to be in foster care 81% more likely to exit foster care

These data can be downloaded, for free, from the Children’s Bureau Website for any U.S. State, and across several years. Visit: https:// cwoutcomes.acf.hhs.gov/cwodatasite/ for more information.

3.2

Population Versus Decision-Based Enumeration

One approach to examining disproportionality and disparities is to compare the racial composition of children in foster care to the racial composition of children in the U.S. population. This is referred to as population-based enumeration. Population-based enumeration is helpful for providing a general sense of disproportionality in the child welfare system. Using the data presented in Fig. 3.1, population-based disproportionality would be calculated by dividing the percent of a specific race from the ‘In Substitute Care’ column by the percent of that same race in the ‘U.S. Child Population’ column. For example, if we divide the percent of African American children in substitute care (23%) by the percent of African American

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children in the U.S. population (14%) we calculate a disproportionality rate (23/14 ¼ 1.64). This tells us that African American children are over-represented in substitute care compared to their representation in the general population. Likewise, for White children we take the percent of White (non-Hispanic) children in substitute care (44%) divided by the percent of White children in the U.S. population (51%) disproportionality to arrive at a disproportionality rate (44/51 ¼ 0.86). Our answer, 0.86, shows that White children are under-represented in substitute care, compared to their representation in the general population. However, using the general population as the denominator misses all the decisions in the child welfare system that led up to a child entering foster care. For instance, it ignores which children are most likely to be reported to Child Protective Services (CPS), and who is likely to have that report accepted for an investigation. In other words, the disparity may occur prior to a child being in foster care, at some unmeasured decision point earlier in the CPS experience. Not all children living in the U.S. come to the attention of the child welfare system, but of those who do, children of color are more likely to come in contact than White children (e.g., Child Welfare Information Gateway, 2016; Derezotes et al., 2004; Rolock, 2011; Shaw, Putnam-Hornstein, Magruder, & Needell, 2008). This initial report to child welfare can be thought of as the “front door” of the system. Disproportionality and disparity evident at this first point of contact with the system may change at the point when a decision is made to investigate a report of maltreatment, and once again, when a decision is made to remove a child from their home and bring them into state custody through the child welfare system. Thus, prior decision points may enhance or diminish the disparity observed at a later decision point. To more precisely account for disproportionality throughout the system, another approach is to calculate measures of disproportionality in a particular stage of service by comparing it to the proportion of children in a preceding decision point. This is decision-based enumeration. Specifically, each calculation uses the number of children in the preceding decision or stage of service as its denominator rather than the U.S. population. The child welfare system typically begins with an initial report of alleged maltreatment. For children who are subjects of alleged maltreatment, multiple, subsequent, nested decisions are made that ultimately impact the likelihood that they will enter state custody (foster or substitute care). Key decision points are: • If the report of maltreatment will be investigated (or deemed not necessary to investigate). • If the report is investigated, a subsequent decision is made to substantiate (find credible) the maltreatment allegation. • A decision is also made about whether a child should be removed from their home and placed in state custody. • Once in foster care, a decision is made that the child should exit substitute care to a permanent home (to reunify with her or his biological parents, or exit care through adoption or guardianship).

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These decisions are made by different people along the way, including child welfare caseworkers, their supervisors, agency administrators, judges, and legal professionals. At each point that a decision is made the potential for disproportionality exists. Thus, a decision-based approach might look at disparity at several points. The first disparity index would use children in the community’s general population as the denominator, and children reported to CPS as the numerator. Another disparity index could capture the next decision point using children reported for investigation as the denominator and children whose reports were investigated as the numerator. This would show the same group’s likelihood to have a report accepted for a full investigation (sometimes referred to as ‘screened in’) and investigated. The decision points are selected based on the decision-making process, and the availability of data. For instance, often anonymity is guaranteed for people who make calls to report potential maltreatment, and callers may be hesitant to divulge personal characteristics. Therefore, using initial reports as the first point in a decision-making process is problematic because relevant data, including race, may not be collected. The Child Welfare Information Gateway (2013) created a diagram of key child welfare decisions involved with a child’s pathway through a child welfare system (see Fig. 3.3). We can conceive of disparity indices calculated at each of the critical decision points listed in the figure. These decisions vary by site or jurisdiction, and are often more complicated than the one outlined in Fig. 3.3 (see for instance, an Alameda County diagram: https://www.alamedasocialservices.org/pub lic/services/children_and_family/AlamedaDCFSFlowChart.pdf). For ease of examination and understandability, these decisions may also be limited to just a few key decisions (see, for instance: Rolock, 2011). It is important to understand decision points in the child welfare system where disparities exist for children and families. However, to fully understand these issues, we must also examine differences in risk factors. For example, despite the fact that poverty alone should not be reason for substitute care entry, some research suggests that children living in poverty are at greater risk of maltreatment than children who do not live in poverty (Putnam-Hornstein, Needell, King, & Johnson-Motoyama, 2013; Wulczyn, 2011). This may result in disproportionate need for services in low-income communities, which may be predominately occupied by children of color. It is, therefore, incumbent upon us to explore all of the potential factors that may be causing disparities, including institutional and structural racism that may lead to increased risk for some families to live in poverty and other families to live in affluence. Finally, disproportionality rates and disparity indices identify where disparate treatment occurs. It does not suggest what should be done to address disparities and ultimately disproportionality. Strategies for addressing disparities and disproportionality should be developed locally, in consultation and collaboration with community stakeholders, and across major systems (e.g., courts, law enforcement, education, child welfare).

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Fig. 3.3 A child’s journey through the child welfare system. Source: Child Welfare Information Gateway (2013)

3.3

Issues with Measurement for Low-Incidence Groups

When a racial or ethnic group is small, certain types of disproportion and disparity can be hard to detect using typical quantitative methods. In this section, we discuss two types of challenges that occur when measuring low-incidence groups: Low confidence in statistical estimates and heterogeneous populations combined into single categories. We will also discuss alternate ways of examining the experiences of low-incidence racial and ethnic minorities.

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Analysis using inferential statistics is an important part of social science research. These analyses can help answer research questions in the field of child welfare such as whether two racial subgroups are significantly different from each other or to what extent race and ethnicity is associated with risk factors (e.g., childhood adversity) and child welfare outcomes (e.g., re-reports to CPS). The results from such analyses are only inferences based on probability and the confidence we have in these inferences is strongly influenced by sample size. Studies that use smaller samples or complex analyses may not have sufficient confidence in results about low-incidence racial and ethnic groups. Similar challenges have been encountered in health disparity research (Bilheimer & Klein, 2010; Gold, Dodd, & Neuman, 2008). To address this issue, researchers often combine small racial and ethnic subgroups into a larger “other” category. This approach may reduce the likelihood that a study will present inaccurate results, but it also reduces the study’s ability to meaningfully capture the experiences of a specific racial or ethnic group. Another option used by researchers to address this issue is to ‘over-sample’ some groups. In other words, rather than select the same percentage of children from all racial or ethnic groups, a researcher might select a larger percentage of children from underrepresented groups. In general, categories of race and ethnicity commonly used in quantitative analyses are too general to portray the diverse racial and ethnic identities of respondents. For instance, people who have mixed-race heritage may be asked to select a primary race or ethnicity, or simply be recorded in a “multi-race” or “other” category. Other ethnic groups, such as Middle Eastern/North African are not usually included as separate ethnic categories. Respondents who may identify as Middle Eastern, for instance, may feel compelled to skip race/ethnicity items, or select “White, non-Hispanic” or “other.” Even common categories such as “Hispanic” and “Asian” combine people from many countries and cultures into a single category. One study of California birth records found differences in reported and substantiated maltreatment when comparing Hispanic mothers from different countries of origin (Johnson-Motoyama et al., 2015). Specifically, the study found Puerto Rican-born mothers had the highest rates of CPS involvement compared to other Hispanic-origin mothers. Whether a family has recently immigrated also contributes to the heterogeneity found within racial or ethnic classification categories. For instance, in the same study, Johnson-Motoyoma and colleagues also found that infants with foreign-born Hispanic mothers were less likely to experience CPS reports or substantiations compared to U.S.-born Hispanic mothers. Understanding the effects of immigration and assimilation on family well-being is an emerging field of study for health, mental health, and child welfare scholars (e.g., Marks, Ejesi, & García Coll, 2014). Given the limitations of quantitative measurement, qualitative and mixed method approaches can provide important nuance and voice to the study of racial and ethnic experiences in the child welfare system. Through focus groups and interviews, researchers can incorporate the experiences of families of color not captured in quantitative data. For instance, one study conducted interviews with immigrant families involved in the Canadian child welfare system to better understand the

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challenges in their home life that may drive service needs (Maiter, Stalker, & Alaggia, 2009). Finally, even the best-intentioned child welfare researchers have to grapple with the ethical responsibility of studying families of color who have endured legacies of both systemic discrimination and unethical research practices (see Corbie-Smith, 1999 for a description of the Tuskegee syphilis study on African American men; see Hodge, 2012 for a review of research abuses conducted on American Indians). Consequently, it is not surprising that some non-White communities are reluctant to participate in research, especially by outsiders. Using researchers with similar lived experiences as study participants may help to counteract mistrust (Harris & Hackett, 2008). There has also been a growing interest in participatory action research (Kemmis & McTaggart, 2005), where families and other stakeholders collaborate with child welfare researchers in the design of the study and the interpretation of results (e.g., Miller, Cahn, & Orellana, 2012). Box 3.3 How We Measure Race in United States The U.S. Office of Management and Budget (OMB) defines the way federal agencies, including the U.S. Census, measure race and ethnicity. Researchers and non-profit agencies often adopt similar categories to ensure their data are comparable with federal data. Respondents can select multiple race categories including: White, Black or African American, American Indian or Alaska Native, Asian, Native Hawaiian or Other Pacific Islander (Office of Management and Budget, 1997). Ethnicity is a separate category and only indicates whether the person is of Hispanic origin. Federal data collection instruments, such as the U.S. census may provide other options (see questions from the 2010 Census, below), but the OMB requires that these additional categories must be able to collapse into their standard definitions. The Census questionnaire also includes the option for “some other race.” Including multiple race categories along with a separate Hispanic ethnicity item may give the respondent flexibility, but it also introduces some challenges. First, respondents of Hispanic ethnicity may be unsure what to indicate as race and select “some other race.” In fact, a recent analysis of 2000 and 2010 Census data indicated that, because of responses from Hispanics, “some other race” was the third largest race group in the 2000 and 2010 Census (Humes et al., 2011). Moreover, to make results more interpretable, researchers often recode race/ethnicity into mutually exclusive categories, such as non-Hispanic White, non-Hispanic Black, Hispanic, non-Hispanic Asian, non-Hispanic American Indian, and an “other” category. Yet recombining separate race and ethnicity categories requires researchers to make choices about where to count people of multiple races and ethnicities. For instance, should someone who identifies as African American and Hispanic be classified as mixed-race, African American, or Hispanic? Currently there are efforts underway to revise federal (continued)

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Box 3.3 (continued) reporting of the measurement of race and ethnicity (e.g., Mathews et al., 2017). In the meantime, researchers and child welfare professionals should be aware that quantitative data masks the complexity of capturing an individual’s racial and ethnic identity.

3.4

Selection of a Comparison Group

Comparison between groups is inherent to the definition of disparity (see p. 1 of this chapter). Therefore, when considering the design of studies that are meant to explore racial disparities, researchers must consider which racial and ethnic groups will be compared to one another. The selection of comparison groups also has implications for the interpretation of the study’s results. For many years, disparate treatment and outcomes of children of color in the child welfare system has often been discussed as a comparison between the treatment of Black children and White children, American Indian children and White children or Hispanic children and non-Hispanic White children. This trend is also noted in disciplines such as medicine, public health and juvenile justice. However, U.S. Census (2010) estimates continue to predict shifts in the demographics of the U.S. population. For instance, between 1990 and 2009, the non-Hispanic Black population in the United States grew by 29%; the Hispanic of

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Fig. 3.4 Using White as a comparison group

any race population grew by 116%, while the non-Hispanic White population only grew by 6%. The question arises: Is White always the appropriate comparison group? Some might argue that selecting White as the standard comparison group adds to the ease of interpretation when trying to assess differences between children of color and White children (see Fig. 3.4). However, as noted above, the racial and ethnic makeup of the U.S. is changing, thus leading to the potential for missed information if solely relying on this standard. Another option is to compare one group to ‘all others’ who are not a part of that group. For example, researchers could compare the disparity rate for Black children who are victims of maltreatment to ‘all other’ children who are victims of maltreatment (Fig. 3.5 provides a side-by-side comparison of these two methods). This method would provide a picture of the status of Black children in care without setting one stand-alone group as the standard for comparison by which all others are assessed. Some researchers calculate disparity indices for each racial or ethnic group, comparing each to ‘all others’, and to each specific group (i.e. Blacks compared to all non-Blacks, to Whites, Hispanics, Asians, Native Americans), which is the most comprehensive look at disparities (Shaw et al., 2008). However, researchers may find it difficult to provide succinct interpretations and summaries of the data using this level of detail (Fig. 3.6).

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Fig. 3.5 Example of the use of White as a comparison group compared to the use of all others as the comparison

3.5

How Other Fields Are Looking at These Issues?

Discussions about the appropriate ways to categorize, measure and interpret disparate engagement with social systems and subsequent outcomes are taking place within various disciplines. In regards to research on racial and ethnic disparities, public health officials are cautioning scholars to move away from viewing White as the standard reference group for all racial and ethnic group comparisons within the U.S. (Pérez-Stable, 2018). Among medical scholars and practitioners, the goal of the work is not simply a reduction in rates of disparity, however, it’s the complete elimination of racial and ethnic health disparities. Like public health scholars, medical scholars argue the importance of taking a nuanced approach which considers multiple and intersecting social group factors (i.e. race/ethnicity, nativity, gender, education, socioeconomic status, disability and geographic location) when constructing disparity indices and comparing change over time (Harper & Lynch, 2005). Epidemiologists support similar approaches, suggesting that differences in cross-cultural norms, attitudes and behaviors may drive differential outcomes that are not accurately interpreted when measured and normed on nonequivalent populations (Ramírez, Ford, Stewart, & Teresi, 2005). As mentioned earlier in this chapter, some of this work is taking place using qualitative and community participatory methods to ensure that groups which may be considered low-incidence, have their voices and experiences considered. For example, Van Dyke et al. (2016) used focus groups and key informant interviews to determine the most appropriate ways to aggregate tribal data to best highlight the

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Fig. 3.6 Example of the use of multiple comparison groups

health disparity concerns of five American Indian tribes from Washington, Idaho, and Montana. During this process the researchers and tribal leaders found that geographic proximity, community type, access to resources, environmental exposures and economic development, were all factors that were necessary to understand to begin to address disparate health outcomes within the tribal communities (Van Dyke et al., 2016). Additional instances of privileging the context of the group with

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disparate outcomes has been seen in research on special education (Bollmer, Bethel, Garrison-Mogren, & Brauen, 2007) and behavioral health (Gonzalez et al., 2010; Manson, 2003). As such, scholars studying racial disparities in these areas have utilized risk ratios that were constructed using the racial or ethnic group of interest as compared to all other people (i.e. Blacks compared to non-Blacks, or people of Hispanic ethnicity compared to all people who are not of Hispanic ethnicity).

3.6

Summary

At the heart of discourse about racial and ethnic disparity is the question of causality: understanding when and how disparity occurs and accrues can help inform how to intervene. Racial and ethnic disproportion and disparity are well documented in child welfare systems, but much work still needs to be done to explain their presence. Although the remaining chapters will present the latest empirical and theoretical scholarship in this area, this section presents a brief synthesis of findings that have informed the current knowledge base. More specifically, we address the notion of variability: that is, studying the variation of racial disparity over time and space, may give insight into specific explanatory factors. First, as evident in Table 3.1, from a systems perspective, disparity accrues over time. Studies have isolated factors prior to CPS involvement as well as decision points within the CPS system that contribute to disproportion and disparity. For instance, several studies have reported that socioeconomic factors, and specifically poverty, are significant risk factors for CPS-involvement (Drake et al., 2011; Font, Berger, & Slack, 2012; Putnam-Hornstein et al., 2013). The interaction between race/ethnicity, and socioeconomic risk may contribute to the disproportionally high reports of Black families to the CPS system (Putnam-Hornstein et al., 2013). Data from the CPS system also indicate that much of the racial disproportion found inside the child welfare system originates from outside the system. That is, the patterns of racial and ethnic disproportionality are established at the earliest point in the child welfare system—when allegations of maltreatment are reported to the agency (Putnam-Hornstein & Needell, 2011). The association between risk and CPS-involvement does not discount the very real effects of discrimination within communities of color or the possibility that biased decision making within child welfare agencies contributes to systemic racial and ethnic disparity. Rather, understanding the impact of family and community-level risk factors can focus attention on community-based prevention and intervention efforts as part of the solution. Second, racial and ethnic disparity is not distributed consistently across geographic areas. Using national, state, or even county data may mask variation in community level risk (Aron et al., 2010). Studies that take geography into consideration (e.g., the county in which an investigation occurs) have found that African American children are between two and five times more likely to be investigated for maltreatment than White children (Barboza, 2016; Crampton & Coulton, 2008; Drake, Lee, & Jonson-Reid, 2009; Rolock & Testa, 2005). Drake and Rank (2009)

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reported that African American children are more likely to live in racially and socioeconomically segregated neighborhoods. They also found that White children were more likely than African American children to be reported in high-poverty neighborhoods and that African American children were more likely to be reported in low-poverty neighborhoods. Clearly these issues are complex, resulting in some researchers calling for more work to be done in neighborhoods where maltreatment has gone undetected to fully understand these complex issues (Barboza, 2016). In addition to community-level differences, agencies vary widely in the likelihood to investigate, substantiate, place a child in out of home care, and ultimately reunify families. For instance, the average number of child victims per 1000 children in the U.S. 2016 was 9.1, but at the state level, this rate ranged from as low as 1.6 in Pennsylvania to as high as 23.3 in Massachusetts (U.S. Health and Human Services, 2018). Some of this variation may reflect true differences in maltreatment rates across states, but it also suggests a high degree of variability in terms of how child welfare systems respond to allegations of maltreatment. This variability across CPS agencies complicates efforts to untangle whether and how specific decision points during a CPS episode may contribute to disparity. Finally, the disparity observed in terms of children being reported and determined to be victims of maltreatment captures only part of the picture. The vast majority of CPS reports are closed without an investigation. In 2016 there were over 4.1 million referrals, where allegations of maltreatment were made. This represented 7.4 million children. Of those referrals, 58% were screened in (became maltreatment reports). Of those 2.3 million reports, 3.5 million children received a response by a child protection office. Of those, 676,000 were determined to be victims of maltreatment (U.S. Department of Health and Human Services, 2018). Even if there was no additional disparity that accrued in the system (and there is evidence that there is at least some), Black families, and other families of color, experience much higher rates of CPS involvement in their family life, and a large proportion of that involvement is ultimately found to be unwarranted.

References Aron, S. B., McCrowell, J., Moon, A., Yamano, R., Roark, D. A., Simmons, M., et al. (2010). Analyzing the relationship between poverty and child maltreatment: Investigating the relative performance of four levels of geographic aggregation. Social Work Research, 34(3), 169–179. Barboza, G. E. (2016). The geography of child maltreatment: A spatiotemporal analysis using Bayesian hierarchical analysis with integrated nested Laplace approximation. Journal of Interpersonal Violence, 1, 1–31. https://doi.org/10.1177/0886260516639583. Bilheimer, L. T., & Klein, R. J. (2010). Data and measurement issues in the analysis of health disparities. Health Services Research, 45(5p2), 1489–1507. Bollmer, J., Bethel, J., Garrison-Mogren, R., & Brauen, M. (2007). Using the risk ratio to assess racial/ethnic disproportionality in special education at the school-district level. Journal of Special Education, 41(3), 186–198. Child Welfare Information Gateway. (2013). How the child welfare system works. Washington, DC: U.S. Department of Health and Human Services, Children’s Bureau.

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Child Welfare Information Gateway. (2016). Racial disproportionality and disparity in child welfare. Washington, DC: U.S. Department of Health and Human Services, Children’s Bureau. Corbie-Smith, G. (1999). The continuing legacy of the Tuskegee Syphilis Study: Considerations for clinical investigation. American Journal of the Medical Sciences, 317(1), 5–8. Crampton, D., & Coulton, C. J. (2008). The benefits of life table analysis for describing disproportionality. Child Welfare, 87, 189–202. Derezotes, D. M., Poertner, J., & Testa, M. F. (Eds.). (2004). Race matters in child welfare: The overrepresentation of African American children in the system. Washington, DC: Child Welfare League of America. Drake, B., Jolley, J. M., Lanier, P., Fluke, J., Barth, R. P., & Jonson-Reid, M. (2011). Racial bias in child protection? A comparison of competing explanations using national data. Pediatrics, 127 (3), 471–478. Drake, B., Lee, S. M., & Jonson-Reid, M. (2009). Race and child maltreatment reporting: Are Blacks overrepresented? Children and Youth Services Review, 31, 309–316. Drake, B., & Rank, M. R. (2009). The racial divide among American children in poverty: Reassessing the importance of neighborhood. Children and Youth Services Review, 31(12), 1264–1271. Font, S. A., Berger, L. M., & Slack, K. S. (2012). Examining racial disproportionality in child protective services case decisions. Children and Youth Services Review, 34(11), 2188–2200. Gold, M., Dodd, A. H., & Neuman, M. (2008). Availability of data to measure disparities in leading health indicators at the state and local levels. Journal of Public Health Management and Practice, 14(6), S36–S44. Gonzalez, H., Vega, W., Williams, D., Tarraf, W., West, B., & Neighbors, H. (2010). Depression care in the United States: Too little for too few. Archives of General Psychiatry, 67, 37–46. Harper, S., & Lynch, J. (2005). Methods for measuring cancer disparities: Using data relevant to healthy people 2010 cancer-related objectives. Harris, M. S., & Hackett, W. (2008). Decision points in child welfare: An action research model to address disproportionality. Children and Youth Services Review, 30(2), 199–215. Hill, R. B. (2007). An analysis of racial and ethnic disproportionality and disparity at the national, state and county levels. Casey-CSSP Alliance for Racial Equity in Child Welfare. Retrieved from http://cssp.org Hodge, F. S. (2012). No meaningful apology for American Indian unethical research abuses. Ethics & Behavior, 22(6), 431–444. Humes, K., N. Jones, and R. Ramirez. (2011). Overview of race and hispanic origin: 2010, U.S. census bureau, 2010 census briefs, C2010BR-02.. Retrieved from www.census.gov/prod/ cen2010/briefs/c2010br-02.pdf. Johnson-Motoyama, M., Putnam-Hornstein, E., Dettlaff, A. J., Zhao, K., Finno-Velasquez, M., & Needell, B. (2015). Disparities in reported and substantiated infant maltreatment by maternal Hispanic origin and nativity: A birth cohort study. Maternal and Child Health Journal, 19(5), 958–968. Kemmis, S., & McTaggart, R. (2005). Participatory action research: Communicative action and the public sphere. Thousand Oaks, CA: Sage. Maiter, S., Stalker, C., & Alaggia, R. (2009). The experiences of minority immigrant families receiving child welfare services: Seeking to understand how to reduce risk and increase protective factors. Families in Society: The Journal of Contemporary Social Services, 90(1), 28–36. Manson, S. M. (2003). Extending the boundaries, bridging the gaps: crafting mental health: Culture, race, and ethnicity, a supplement to the surgeon general's report on mental health. Culture, Medicine and Psychiatry, 27(4), 395–408. Marks, A. K., Ejesi, K., & García Coll, C. (2014). Understanding the U.S. immigrant paradox in childhood and adolescence. Child Development Perspectives, 8(2), 59–64.

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Mathews, K., Phelan, J., Jones, N. A., Konya, S., Marks, R., Pratt, B. M., Coombs, J., & Bentley, M. (2017). 2015 National content test race and ethnicity analysis report. U.S. Department of Commerce, Economics and Statistics Administration, U.S. Census Bureau. McRoy, R. G. (2005). Overrepresentation of children and youth of color in foster care. In G. P. Mallon & P. M. Hess (Eds.), Child welfare for the twenty-first century: A handbook of practices, policies and programs. New York: Columbia University Press. Miller, K. M., Cahn, K., & Orellana, E. R. (2012). Dynamics that contribute to racial disproportionality and disparity: Perspectives from child welfare professionals, community partners, and families. Children and Youth Services Review, 34(11), 2201–2207. Miller, O., & Esenstad, A. (2015). Strategies to reduce racially disparate outcomes in child welfare. Retrieved from http://www.cssp.org/publications/child-welfare/alliance/Strategies-to-ReduceRacially-Disparate-Outcomes-in-Child-Welfare-March-2015.pdf Office of Management and Budget (1997). Revisions to the standards for the classification of federal data on race and ethnicity. Retrieved from www.whitehouse.gov/omb/fedreg/1997stan dards.html. Pérez-Stable, E. J. (2018, June 27). Communicating the value of race and ethnicity in research. [Blog post]. Retrieved from https://www.nih.gov/about-nih/what-we-do/science-health-publictrust/perspectives/science-health-public-trust/communicating-value-race-ethnicity-research Putnam-Hornstein, E., & Needell, B. (2011). Predictors of child protective service contact between birth and age five: An examination of California’s 2002 birth cohort. Children and Youth Services Review, 33(8), 1337–1344. Putnam-Hornstein, E., Needell, B., King, B., & Johnson-Motoyama, M. (2013). Racial and ethnic disparities: A population-based examination of risk factors for involvement with child protective services. Child Abuse & Neglect, 37, 33–46. Ramírez, M., Ford, M. E., Stewart, A. L., & Teresi, J. (2005). Measurement issues in health disparities research. Health Services Research, 40(5p2), 1640–1657. Rastogi, S., Johnson, T. D., Hoeffel, E. M., & Drewery, M. P (2011). The Black population: 2010. US Department of Commerce, Economics and Statistics Administration, US Census Bureau. Rolock, N. (2011). New methodology: Measuring racial or ethnic disparities in child welfare. Children and Youth Services Review, 33, 1531–1537. https://doi.org/10.1016/j.childyouth. 2011.03.017. Rolock, N., & Testa, M. R. (2005). Indicated child abuse and neglect reports: Is the investigation process racially biased? In D. Derezotes, J. Poertner, & M. F. Testa (Eds.), Race matters in child welfare: The overrepresentation of African American children in the system (pp. 119–130). Washington, DC: Child Welfare League of America. Shaw, T., Putnam-Hornstein, E., Magruder, J., & Needell, B. (2008). Measuring disparity in child welfare. Child Welfare, 87(2), 23–36. U.S. Census Bureau. (2010). Table 4. Estimates of the resident population by race and hispanic origin for the United States and States: July 1, 2009 (SC-EST2009-04). Retrieved from www. census.gov U.S. Census Bureau. (2017). Population estimates program, V2017. Retrieved from https://www. census.gov/quickfacts/fact/table/US/PST045217 U.S. Department of Health and Human Services, Administration on Children, Youth, and Families, Children’s Bureau. (2017). The AFCARS report [pdf file]. Retrieved from https://www.acf.hhs. gov/sites/default/files/cb/afcarsreport24.pdf. U.S. Department of Health and Human Services, Children’s Bureau. (2018). Child maltreatment 2016. Retrieved from https://www.acf.hhs.gov/cb/research-data-technology/statistics-research/ child-maltreatment Van Dyke, E. R., Blacksher, E., Echo-Hawk, A. L., Bassett, D., Harris, R. M., & Buchwald, D. S. (2016). Health disparities research among small tribal populations: Describing appropriate criteria for aggregating tribal health data. American Journal of Epidemiology, 184(1), 1–6. Wells, S. J. (2011). Disproportionality and disparity in child welfare: An overview of definitions and methods of measurement. In D. K. Green, K. Belanger, R. G. McRoy, & L. Bullard (Eds.),

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Challenging racial disproportionality in child welfare: Research, policy, and practice (pp. 3–12). Washington, DC: CWLA Press. Wulczyn, F. (2011). Research in action: Disparity, poverty, and the need for knowledge. Chapin Hall: University of Chicago.

Nancy Rolock, AM, PhD, is the Henry L. Zucker Associate Professor of Social Work Practice and Associate Dean of Research and Training at the Jack, Joseph and Morton Mandel School of Applied Social Sciences, Case Western Reserve University. She has conducted child welfare research since 1996. Her research illuminates racial and ethnic disparities in the child welfare system, and examines barriers to stability for children with child welfare experiences. Dr. Rolock is committed to using intervention research and implementation science to build evidence-informed services and supports for children and families involved in the child welfare system. Dr. Rolock has directed national research studies examining the long-term outcomes for children who have exited foster care through adoption or guardianship. Understanding the risk and protective factors associated with the long-term stability of children, and their families, is of utmost importance to the understanding of child and family well-being. Dr. Rolock seeks to illuminate these issues through her research. Qiana Cryer-Coupet is an Assistant Professor of Social Work at North Carolina State University and director of the NC Fatherhood Research Lab. Her program of research focuses on the impacts of paternal involvement on the physical and mental health of children, adolescents and families. Her current research utilizes a systems perspective to examine determinants of father involvement among Black men with children in kinship care. Within this subpopulation, she is particularly interested in paternal engagement among those who have been impacted by the criminal justice system, substance use disorders and housing instability. Dr. Cryer-Coupet teaches research methods, program evaluation and human behavior courses in the MSW program at NC State. Colleen Janczewski is an Assistant Professor at the Helen Bader School of Social Welfare, University of Wisconsin-Milwaukee and research faculty and policy analyst at the Institute for Child and Family Well-Being. Dr. Janczewski is a child welfare researcher and has designed and implemented process and outcome evaluations for child- and family-service systems in multiple states and counties across the U.S. She has expertise in applying advanced statistical techniques to inform policy decisions and practice innovations in social service systems. Her research interests include trauma and child maltreatment, decision-making in public systems, and service uptake in disengaged, stigmatized, and vulnerable populations. Dr. Janczewski received a Ph.D. in social welfare from the University of Wisconsin-Milwaukee and a master’s degree in social work from Virginia Commonwealth University.

Chapter 4

Racial Disproportionality and Disparities Among African American Children in the Child Welfare System Jessica Pryce and Anna Yelick

4.1

Introduction

The future for all of us will be determined, to a great extent, by our ability to take action and improve the outcomes for African American children.—Marian Wright-Edelman, founder of Children’s Defense Fund

The overrepresentation of children of color in our child welfare system has been a troubling and perplexing phenomenon. These disparities were captured by the current Kids Count data book (2019), which provides information about the child population in the United States. According to recent statistics, systemic racial inequities persist, which leads to poor outcomes for Black children, as well as other children of color, compared to their White peers. The public child welfare system is the overseer of child safety and wellbeing, so naturally when outcomes continue to be poor for certain subgroups, a re-examination of our system as well as the broader society, is warranted. There is a need for a deeper analysis of the root causes of the disparate outcomes for these children and families as well as advancements in research-informed interventions and strategies to combat these disparities. This chapter will discuss the impact of policies on Black families from a historical context as well as discuss the child welfare-specific policies that have contributed to disparity among Black children in the public child welfare system. This chapter will then outline current trends of both society as a whole and the public child welfare system and explore the negative outcomes among Black children. Finally, this chapter will outline strategies and tools that have been documented as impacting the disparity and disproportionality and discuss the future direction of research, policy, and practice.

J. Pryce (*) · A. Yelick Florida Institute for Child Welfare, Florida State University, Tallahassee, FL, USA e-mail: [email protected] © Springer Nature Switzerland AG 2021 A. J. Dettlaff (ed.), Racial Disproportionality and Disparities in the Child Welfare System, Child Maltreatment 11, https://doi.org/10.1007/978-3-030-54314-3_4

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The Impact of Policy on Black Families Historical Context

The influence of history on the current state of Black families is irrefutable. Past policies have given birth to an “underclass” of chronic and persistently impoverished Black families (Graff, 2014; Roberts, 2011), that have shaped the public perception of Black families. For example, after the abolishment of slavery through the 13th Amendment, several states adopted “The Black Codes,” which are laws that supported a system of White supremacy and laid the foundation for Jim Crow laws (Hansan, 2011). The Jim Crow Laws enforced a separate but equal manifesto that influenced the treatment and care of Black children, who were not permitted to be cared for by formal institutions (Roberts, 2002). This resulted in a dual track service delivery system that unfairly benefitted White families. There were a few colored orphanages; though many Black-only facilities under Jim Crow were generally inferior (Roberts, 2002), and Black children were more than likely cared for by extended family. The Jim Crow Laws not only put limitations on where orphaned Black children could be cared for, but also as a legal sanction, it set in motion a cycle of educational, economic, and social disadvantages for Black families (Graff, 2014). These disadvantages often start because of the poverty that Black families experience, which can contribute to significant physical and mental dangers (Bowman, n.d.). Poverty stifles opportunities for Black families such that even when these families move out of poverty, they still experience inequalities in housing, insurance, employment, and education (Bowman, n.d.). There are often unintended consequences of social policy. For example, Aid to Dependent Children (ADC) was born out of the Social Security Act of 1935 and it reinforced heteronormative ideals, promoting the two-parent household (Gordon, 1994; Kessler-Harris, 2001). This policy set up a morality clause, forcing poor single mothers who received assistance to conform to the White middle-class notion of motherhood (Nadasen, 2007). This included “suitable home” laws that denied aid to families who were considered morally corrupt, “substitute father” rules that denied aid to families if there was evidence of a man present in the home, and “employable mother” laws that denied assistance to women who were physically able to work (Abramovitz, 1989; Bell, 1965; Piven & Cloward, 1971). Between the 1950s and 1960s, the percentage of Black families receiving assistance grew from 31% to 48%, which resulted in public concern about the utilization of welfare (Nadasen, 2007). This increase was partly contributed to the increase in single motherhood by Black women, most of whom had never been married. Although historical research indicated that Black women had a higher rate of children out-of-wedlock, White women in similar situations typically had institutional support that protected them from public scrutiny. In fact, Black women had fewer avenues for adoption coupled with the Black community discouraging mothers from giving their children up for adoption (Kunzel, 1994; Solinger, 1994). Therefore, the higher rate of single

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motherhood among Black women along with higher poverty rates, contributed to more Black women receiving public assistance (Nadasen, 2007). This higher utilization of welfare, along with continued racism, contributed to a narrative surrounding welfare policy that depicts Black people, particularly black women, as undeserving of assistance. In the 1970s, the term “Welfare Queens” was used to describe Black single mothers as “scamming” the welfare system to live more luxuriously than the average White family (Nicholson, 2016). Another narrative is of the Black single mother with more children than she can handle, who is unemployed but uninterested in working, preferring to “live off the government” (Nadasen, 2007). Contributing to this mindset has been the historical use of worthy versus unworthy to describe who deserves help and who does not, which unsurprisingly has a basis in racism—White women are typically considered worthy and Black women are typically considered unworthy. These narratives/stereotypes have contributed to welfare reforms that limit the safety net of those utilizing these services, which led to the mantra “pull yourself up by your bootstraps.” It is important to understand that because of the historical racism that has contributed to inequity, Black people are disproportionately more likely to utilize welfare and less likely to have insulated supports—i.e., family to help them financially, highlevel of education, or multiple employment options (Alon & Haberfeld, 2007; Ciabattari, 2007; Pettit & Ewert, 2009). These individuals by historical design, have a harder time pulling themselves up by their bootstraps. The current child welfare system is influenced by the past discriminatory policies, not just in terms of reporting maltreatment and placing children in foster care but also related to diversity of foster parents and their eligibility and availability. This lack of diversity impacts thousands of children, who languish in foster care (Hill, 2007) and contribute to placement instability particularly among Black children. The next section explores child welfare policies and the impact on Black families.

4.2.2

Child Welfare Policies

Early settlers in the United States regarded children as essential to the economic function of the family, but often disregarded the needs of these children (McGowan, 2014). Though poverty was, and in many ways still is, considered a problem caused by the individual, the economy during these times relied heavily on the workforce. Therefore, child welfare was an act of “saving” children from inheriting the “bad habits” of their parents. This trend continued into the nineteenth century, with the utilization of orphanages (Rosenfeld et al., 1997). However, orphanages were not a great alternative and often could not accommodate the growing number of children in need of care (Cook, 1995). Shortly after, the first systematic placing program was initiated (Wheeler, 1983), asserting that children living in a family-like environment were better off than children raised in an orphanage (Cook, 1995). During the twentieth century, the need for a formal system became clear and a recognition of

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the state’s responsibility for dependent children evolved (McGowan, 2014). Eventually, Federal laws and mandates were enacted to guide child welfare work. One of the first major laws that tangentially introduced child protection as a need was the Social Security Act of 1935 (Adler, 2001; Schene, 1998), which highlighted the importance for children to feel safe (Wulczyn, 2004). This federal legislation gave way to the enactment of Aid to Dependent Children program and the Aid to Families with Dependent Children program, both of which offered cash assistance to financially unstable families (Schene, 1998). These programs were spearheaded in an effort to assist all women were single mothers, no matter how they got to that position. Moreover, these programs were designed to remove the stigma associated with utilizing public assistance as mother-headed families (Gordon & Batlan, 2011). These programs were thought to be used only until families gained increased financial stability and as more individuals used either of the programs, the less frequently the programs would be relied on, eventually leading to the abolishment of each program. However, a provision in the law, authorized ADC and AFDC assistance only to “suitable homes,” resulting in only 30 of the 79 of every 1000 children in need to receive assistance. Furthermore, these programs were especially problematic for Black families, who in the 1930s and 1940s, were still experiencing work-related and job-related discrimination, which impacted their earning potential and limited their ability to access these programs (Nicholson, 2016). Given that many children were denied benefits through the ADC and AFDC on the premise that their parents’ behavior was deemed immoral (Murray & Gesiriech, 2005), the Flemming Rule of 1960 was enacted to protect needy children from being removed from aid. The Temporary Assistance to Needy Families (TANF) block grant program in 1996 (Gordon, 2011) eventually replaced the ADC and AFDC. TANF offers time-limited benefits and has essentially forced single parents into the labor force. However, these jobs were often minimum-wage and insecure, limited benefits and resulted in families becoming poorer because they needed to secure childcare. Policymakers assumed by giving states the flexibility in how they provide financial assistance under TANF that this resource would be fairly distributed, but a result of this flexibility has been that states where Black families are more likely to utilize TANF still receive fewer benefits and assistance (Floyd, 2018). One example of this is that in states where Black families are likelier to live, TANF benefits are less likely to cover housing costs. Specifically, 48% of Black families live in states with TANF benefits that cover less than a third of housing costs compared to 30% of White families. Further, about 61% of Black people live in states that perform poorly on at least one TANF measure: (1) benefit levels at or below 20% of the poverty line; (2) a TANF-to-poverty ratio of 10 of less; or (3) spending 10% or less of TANF funds on basic assistance compared to 48% of White people (Floyd, 2018). These early policies focused on financial benefits for children and families, with the goal of minimizing neglect–related caes, but did little to address child physical or sexual abuse. The Child Abuse Prevention Treatment Act (CAPTA) of 1974 was enacted to provide common language across states regarding child abuse and defined child abuse as an act on the part of the guardian that results in harm (emotional, physical, or sexual) to the child (Public Law 93-247). CAPTA established federal

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funding sources for the services provided to maltreated children as well as required each state adopt specific procedures for reporting, investigating, and implementing services for maltreated children (Alvarez, Donohue, Kenny, Cavanagh, & Romero, 2005). However, there were unintended consequences of CAPTA, felt primarily by Black children and families. The child welfare system became more punitive without adequately addressing the cultural and diverse parenting strategies. Much like the ADC and AFDC, caseworkers would assess the homes of families with child maltreatment allegations from their own personal values and viewpoints. This was demonstrated in the qualitative research study from the Center for the Study of Social Policy’s Racial Equity Review out of Michigan’s child welfare system. In this study, Black parents were frequently described as hostile or angry, yet professionals failed to identify the context for these labels (see Roberts, 2012). Other literature also identified cultural differences between the caseworker and family, suggesting caseworkers viewed the parenting practices of Black mothers as harsher compared to the parenting practice of White mothers (Berger, McDaniel, & Paxon, 2006). Given that CAPTA led to an increase in the number of child maltreatment allegations, the number of children removed from their homes, the number of placement moves, and longer stays in foster care (Murray & Gesiriech, 2005), the Adoption Assistance and Child Welfare Act (AACWA) of 1980 was enacted (Pecora et al., 2010; Public Law 96-272). The AACWA established permanency requirements in an attempt to diminish the foster care “drift”—children moving from placement to placement without a sense of permanent home (Pecora et al., 2010). Strengthening permanency was also addressed through incentivizing adoption, specifically of children with special needs (Rollin, Vandervort, & Haralambie, 2005). Despite the efforts of the AACWA, the number of children placed in foster care began to rise in the mid-1980s, a nearly 76% increase. Researchers during this time pointed to multiple effects of the dramatic rise such as a decrease in economic stability, the War on Drugs, and higher rates of incarceration among women (Murray & Gesiriech, 2005), which all disproportionately affect Black families. Given the AACWA did not meet the intended expectations and the child welfare system was still failing its most vulnerable population, the Adoption and Safe Families Act of 1997 was enacted. This act reaffirmed the commitment to family preservation as a means of reducing the number of children placed in out-of-home care, requiring that agencies make a “reasonable effort” to maintain the family. This act established that the child’s health and safety is paramount; therefore, in situations where imminent harm is likely, the ASFA creates more opportunity for agencies to terminate the parent’s rights. Additionally, the ASFA allows states to establish “aggravated circumstance,” that render a parent ineligible for family preservation or family reunification services. The ASFA incentivized state agencies to place foster children in safe, permanent homes at a faster rate, and provided states with additional funding when this goal was achieved. The ASFA shifted the primary focus of the child welfare system from preventative and reunification services to termination of parental rights (Auzpitz, 2017), specifically to “clear a path” for adoption so children will not linger in the child welfare system. Despite these efforts, Black children continued to languish in the child welfare system longer compared to

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White children as the ASFA ignored the unique needs of children of color, promoting a “race-neutral” policy that disproportionately affected Black families (Boyd, 2015). Specifically, race continued to be a factor in the adoption of Black children within the child welfare system, with Black children less likely to be adopted compared to White children (Auzpitz, 2017). The Multiethnic Placement Act of 1994 (MEPA) was established to diminish the effects of racism in foster care and adoptive placement (Child Welfare Information Gateway, n.d.). The MEPA prohibited agencies from discriminating against families or children based on the family’s or child’s race or national origin when making decisions regarding foster care or adoption (P.L. 103-382, 1994). The MEPA also required agencies to develop plans for recruitment of ethnic and racially diverse foster and adoptive families that adequately represent the children receiving services within the agency. These provisions were incorporated to reduce the disproportionate number of Black children in the child welfare system throughout all points of transition (CWLA, 2007), an issue that had continued to grow, while overall numbers within the child welfare system declined. The Inter-Ethnic Adoption Provisions (IEAP) expanded and replaced MEPA, which further stipulated that race could not be used as a determinate factor in adoption and foster care placements (Auzpitz, 2017). The Child Welfare League of America (CWLA) found that despite the best efforts of MEPA, the number of Black children in the foster care system remained disproportionate, and Black children tended to remain in foster care approximately 12 months longer than White children. New legislation passed in 2018, the Family First Prevention Services Act (FFPSA), a bipartisan law attempting to reform the child welfare system by providing services to families at risk of entering out-of-home placement (NCSL, 2019). This new law highlights several attempts to reduce the number of children placed in foster care and residential care settings. The FFPSA encourages agencies to develop prevention services and programs, restrict the number of placements of children in out-of-home care, and make provisions to increase the support to kinship care families (NCSL, 2019). This policy makes provisions for states to better support families staying together, increase funding support for teens in foster care, and expand independent living services. One method of ensuring states are providing their child welfare population with the best services available, is ensuring all programs have evidence that is promising, supported, or well-supported (Rosenberg & McKlindon, 2019). At this point it is too early to know what benefits the FFPSA will have, specifically on Black children and their families. One method to combat systemic racism within the child welfare system, is to implement anti-racist policies that account for the unique needs of ethnically diverse children and families. A failure to fully encapsulate the multiple, intersecting discrimination that these families face will result in their increased involvement in the child welfare system (Boyd, 2015). For example, federal legislation that emphasizes permanency—permanent guardians, and adoption, could likely threaten the family preservation of Black families when a chance for reunification may have existed had these families been afforded more resources, preventive services, or options for relative care placement (Roberts, 2002).

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Current Trends

In 2017, there were more than 665,000 verified cases of child maltreatment (KIDSCount Data Center, 2019a), and of these confirmed cases, only 18% were identified as Black children (KIDSCount Data Center, 2019b). Of note, 23% of children currently in out-of-home care in 2016 were identified as Black, disproportionate to the percentage of confirmed cases of maltreatment AND disproportionate to the percentage of Black children (14%) in the United States in 2016 (KIDSCount Data Center, 2019c). These statistics support the literature suggesting Black children are more likely to be removed from their families, experience a longer stay in foster care, and wait for longer periods of time to reunify with their families (Hill, 2006; Lu et al., 2004; Putnam-Hornstein, Needell, King, & Johnson-Motoyama, 2013). Literature also suggests that race influences the types of services that families receive in the child welfare system (Lovato-Hermann, Dellor, Tam, Curry, & Freisthler, 2017). When compared to White children, Black children and families in the child welfare system experience lower access to services and higher rates of placement instability (Garcia, Kim, & DeNard, 2016), as well as less engagement with caseworkers (Cheng & Lo, 2012). While, the statistics suggest that Black children exit out-of-home placements (22%) at a similar rate that they enter out-ofhome placements (21%), it is likely these children experience more trauma while in out-of-home care due to placement instability, less family visitation and inadequate and culturally insensitive services. Additionally, 40% of Black children placed in out-of-home care experience more than two placement moves compared to 32% of White children (KIDSCount Data Center, 2018a) and the literature argues that placement instability can have calamitous effects on children (Rubin, O’Reilly, Luan, & Localio, 2007). Comparing the proportion of Black children who are adopted to the proportion of Black children waiting for adoption is telling. In 2016, only 17% of Black children were adopted compared to 49% of White children (KIDSCount Data Center, 2018b), compared to the 23% of Black children waiting for adoption and 44% of White children waiting for adoption (KIDSCount Data Center, 2018c). To better understand the prevalence of disproportionality among Black children, a racial disproportionality index (RDI) has been utilized (Kim, Chenot, & Ji, 2011). The RDI compares the percentage of children by race in the general population to those same groups within different aspects of the child welfare system. An RDI of 1.0 signifies that a group is represented proportionately to its numbers in the general population, though an RDI of 2.0 means that the group is twice the rate compared to the general population (Child Welfare Information Gateway, 2016a). In 2014, the RDI for Black children identified as victims of child maltreatment was 1.6, the highest RDI among all groups, with American Indian/Alaska Native coming in second at 1.5 (Child Welfare Information Gateway, 2016a). In comparison to White children (RDI of 0.9), who are identified as victims of child maltreatment at a lower rate compared to the general population is important to note. This trend, with Black children consistently having a higher RDI compared to the general population

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while White children have a lower RDI compared to the general population continues throughout different points of transition in the child welfare system. For example, the RDI of children entering foster care was 1.6 among Black children compared to 0.9 among White children and the RDI of children waiting to be adopted was 1.7 compared to 0.8 among White children (Child Welfare Information Gateway, 2016a). All of these statistics begin to paint a picture of the public child welfare system: there is inequity in the perception, decision making and treatment/services of Black families compared to White families. There are clear racial biases prevalent within the child welfare system, but these biases do not rest solely on the public child welfare system. In fact, researchers have pointed to larger systemic racial biases as contributors to the racial biases in the child welfare system (Bartholet, 2009; Dettlaff et al., 2011). Data collected from the National Incidence Study (NIS-4) report (2010) suggested there was a higher rate of preventable injury deaths among Black children and higher arrest rates among Black mothers compared to White mothers (Bartholet, Wulczyn, Barth, & Lederman, 2011). This is potentially a significant statement given that in 2017, 65% of Black children were reportedly living with a single parent compared to 24% of White Children (KIDSCount Data Center, 2019d). This is only one statistic that begins to demonstrate disparate outcomes throughout society for Black children and families. According to recent statistics, in 2017, nearly 33% of Black children live in families with incomes below the federal poverty level compared to 11% of White children (KIDSCount Data Center, 2018d). Additionally, 16% of Black children lived in extreme poverty—i.e., living in families with incomes less than 50% of the federal poverty level, compared to 5% of White children (KIDSCount Data Center, 2019e). The disproportionate number of Black children who experience poverty is indicative of a system that has yet to achieve equity. This is particularly salient given the risk factors associated with living in poverty, such as significantly elevated risks of maltreatment, homelessness (Barth, Wildfire, & Green, 2006), under- or unemployment, and increased utilization of welfare services (Courtney, Piliavin, Dworsky, & Zinn, 2001). In fact, in 2017, the statistics suggest that nearly 50% of Black children live in families that receive public assistance—supplemental security income, cash public assistance, or Food Stamps, compared to 16% of White children (KIDSCount Data Center, 2019f). These data suggest an alarming trend that Black children and families are less likely to stabilize because of the residual effects of a system that is inherently racist—i.e., the societal structures that systematically disadvantage families of color (Kleven, 2008). These disadvantages perpetuate an inequitable distribution of wealth and resources along racial lines, which is promoted by institutions. These factors intersect to create a “devastating nature of life circumstances for too many black families” (Bartholet et al., 2011, p. 4). Recent scholars have found that black children are more likely to receive an outof-home placement decision (Yelick & Thyer, 2020), and they have worse outcomes once in the system compared to White children (Fluke, Harden, Jenkins, & Ruehrdanz, 2010; Hill, 2006; Morton, Ocasio, & Simmel, 2011). The child welfare

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system acts as a punitive governance that continues to perpetuate social inequities among those most in need of a safety and provisions (Roberts, 2012). The following section provides a discussion of the explanatory factors that contribute to the disparity within the child welfare system.

4.4

Explanatory Factors

Scholars who study racial disparity generally caution readers about the relationship of race and outcomes being confounded by myriad other maladies (Courtney et al., 1996). There is a deeper issue that contributes to the overrepresentation of Black children in the child welfare system: Black families experience more discrimination at multiple levels compared to White families (Drake & Jonson-Reid, 2010). This intersectionality is a key component to understanding the factors that influence child maltreatment. Researchers suggest that individuals, and by proxy families, can experience multiple layers of discrimination, such as being a Black, poor, and single parent family (Murphy, Hunt, Zajicek, Norris, & Hamilton, 2009; Yelick & Thyer, 2020). Given disproportionality has been a focal point of child welfare leaders for years (Bartholet, 2009), with a considerable amount of effort expended in examining the racial disparities in the child welfare system, there have been a number of studies examining disproportionality and the factors that contribute to the overrepresentation of Black children in our system. Even though research suggests an abundance of explanatory factors, little research has uncovered causal links. While evidence supports the notion that intersectionality is a notable concern and that issues of poverty and need among Black children and families likely perpetuate their disparate outcomes within the child welfare system, understanding the impact of historical racism is still critical. In an article in 2006, Katznelson argued that major policies from the 1930s and 1940s excluded Black families, particularly in southern areas. For example, Black veterans were often unable to secure housing loans even after The GI Bill guaranteed loans for veterans. Katznelson (2006) argued further that policies designed to improve the outcomes of Black Americans, were often ingrained in a “white agenda” translating social power into disparate outcomes for Black families (Jones, 1997). Some policies, on the surface, appear egalitarian and fair, but ultimately and systematically disadvantage Black Americans due in part to the lack of contemporary resources available to these people because of their history of disadvantage (Dovidio, Mann, & Gaertner, 1989). Accepting that this history of oppression leads to a legacy of disparity (Henkel, Dovidio, & Gaertner, 2006), makes fighting disparity difficult but vital. The following is a discussion of some of the explanatory factors of disparity within the child welfare system, keeping in mind that historical racism has lead to a legacy of disparity that exists today.

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Socio-economic Factors

This legacy of disparity is often apparent in socio-economic factors, such as poverty, income, and neighborhoods. Research has shown a link at the state level between the racial disparities in poverty and racial disparities in maltreatment (Lanier, MaguireJack, Walsh, Drake, & Hubel, 2014; Maguire-Jack, Lanier, Johnson-Motoyama, Welch, & Dineen, 2015). Poverty has been a persistent factor among Black families, with a widening gap in economic security with Black Americans making less than two-thirds that of White Americans (Henkel et al., 2006). Socio-economic factors are especially salient when examining factors related to maltreatment. Economic disadvantage has been linked with socio-emotional adversity of children (Barnett, 2008) such as behavior problems, reduced social competence, lower-levels of selfregulation, and elevated stress (Berger, Paxon, & Waldfogel, 2009; Evans & English, 2002). Research has demonstrated a relationship between poverty disparity and maltreatment disparity within Black Families (Drake et al., 2011; Lanier et al., 2014), with higher income inequality predicting higher rates of maltreatment (Eckenrode et al., 2014; Maguire-Jack et al., 2015). Specifically, neglect is highly correlated with low-income and poverty (e.g., Gil, 1970; Waldfogel, 1998), such that children from low-income families are more likely to be reported to child welfare services as well as placed in out-of-home care compared to children from medium to high income families (Waldfogel, 2000). Poverty is a pervasive issue, influencing rates of maltreatment among disadvantaged groups such as teen parents, singleparents, parents experiencing unemployment, and parents receiving public assistance (Boyer & Halbrook, 2011; McPherson & Das, 2010). Child poverty has significant impacts on racial disparity in the child welfare system (Kim et al., 2011), particularly given poverty is a significant risk factor for child maltreatment that is often conflated with race (Kim et al., 2011). Dettlaff and colleagues noted that income diminishes the effects of race on substantiation and emerged as a stronger explanatory factor (Dettlaff et al., 2011), suggesting a larger systemic issue: Black families have more risk factors associated with maltreatment, such as increased poverty rates, substance use issues, and higher rates of singleparent families compared to White children (Bartholet, 2009). Further, these risk factors have often persisted throughout history, culminating in a reality among Black families that is steeped in historical racism. Describing the differential effects of the salient factors related to maltreatment will likely aid child welfare professionals in correctly assessing the safety and well-being of children without exposing these families to undue harm (Boyer & Halbrook, 2011).

4.4.2

Implicit Bias

While it is important to note that the disproportionate needs and poverty within Black families are largely the result of structural racism, there are other factors that

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contribute to the racial disproportionality and disparity in the child welfare system. In the third edition of Black Families, Black parents reported feeling more concerned about the hidden and implicit racism, than the overt racism during legalized segregation (Tatum, 1992). Research suggests that implicit bias could be influencing decisions within child welfare. A study done in Texas found that even though Black families showed lower risk on assessments, they were still more likely to have their cases substantiated and to have their children removed (Dettlaff et al., 2011; Rivaux et al., 2008). This could be indicative of a systemic issue among child welfare professionals, who often hold Black parents to a different standard of parenting than White parents (Berger et al., 2006). Institutional racism are often hard to detect because they are imbedded in a society that is easy to ignore among White people and dismissed as a moral failing on the individual rather than a larger systematic issue. For example, Black Americans receive unequal treatment from medical professionals resulting in unfavorable outcomes and typically live in residentially segregated neighborhoods even after the push for more integration (Henkel et al., 2006). Institutional racism contributes to implicit biases and discrimination, manifesting unconsciously, which can be particularly problematic when people are more vigilant towards overt examples of racism. This subconscious discrimination among people making case decisions (e.g. caseworkers, mandated reporters, community members), along with lack of cultural sensitivity training, has further perpetuated the disproportionality at each stage (i.e. reporting, investigation, substantiation, placement, and exits) in the child welfare system (Boyd, 2015; Fluke et al., 2010; Pryce et al., 2018).

4.4.3

Visibility and Exposure Bias

Advocates of racial equity in child welfare understand that racism is not simply a matter of personal prejudice and hate but a multifaceted problem that is prevalent within and across systems. For example, a family who is receiving services and utilizing support from our system and across other systems invariably have more visibility than most families. Some researchers argue that increased access and availability to social services reduces maltreatment (Freisthler, 2013; Maguire-Jack & Klein, 2015); however, Black families are less likely to receive services for mental health issues (Broman, 2012; SAMHSA, 2013) and often live in areas with fewer resources available (Hipp & Yates, 2011). Communities that experience poverty lack access to quality services that can be utilized to proactively address any concerns within the family, which can lead to increased risk for child maltreatment (Maguire-Jack, Cao, & Yoon, 2018). Poverty, then, increase the amount of visibility and exposure (Roberts, 2008) these families experience with reactive social services such as financial housing assistance and food and cash assistance potentially increasing the scrutiny of these families among social service agency workers (Child Welfare Information Gateway, 2016a).

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Additionally, it has been posited that the child welfare system acts as a method of surveillance and policing of Black families rather than addressing racism and the societal roots of the problem (Roberts, 2002, 2014). Scholars also argue that racism is embedded in the structure of society and institutions, unjustly impacting the child welfare laws and systems that reinforce the unequal treatment of black families (Denby & Curtis, 2013; Dixon, 2008; Roberts, 2002).

4.4.4

Geographic Context

There is evidence to support that the geographic context plays an important role in the understanding of disparity and disproportionality and the identification of promising practices and strategies. For example, at the national level, Hispanic children are slightly underrepresented in out-of-home care (21%), but overrepresented in some states (Child Welfare Information Gateway, 2016a). There are differences among Black children, particularly in urban and rural counties. Further, research suggests that children living in racially diverse neighborhoods are more likely to be reported to child protective services compared to children living in homogenous neighborhoods (Klein & Merritt, 2014). Research has pointed to the importance of geographical factors and racial disparity in the child welfare system (e.g., Font et al., 2012), suggesting that focusing solely on race and culture will do little to change the disparity that exists in the child welfare system. Research suggests that the impact of child welfare is felt more intensely in innercity neighborhoods (Roberts, 2012). A high number of child protection cases occur in low-income Black communities and most Black families live in neighborhoods that have high rates of child welfare involvement (Roberts, 2008). The reality is that Black children and families often expect child welfare involvement as a normative life experience. The disproportionate representation of Black children in the child welfare system may be attributed to the disproportional residence of Black families in high poverty geographical areas (Maguire-Jack et al., 2015). There are geographical differences in service accessibility and availability (Slovak & Carlson, 2009), which could have an impact on child welfare. Specifically, the association between poverty and substance-use factors and child maltreatment coupled with the lack of services and social support could influence the involvement of the child welfare system (MaguireJack et al., 2015). Communities with limited resources, particularly those communities that have a high concentration of Black families, have limited access to basic needs, mental health providers, and secure employment options (Allard, 2009). Examining a wide range of factors is critical to begin to reduce racial disparity within the child welfare system. In particular, the geographic contexts, sociodemographic, and case characteristics are crucial elements that contribute to a widening gap in outcomes for Black and White children (Font et al., 2012). This highlights a need to utilize regional data as well as national data when examining these issues (Child Welfare Information Gateway, 2016a).

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Disproportionate Needs of Black Families

The disproportionate needs of Black children is a considerable factor in the discussion of disparity in the child welfare system. Black children often experience certain family situations and socioeconomic challenges (e.g. poverty, unemployment, homelessness, parental incarceration, mental illness, substance abuse, domestic violence, and limited access to community resources) that increases their visibility to social service professionals, as well as, increases risks for some forms of child maltreatment (Boyd, 2015; Fluke et al., 2010). With the broad understanding that neglect as a maltreatment comprises much of our child abuse reports (Child Welfare Information Gateway, 2016a); the persistence of poverty in Black families is a factor worth scrutiny and investment. The strong correlation between race and income often bring challenges to interpretation (Courtney et al., 1996). Many scholars contend that income/poverty is the prominent precipitator of the disparity and disproportionality (Drake et al., 2011; Maguire-Jack et al., 2015), and research has found that poverty and material need increase the likelihood that Black children enter the child welfare system (Drake, Lee, & Jonson-Reid, 2008). Though, there continues to be no research that confirms a relationship between race and the incidence of child maltreatment (Sedlak & Broadhurst, 1996). This indicates there is no evidence that Black parents willfully abuse their children more than others. In fact, some evidence supports that the issue could be cultural, with White child welfare workers holding Black mothers to different standards of parenting than White mothers (Berger et al., 2006). Further, evidence suggests given the intersectionality of Black families’ experience, the attitudes of those who engage with these families can be conflated, meaning because these workers meet with families in certain neighborhoods or with certain characteristics, they could more likely to perceive that family heuristically rather than examining the family objectively (Crea, 2010).

4.5 4.5.1

Promising Practices/Strategies Prevention and Early Intervention

Working proactively with other agencies on prevention measures can decrease the numbers of all children entering our system (Prinz, 2016). In particular, Home Visiting Programs (Lee, Kirkland, Miranda-Julian, & Greene, 2018), partners with families to enhance their capacity with support services (Lee et al., 2018). As a preventive measure, home visiting services have been documented as an important strategy to address the disproportionality of black children in our system (Kitzman, Olds, & Cole, 2010; Olds et al., 2014). A randomized control study of low-income Black mothers who were visited by a nurse for the first 2 years of the child’s life resulted in several positive outcomes compared to mothers who did not receive the home visits (Kitzman et al., 2010; Olds et al., 2014). This finding is not surprising to child welfare professionals or even families; it has been known for a long time that

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early prevention, particularly in-home/home-visiting support, has pulled thousands of families out of the snares of poverty and isolation relating to caring for young children (Lee et al., 2018). Therefore, targeted prevention services for Black families could very likely impact their overrepresentation. Specifically, support services that address poverty, housing and employment, and childcare (Child Welfare Information Gateway, 2016a).

4.5.2

Reporting

Black families are overrepresented at multiple decision-making points within our system and the main one, possibly the most important one, is the “front door”; the reporting of maltreatment to abuse registries and hotlines (Krase, 2013). Families come into the knowledge of child protection by a reporting system, therefore; it is imperative that we try to ensure those reports are not influenced by racial or ethnic bias (Child Welfare Information Gateway, 2016b). Research has already shown that Black families are more likely to be reported for abuse and neglect (Cappelleri, Eckenrode, & Powers, 1993). Laws about mandated reporting could benefit from revision. Ethical principles are in constant opposition when negotiating rights of children and the rights of parents (Feng, Chen, Fetzer, Feng, & Lin, 2012). Several professions are mandated by law to report their suspicions of child abuse and neglect; some include social workers, teachers, childcare providers, and law enforcement officers (Child Welfare Information Gateway, 2016b). These professionals are required to report facts about why they suspect abuse; though they do not have the burden of providing proof that the abuse has actually occurred (Child Welfare Information Gateway, 2016b). Feng et al. (2012) writes that achieving justice in the reporting stage of child protection is difficult. The role of reporting invariably infringes on child and parent autonomy. Additionally, surveillance bias may lead to the increased, systematic scrutiny of Black families compared to White families (Chaffin & Bard, 2006). The surveillance bias leads to the “at-risk” group (Black-families) being over-scrutinized for risk of maltreatment, which leads to a higher likelihood of having a maltreatment report accepted and substantiated (Chaffin & Bard, 2006).

4.5.3

Investigation and Assessment

Research has shown that Black families are more likely to have their cases investigated as opposed to being offered supportive services (Putnam-Hornstein et al., 2013); and they are more likely to have their cases substantiated when compared to White families (Fluke, Yuan, Hedderson, & Curtis, 2003; Hill, 2007; Krase, 2013). In addition to whether a family is relegated to a full and intrusive investigation, research has also shown that caseworkers have different perceptions of risk level

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depending on a child’s race (Dettlaff et al., 2011; Child Welfare Information Gateway, 2016b). Structured Decision-Making models (SDM) were created with the goal of decreasing subjectivity and potential bias (Crea, 2010). One of the main purposes of SDMs is to reduce the number of repeated maltreatment incidences experienced by a family (Gambrill & Shlonsky, 2000; Johnson, 2006). Different factors contribute to the decision-making process, which influence the outcomes for that decision (Baumann, Dalgleish, Fluke, & Kern, 2011) and SDMs are useful in ameliorating the decision-maker factors, such as inexperience of the decision-maker or personal biases, providing standards for consistent decision-making (Lindley, 1985). In this regard, SDMs provide child welfare professionals with a standard instrument to make consistent decisions regarding the assessment of child maltreatment (Wells & Correia, 2012); though some research has found no difference relating to disproportionality while utilizing SDM tools (Miller, 2011; Osterling, D’Andrade, & Austin, 2008). It’s also important to note that the tools are rarely tested on non-White groups (Child Welfare Information Gateway, 2016a); therefore, it is difficult to rule out biases.

4.5.4

Blind Removal Meetings

This strategy has been piloted in a community in New York. In an effort to control for bias in decision making, this community implemented Blind Removals Meetings (Pryce et al., 2018). Blind removal meetings consist of a committee of child welfare professionals convening to determine if a child(ren) will be removed from their family home, without know the race or other demographics of the family. The case worker, who has already seen the family and conducted an initial assessment of risk, presents the facts of the case but never mentions demographics or neighborhood. All identifiable information on the case file is removed and the discussion focuses on what has occurred, relevant history, and family capacity and strength. After the presentation of the case, the committee makes a recommendation regarding whether the children should be removed from the family and placed in foster care. Tracking this process over 5 years rendered pretty staggering results. The rates started at 55.5% of black children being removed from their homes, and it went down to 29% (Pryce et al. 2018). This approach confirms an uncomfortable reality that biases are playing a role in decision making and this impact is also prevalent in other systems. This approach has been piloted in the criminal justice system (Williams, 2019) where black people are arrested and charged at higher rates than other races (Lyons, Lurigio, Roque, & Rodriguez, 2013). A pilot implemented in San Francisco became curious about decisions if prosecutors did not know the race of the offender (Williams, 2019). This blind removal approach has produced initial positive results and could be a viable strategy for other agencies.

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Future Directions

Future progress on issues of disproportionality has to be multifaceted and tailored to subgroups based on their levels of vulnerability and overrepresentation. Future steps should be multi-pronged so that there is change on the legislative level as well as organizational capacity (training) and research.

4.6.1

Legislative Intervention

Some states have begun to address disparity and disproportionality through legislation. The National Conference of State Legislatures created a report of the state legislative initiatives to address the question of “whether the nation’s child welfare system undermines the strength of families, particularly families of color.” State initiatives to address and diminish disparate outcomes in child welfare are continuously being developed and tested. One new legislative act out of Minnesota, the Minnesota African American Family Preservation Act [MAAFPA], is a “racespecific law” that seeks to keep children with their own family, unless there have been exhaustive efforts to no avail. These types of laws are steeped in Black historical context, as these communities have historically created alliances and councils (Black Panther, NAACP, etc.) to keep a watchful eye over the systemic racism that affects Black families. Enacting state and federal policies that address inequity is critical and has potential for broad and consistent momentum.

4.6.2

Training

Training is not the panacea for addressing racial disparity and disproportionality but it is a viable tool towards equipping our workforce to make better and more informed decisions. Vinokur-Kaplan and Hartman (1986) found that 78% of frontline workers and 80% of supervisors had not received any training or coaching on provision of services for African American Families. Not much has changed in the last 20 years; though there have been studies completed on the impact of anti-racist training within child welfare (Johnson, Antle, & Barbee, 2009), finding that there was satisfaction among the training participants, as well as, an increase in their knowledge and selfawareness. Researchers and practitioners maintain that increased cultural awareness and sensitivity will serve to address the issue of disproportionality by dealing directly with workers’ racial attitudes and biases (Chibnall et al., 2003; Kokaliari, Roy, & Taylor, 2019).

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Research

Although there is a scarcity of research that has isolated race when analyzing outcomes relating to child welfare involvement, there have been some notable contributions to the literature regarding the complexity of disproportionality and disparity. Continuing to build on the strategies and promising practices that are being implemented is critical. Researchers suggest that efforts to address racial disproportionality need to extend beyond cultural competence training and beyond the recruitment of a diverse workforce, as these have not reduced the racial disparity within the child welfare system (Font et al., 2012). Going forward, rigorous research should be focused on the other factors, some of which have stronger explanatory evidence for the disparity including reducing income inequities and poverty among Black families (Dettlaff et al., 2011); geographical contexts (Font et al., 2012); disparity in risk factors associated with maltreatment (Maguire-Jack et al., 2015); and the intersecting factors that contribute to higher risks for maltreatment (Murphy et al., 2009; Yelick & Thyer, 2020).

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Berger, L. M., McDaniel, M., & Paxon, C. (2006). How does race influence judgments about parenting. Focus, 24, 24–30. Berger, L. M., Paxon, C., & Waldfogel, J. (2009). Income and child development. Children and Youth Services Review, 31, 978–989. https://doi.org/10.1016/j.childyouth.2009.04.013. Bowman, B. T. (n.d.). The state of the Black child. In National Black Child Development Institute, Being Black is not a risk factor: A strengths-based look at the state of the Black child. Retrieved from https://www.nbcdi.org/sites/default/files/resource-files/Being%20Black%20Is%20Not% 20a%20Risk%20Factor_0.pdf Boyd, R. (2015). A conceptual framework for African American disproportionality and disparity in child welfare. Retrieved from http://cascw.umn.edu/portfolio_tags/cw360/ Boyer, B. A., & Halbrook, A. E. (2011). Advocating for children in care in a climate of economic recession: The relationship between poverty and child maltreatment. Northwestern Journal of Law and Social Policy, 6, 300–317. Broman, C. (2012). Race differences in the receipt of mental health services among young adults. Psychological Services, 9, 38–48. https://doi.org/10.1037/a0027089. Cappelleri, J. C., Eckenrode, J., & Powers, J. L. (1993). The epidemiology of child abuse: Findings from the second national incidence and prevalence study of child abuse and neglect. American Journal of Public Health, 83, 1622–1624. Chaffin, M., & Bard, D. (2006). Impact of intervention surveillance bias on analyses of child welfare report outcomes. Child Maltreatment, 11, 301–312. https://doi.org/10.1177/ 1077559506291261. Cheng, T. C., & Lo, C. C. (2012). Racial disparities in access to needed child welfare services and worker-client engagement. Children and Youth Services Review, 34(9), 1624–1632. Chibnall, D., Dutch, N. M., Jones-Harden, B., Brown, A., Gourdine, R., Smith, J., et al. (2003). Children of color in the child welfare system: Perspectives from the child welfarecommunity. U.S. Department of Health and Human Services. Child Welfare Information Gateway. (2016a). Racial Disproportionality and Disparity in Child Welfare. Retrieved from https://www.childwelfare.gov/pubpdfs/racial_disproportionality.pdf. Child Welfare Information Gateway. (2016b). Mandatory reporters of child abuse and neglect. Washington, DC: U.S. Department of Health and Human Services, Children’s Bureau. Child Welfare Information Gateway. (n.d.). Major federal legislation index and search: Multiethnic Placement Act of 1994. Retrieved from https://www.childwelfare.gov/topics/systemwide/lawspolicies/federal/search/?CWIGFunctionsaction¼federallegislation:main.getFedLedgDetail& id¼46 Child Welfare League of America. (2007). Child welfare standards of excellence. Arlington, VA: Author. Ciabattari, T. (2007). Single mothers, social capital, and work-family conflict. Journal of Family Issues, 28, 34–60. Cook, J. F. (1995). A history of placing-out: The orphan trains. Child Welfare, 74, 181–197. Courtney, M. E., Barth, R. P., Berrick, J. D., Brooks, D., Needell, B., & Park, L. (1996). Race and child welfare services: Past research and future directions. Child Welfare, 75(2), 99–137. Retrieved from http://search.ebscohost.com/login.aspx?direct¼true&db¼rzh& AN¼107040911&site¼ehost-live Courtney, M., Piliavin, I., Dworsky, A., & Zinn, A. (2001). Involvement of TANF families with child welfare services. Paper presented at annual meeting of the Association for Public Policy Analysis and Management, Washington, DC. Crea, T. M. (2010). Balanced decision making in child welfare: Structured processes informed by multiple perspectives. Administration in Social Work, 34, 196–212. https://doi.org/10.1080/ 03643101003609529. Denby, R. W., & Curtis, C. M. (2013). African American children and families in child welfare: Cultural adaptation of services. New York: Columbia University Press.

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Graff, G. (2014). The intergenerational trauma of slavery and its aftermath. Journal of PsychoHistory, 41(3), 181–197. Retrieved from http://search.ebscohost.com/login.aspx?direct¼true& db¼a9h&AN¼93482520&site¼ehost-live Hansan, J. E. (2011). Jim Crow laws and racial segregation. Social Welfare History Project. Retrieved from http://socialwelfare.library.vcu.edu/eras/civil-war-reconstruction/jim-crowlaws-andracial-segregation/ Henkel, K. E., Dovidio, J. F., & Gaertner, S. L. (2006). Institutional discrimination, individual racism, and Hurricane Katrina. Analyses of Social Issues and Public Policy, 6, 99–124. Hill, R. B. (2006). Synthesis of research on disproportionality in child welfare: An update. Washington, DC: Casey-CSSP Alliance for Racial Equity in the Child Welfare System. Hill, R. B. (2007). An analysis of racial/ethnic disproportionality and disparity at the national, state and county levels. Seattle, WA: Casey Family Programs. Hipp, J. R., & Yates, D. K. (2011). Ghettos, thresholds, and crime: Does poverty really have an accelerating increasing effect on crime? Criminology, 49(4), 955–990. Johnson, W. (2006). The risk assessment wars: A commentary: Response to “Evaluating the effectiveness of actuarial risk assessment models” by D. Baumann, J. R. Law, J. Sheets, G. Reid, & J. C. Graham, Children and Youth Services Review, 27, pp. 465–490. Children and Youth Services Review, 28, 704–714. Johnson, L. M., Antle, B. F., & Barbee, A. P. (2009). Addressing disproportionality and disparity in child welfare: Evaluation of an anti-racism training for community service providers. Children and Youth Services Review, 31, 688–696. https://doi.org/10.1016/j.childyouth.2009.01.004. Jones, J. M. (1997). Prejudice and racism (2nd ed.). New York: McGraw-Hill. Katznelson, I. (2006). When affirmative action was white. Poverty & Race Research Action Council, 15, 1–16. Kessler-Harris, A. (2001). In pursuit of equity: Women, men, and the quest for economic citizenship in 20th-century America. New York, NY: Oxford University Press. KIDSCount Data Center. (2018a). Children in foster care with more than two placements by race and Hispanic origin in the United States. Retrieved from https://datacenter.kidscount.org/data/ tables/8823-children-in-foster-care-with-more-than-two-placements-by-race-and-hispanic-ori gin?loc¼1&loct¼1#detailed/1/any/false/870,573,869,36,868,867,133,38,35,18/ 2638,2601,2600,2598,2603,2597,2602,1353/17682,17683 KIDSCount Data Center. (2018b). Children in child welfare system who have been adopted by race and Hispanic origin in the United States. Retrieved from https://datacenter.kidscount.org/data/ tables/6677-children-in-child-welfare-system-who-have-been-adopted-by-race-and-hispanicorigin?loc¼1&loct¼1#detailed/1/any/false/870,573,869,36,868,867,133,38,35,18/ 2638,2601,2600,2598,2603,2597,2602,1353/13730,13731 KIDSCount Data Center. (2018c). Children in foster care waiting for adoption by race and Hispanic origin in the United States. Retrieved from https://datacenter.kidscount.org/data/ tables/6674-children-in-foster-care-waiting-for-adoption-by-race-and-hispanic-origin?loc¼1& l o c t ¼1 # d e t a i l e d / 1 / a n y / f a l s e / 8 7 0 , 5 7 3 , 8 6 9 , 3 6 , 8 6 8 , 8 6 7 , 1 3 3 , 3 8 , 3 5 , 1 8 / 2638,2601,2600,2598,2603,2597,2602,1353/13723,13724 KIDSCount Data Center. (2018d). Children in poverty by race and ethnicity in the United States. Retrieved from https://datacenter.kidscount.org/data/tables/44-children-in-poverty-by-raceand-ethnicity?loc¼1&loct¼1#detailed/1/any/false/871,870,573,869,36,868,867,133,38,35/ 10,11,9,12,1,185,13/324,323 KIDSCount Data Center. (2019a). Children in foster care in the United States. Retrieved from https://datacenter.kidscount.org/data/tables/6243-children-in-foster-care?loc¼1& loct¼1#detailed/1/any/false/871,870,573,869,36,868,867,133,38,35/any/12987 KIDSCount Data Center. (2019b). Children who are confirmed by child protective services as victims of maltreatment by race and Hispanic origin in the United States. Retrieved from https:// datacenter.kidscount.org/data/tables/9909-children-who-are-confirmed-by-child-protective-ser vices-as-victims-of-maltreatment-by-race-and-hispanic-origin?loc¼1&loct¼1#detailed/1/any/ false/871,870,573/2638,2601,2600,2598,2603,2597,2602,1353/19244,19245

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KIDSCount Data Center. (2019c). Child population by race in the United States. Retrieved from https://datacenter.kidscount.org/data/tables/103-child-population-by-race?loc¼1& loct¼1#detailed/1/any/false/37,871,870,573,869,36,868,867,133,38/68,69,67,12,70,66,71,72/ 423,424 KIDSCount Data Center. (2019d). Children in single-parent families by race in the United States. Retrieved from https://datacenter.kidscount.org/data/tables/107-children-in-single-parent-fami lies-by-race?loc¼1&loct¼1#detailed/1/any/false/871,870,573,869,36,868,867,133,38,35/ 10,11,9,12,1,185,13/432,431 KIDSCount Data Center. (2019e). Children in extreme poverty (50 percent poverty) by race and ethnicity in the United States. Retrieved from https://datacenter.kidscount.org/data/tables/8783children-in-extreme-poverty-50-percent-poverty-by-race-and-ethnicity?loc¼1&l o c t ¼1 # d e t a i l e d / 1/ a n y/f a l s e / 8 71 , 8 70 , 57 3 , 86 9 , 36 , 1 33 , 3 5,1 6/ 4038,4040,4039,2638,2597,4758,1353/17619,17620. KIDSCount Data Center. (2019f). Children in families that receive public assistance by race and ethnicity in the United States. Retrieved from https://datacenter.kidscount.org/data/tables/9789 children-in-families-that-receive-public-assistance-by-race-and-ethnicity?loc¼1& l o c t ¼1 # d etailed/1/any/false/871,870,573,869,36,133,35,16/ 4038,4040,4039,2638,2597,4758,1353/19062,19063. Kim, H., Chenot, D., & Ji, J. (2011). Racial/ethnic disparity in child welfare systems: A longitudinal study utilizing the disparity index (DI). Children and Youth Services Review, 33(7), 1234–1244. https://doi.org/10.1016/j.childyouth.2011.02.021. Kitzman, H. J., Olds, D. L., & Cole, R. E. (2010). Enduring effects of prenatal and infancy home visiting by nurses on children: Follow-up of a randomized trial among children at age 12 years. Arch Pediatric Adolescent Medicine, 164(5), 412–418. Klein, S., & Merritt, D. (2014). Neighborhood racial & ethnic diversity as a predictor of child welfare system involvement. Children and Youth Services Review, 41, 95–105. https://doi.org/ 10.1016/j.childyouth.2014.03.009. Kleven, T. (2008). Systemic classism: Systemic racism: Are social and racial justice achievable in the United States. Connecticut Public Interest Law Journal, 8(2), 37–84. Kokaliari, E. D., Roy, A. W., & Taylor, J. (2019). African American perspectives on racial disparities in child removals. Child Abuse & Neglect, 90, 139–148. https://doi.org/10.1016/j. chiabu.2018.12.023. Krase, K. S. (2013). Differences in racially disproportionate reporting of child maltreatment across report sources. Journal of Public Child Welfare, 7(4), 351–369. Kunzel, R. (1994). White neurosis, Black pathology: Constructing out-of-wedlick pregnancy in the wartime and post-war U.S. In J. Meyerowitz (Ed.), Not June Cleaver: Women and gender in postwar America (pp. 304–331). Philadelphia: Temple University Press. Lanier, P., Maguire-Jack, K., Walsh, T., Drake, B., & Hubel, G. (2014). Race and ethnic differences in early childhood maltreatment in the United States. Journal of Developmental and Behavioral Pediatrics, 35, 419–426. https://doi.org/10.1097/DBP.0000000000000083. Lee, E., Kirkland, K., Miranda-Julian, C., & Greene, R. (2018). Reducing maltreatment recurrence through home visitation: A promising intervention for child welfare involved families. Child Abuse & Neglect, 86, 55–66. https://doi.org/10.1016/j.chiabu.2018.09.004. Lindley, D. V. (1985). Making decisions (2nd ed.). New York: Wiley. Lovato-Hermann, K., Dellor, E., Tam, C. C., Curry, S., & Freisthler, B. (2017). Racial disparities in service referrals for families in the child welfare system. Journal of Public Child Welfare, 11(2), 133–149. Lu, Y. E., Landsverk, J., Ellis-Macleod, E., Newton, R., Ganger, W., & Johnson, I. (2004). Race, ethnicity, and case outcomes in child protective services. Children and Youth Services Review, 26, 447–461. Lyons, T., Lurigio, A. J., Roque, L., & Rodriguez, P. (2013). Racial disproportionality in the criminal justice system for drug offenses: A state legislative response to the problem. Race and Justice, 3(1), 83–101.

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Maguire-Jack, K., Cao, Y., & Yoon, S. (2018). Racial disparities in child maltreatment: The role of social service availability. Children and Youth Services Review, 86, 49–55. Maguire-Jack, K., & Klein, S. (2015). Parenting and proximity to social services: Lessons from Los Angeles County in the community context of child neglect. Child Abuse & Neglect, 45, 35–45. https://doi.org/10.1016/j.chiabu.2015.04.020. Maguire-Jack, K., Lanier, P., Johnson-Motoyama, M., Welch, H., & Dineen, M. (2015). Geo-graphic variation in racial disparities in child maltreatment: The influence of county poverty and population. Child Abuse and Neglect, 47, 1–13. McGowan, B. G. (2014). Historical evolution of child welfare services. In G. P. Mallon & P. M. Hess (Eds.), Child welfare for the twenty-first century: A handbook of practices, policies, & programs (pp. 11–46). New York: Columbia University Press. Miller, M. (2011). Structured Decision Making risk assessment: Does it reduce racial disproportionality in Washington’s child welfare system? Olympia: Washington State Institute for Public Policy, Document Number 11-05-3901. Retrieved from http://www.wsipp.wa.gov/ ReportFile/1086/Wsipp_Structured-Decision-Maki. Morton, C. M., Ocasio, K., & Simmel, C. (2011). A critique of methods used to describe the overrepresentation of African Americans in the child welfare system. Children and Youth Services Review, 33, 1538–1542. https://doi.org/10.1016/j.childyouth.2011.03.018. Murphy, Y., Hunt, V., Zajicek, A. M., Norris, A. N., & Hamilton, L. (2009). Incorporating intersectionality in social work practice, research, policy, and education. Washington, DC: NASW Press. Murray, K. O., & Gesiriech, S. (2005). A brief legislative history of the child welfare system. Retrieved from http://pewfostercare.org/research/docs/Legislative.pdf Nadasen, P. (2007). From widow to “welfare queen”: Welfare and the politics of race. Black Women, Gender + Families, 1(2), 52–77. National Conference of State Legislatures. (2019). Family First Prevention Services Act. Retrieved from http://www.ncsl.org/research/human-services/family-first-prevention-services-act-ffpsa. aspx Nicholson, L. (2016). How racism has shaped welfare policy in American since 1935. Retrieved from https://theconversation.com/how-racism-has-shaped-welfare-policy-in-america-since1935-63574 Olds, D. L., Kitzman, H., Knudtson, M. D., Anson, E., Smith, J. A., & Cole, R. (2014). Effect of home visiting by nurses on maternal and child mortality: Results of a two-decade follow-up of a randomized, clinical trial. JAMA Pediatrics, 168, 800–806. https://doi.org/10.1001/ jamapediatrics.2014.472. Osterling, K. L., D’Andrade, A., & Austin, M. J. (2008). Understanding and addressing racial/ ethnic disproportionality in the front end of the child welfare system. Journal of Evidence-Based Social Work, 5(1/2), 9. Retrieved from http://search.ebscohost.com/login.aspx?direct¼true& db¼edb&AN¼31658127&site¼eds-live&scope¼site Pecora, P. J., Whittaker, J. K., Maluccio, A. N., Barth, R. P., Depanfilis, D., & Plotnick, R. D. (2010). The child welfare challenge: Policy, practice, and research (3rd ed.). New Brunswick, NJ: Transaction Publishers. Pettit, B., & Ewert, S. (2009). Employment gains and wage declines: The erosion of Black women’s relative wages since 1980. Demography, 46, 469–492. Piven, F. F., & Cloward, R. (1971). Regulating the poor: The functions of public welfare. New York: Pantheon Books. Prinz, R. J. (2016). Parenting and family support within a broad child abuse prevention strategy: Child maltreatment prevention can benefit from public health strategies. Child Abuse & Neglect, 51, 400–406. https://doi.org/10.1016/j.chiabu.2015.10.015. Pryce, J., Lee, W., Crowe, E., Park, D., McCarthy, M., & Owens, G. (2018). A case study in public child welfare: County-level practices that address racial disparity in foster care placement. Journal of Public Child Welfare, (1), 35. Retrieved from http://search.ebscohost.com.proxy.

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Public Law 103-382. (1994). H.R.6 – Improving America’s Schools act of 1994. Retrieved from https://www.congress.gov/bill/103rd-congress/house-bill/6?q¼%7B%22search%22%3A%5B %22PL103-382%22%5D%7D&r¼1 Public Law 93-247. (1974). Child abuse prevention and treatment act. Retrieved from http:// uscode.house.gov/statutes/pl/93/247.pdf Public Law 96-272. (1980). Adoption assistance and child welfare act. Retrieved from http:// uscode.house.gov/statutes/pl/96/272.pdf Putnam-Hornstein, E., Needell, B., King, B., & Johnson-Motoyama, M. (2013). Racial and ethnic disparities: A population-based examination of risk factors for involvement with child protective services. Child Abuse and Neglect, 37(1), 33–46. Rivaux, S. L., James, J., Wittenstrom, K., Baumann, D., Sheets, J., Henry, J., et al. (2008). The intersection of race, poverty and risk: Understanding the decision to provide services to clients and to remove children. Child Welfare, 87(2), 151–168. Roberts, D. (2002). Shattered bonds: The color of child welfare. Children and Youth Services Review, 24, 877–880. Roberts, D. E. (2008). The racial geography of child welfare: Toward a new research paradigm. Child Welfare, 87(2), 125–150. Rosenberg, R., & McKlindon, A. (2019). The Family First Prevention Services Act can fund needed services and supports for older youth in foster care. Child Trends. Retrieved from. https://www. childtrends.org/blog/the-family-first-prevention-services-act-fund-needed-servicessupportsolder-youth-foster-care. Roberts, D. (2011). Prison, foster care, and the systemic punishment of black mothers symposium: Over policed and under protected: Women, race, and criminalization: I. Establishing the framework. Roberts, D. E. (2012). Prison, foster care, and the systemic punishment of Black mothers. 59 UCLA Law Review, 59, 1474–1500. Roberts, D. E. (2014). Child protection as surveillance of African American families. Journal of Social Welfare & Family Law, 36(4), 426–437. Rollin, M., Vandervort, D., & Haralambie, A. M. (2005). Federal child welfare law and policy: Understanding the federal law and funding process. In M. Ventrell & D. N. Duquette (Eds.), Child welfare law and practice: Representing children, parents, and state agencies in abuse, neglect, and dependency cases (pp. 143–183). Denver: Bradford. Rosenfeld, A. A., Pilowsky, D. J., Fine, P., Thorpe, M., Fein, E., Simms, M. D., et al. (1997). Foster care: An update. Journal of the American Academy of Child & Adolescent Psychiatry, 36, 448–457. Rubin, D. M., O’Reilly, A. L., Luan, X., & Localio, A. R. (2007). The impact of placement stability on behavioral well-being for children in foster care. Pediatrics, 119, 336–344. Schene, P. A. (1998). Past, present, and future roles of child protective services. The Future of Children, 8, 23–38. Sedlak, A. J., & Broadhurst, D. D. (1996). Third national incidence study of child Abuse and neglect: Final report. Washington, DC: U.S. Department of Health and Human Services. Sedlak, A., McPherson, K., & Das, B. (2010). Supplementary analyses of race differences in child maltreatment rates in the NIS-4. Washington, DC: US Department of Health and Human Services, Administration for Children and Families, Office of Planning, Research, & Evaluation and the Children’s Bureau. Retrieved from http://www.acf.hhs.gov/sites/default/files/opre/nis4_ supp_analysis_race_diff_mar2010.pdf Slovak, K., & Carlson, K. (2009). The dynamics of rural poverty. In C. A. Broussard & A. Joseph (Eds.), Family poverty in diverse contexts (pp. 64–77). New York: Routledge. Solinger, R. (1994). Wake up little Susie: Single pregnancy and race before Roe v. Wade. New York: Routledge. Substance Abuse and Mental Health Services Administration (SAMHSA). (2013). The NSDUH report: Need for and receipt of substance use treatment among Hispanics.

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Tatum, B. D. (1992). Talking about race, learning about racism: The application of racial identity theory in the classroom. Harvard Education Review, 62, 1–24. Vinokur-Kaplan, D., & Hartman, A. (1986). A national profile of child welfare workers and supervisors. Child Welfare, 65, 323–335. Waldfogel, J. (1998). Rethinking the paradigm for child protection. The Future of Children, 8, 104–119. Waldfogel, J. (2000). Child welfare research: How adequate are the data? Children and Youth Services Review, 22, 705–741. Wells, M., & Correia, M. (2012). Reentry into out-of-home care: Implications of child welfare workers’ assessments of risk and safety. Social Work Research, 36, 181–195. Wheeler, L. (1983). The orphan trains. American History Illustrated, 18, 10–23. Williams, T. (2019). Black people are charged at a higher rate than whites. What if prosecutors didn’t know their race? The New York Times. Wulczyn, F. (2004). Family reunification. The Future of Children, 14, 95–113. Yelick, A., & Thyer, B. (2020). The effects of family structure and race on decision-making in child welfare. Journal of Public Child Welfare, 14, 336–356. https://doi.org/10.1080/15548732.2019. 1616651.

Jessica Pryce is a faculty member at Florida State University and currently the Executive Director of the Florida Institute for Child Welfare. For the past 10 years, she has been involved at multiple angles of child welfare (direct practice, teaching/training and policy and research). She has published on child welfare related topics, such as, training and education, racial disparity and research and community partnerships. Dr. Pryce has worked on the frontlines of child welfare, conducted primary research, been a policy advisor to Florida’s legislature and taught graduate level courses in child welfare. In 2019, she received a 5-year appointment to the Advisory Board of the National Child Welfare Workforce Institute. She has maintained and cultivated a commitment to the wellbeing of vulnerable children and families, the sustainability of the child welfare workforce, and effectively addressing inequity. Her paramount goal includes re-building and leading a child welfare system that focuses on strengthening families instead of pulling them apart. Anna Yelick currently works as a post-doctoral research scholar with the Florida Institute for Child Welfare at Florida State University, a position she has worked at since completing her dissertation in 2018. Dr. Yelick’s research interests include decision-making among child welfare professionals to reduce disparity and disproportionality among families and youth who are most vulnerable. Her publication in the Journal of Public Child Welfare, highlighted the need to further explore fidelity of the Florida Practice Model to assess the impact the practice model has on decision-making across the state. Dr. Yelick is also researching the effectiveness of Kinship Navigator Programs in addressing the needs of kinship caregivers and kinship children. Dr. Yelick is also an adjunct professor with Florida State University College of Social Work and serves as an on-call victims’ advocate.

Chapter 5

Racial Disproportionality and Disparities Among Latinx Children Michelle Johnson-Motoyama, Rebecca Phillips, and Oliver Beer

5.1

Introduction

In recent years, the notion of a “Hispanic health paradox” in child welfare has been advanced to suggest that despite inordinate socioeconomic risk, Latinx children and families are less likely to experience maltreatment and less likely to come into contact with the U.S. child welfare system when compared to children and families of similar socioeconomic position in other racial/ethnic groups.1 However, close examination of the limited research on disproportionality and disparities among the Latinx population tells a more complex and nuanced story of risk, resilience, and differential treatment within the U.S. child welfare system that is still in its infancy. The term “disproportionality” refers to the ratio of the percentage of Latinx individuals experiencing maltreatment or at a particular decision point along the child welfare continuum of services to the percentage of Latinx individuals in the general population (Fong, McRoy, & Dettlaff, 2014). The term “disparity” refers to “unequal treatment or outcomes for different groups in the same circumstance or at the same decision point” (Fong et al., 2014). Information regarding disproportionality and disparities in child maltreatment and child protective services (CPS) involvement with regard to the Latinx population is drawn from a number of sources. National Note: “Latinx” and “Hispanic” are used interchangeably in this chapter though they have different meanings and origins. Blackwell, Boj, and Urrieta (2017, p. 129) use Latinx to “embrace the challenge to gender binaries posed by LGBT, genderqueer, and nonnormative gender activists and intellectuals. . .and reflects the shifting terrain of identification and the ongoing commitment to building unity through embracing the diversity of Latinidad by not erasing difference and specificity.” Hispanic is defined as “of or relating to the people, speech, or culture of Spain or of Spain and Portugal, or; of, relating to, or being a person of Latin American descent living in the U.S.” (Merriam Webster, 2018).

1

M. Johnson-Motoyama (*) · R. Phillips · O. Beer College of Social Work, The Ohio State University, Columbus, OH, USA e-mail: [email protected] © Springer Nature Switzerland AG 2021 A. J. Dettlaff (ed.), Racial Disproportionality and Disparities in the Child Welfare System, Child Maltreatment 11, https://doi.org/10.1007/978-3-030-54314-3_5

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Table 5.1 Racial/ethnic disparities in education, poverty, health and child maltreatment Enrolled in high school (%) Did not complete HS (%) Living in poverty (%) Developmental disability diagnosis (%) Report having “excellent” health (%) % of children with no health insurance % of adults with no health insurance Overall maltreatment rate (per 1000) Cumulative investigated (%) Cumulative substantiated (%) Substantiation rate (per 1000)

Latinx 7.1 21.6 18.3 1.9 37.9 23.8 31 14.2 32 13 8

White 5.2 9.4 8.7 4.1 66.1 6.4 12 12.6 28.2 10.7 8.1

Black 6.2 10.2 21.2 2.8 47.3 9.2 20 24 53 20.9 13.9

Citation U.S. Census Bureau (2017) U.S. Census Bureau (2017) U.S. Census Bureau (2016) Lau, Lin, and Flores (2012) Lau et al. (2012) Lau et al. (2012) CDC (2018) Sedlak et al. (2010) Kim et al. (2017) Wildeman et al. (2014) USDHHS (2018)

data sources include the National Incidence Study of Child Abuse and Neglect (NIS), which seeks to document rates of actual vs. reported child maltreatment through a representative sample of professional reporters, and the National Child Abuse and Neglect Data System (NCANDS), which includes official reports of maltreatment made to state CPS agencies. With regard to disparities, results from the Fourth National Incidence Study suggest that child maltreatment rates are slightly higher for Latinx children when compared to White children but significantly lower than that of Black children (see Table 5.1; Sedlak et al., 2010). According to recent data from NCANDS, Latinx children experience maltreatment that is substantiated by state child protective services (CPS) agencies at a rate lower than the national average (13.9/1000) and commensurate with Whites (USDHHS, 2018). Yet studies that have examined maltreatment over the course of a child’s lifetime suggest that Latinx children experience a cumulative incidence of investigated and substantiated maltreatment that is higher than White children (Kim, Wildeman, Jonson-Reid, & Drake, 2017; Wildeman et al., 2014). While children of all races and ethnicities experience a similarly high prevalence of neglect followed by physical abuse, sexual abuse and emotional abuse, Latinx children demonstrate the highest cumulative incidence of investigated emotional abuse when compared to other groups (Kim et al., 2017). National studies relying on adolescent self-report have also found Latinx children to be more likely to report supervisory neglect, physical neglect, and physical assault when compared to non-Latinx White children; however, these differences are no longer statistically significant after adjusting for sociodemographic characteristics (Hussey, Chang, & Kotch, 2006). With regard to disproportionality, national data from NCANDS and the Adoption and Foster Care Analysis and Reporting System (AFCARS) demonstrate that nationally, the representation of Latinx children across the child welfare continuum is proportional to their representation in the general population in any given year. Latinx children under the age of 18 comprise 22.6% percent (18.6 million) of the total U.S. population (U.S. Census Bureau, 2017), 22% of child victims (USDHHS, 2018), and 20% of children entering foster care

5 Racial Disproportionality and Disparities Among Latinx Children

71

(USDHHS, 2018). Of children exiting foster care, 21% were Hispanic and of all children adopted with public agency involvement, 22% were Hispanic. However, local studies demonstrate the importance of the role of geographic location in disproportionality, with some studies finding Latinx children overrepresented in certain states and smaller jurisdictions in the U.S. and underrepresented in others (Fluke, Harden, Jenkins, & Ruehrdanz, 2010). Studies suggest disproportionality and disparities in child welfare vary not only by geography among the Latinx population when compared with other major racial/ethnic groups, but also between Latinx subgroups based on factors such as birthplace, geographic location, socioeconomic position, country of origin, language, and immigration experiences, among a host of other factors. Research also reveals disparate findings with regard to patterns of disproportionality and disparities by maltreatment subtype. Knowledge of these differences, and the theories that have been advanced to explain them, is critically important for the design of effective strategies to address disproportionality and disparities and to prevent child maltreatment. In this chapter, we explore the history and diversity of the Latinx population in the U.S. and present available data on disparities and disproportionality in child maltreatment and child welfare system involvement. We examine the major theories that have been advanced to explain disproportionality and disparities among Latinx children, propose strategies to address observed differences, and outline future directions for research.

5.2

History and Diversity of the Latinx Population in the U.S.

The Latinx population in the U.S. has historically been characterized by rapid growth and geographic dispersion (Stepler & Lopez, 2016) (see Table 5.2). Presently, the Latinx population is the second largest racial or ethnic group in the U.S. behind Whites with a population of 58.9 million (U.S. Census Bureau, 2017) and states with the largest Latinx populations include California, Texas, Florida, New York, and Illinois (Flores, 2017). Often considered a single racial/ethnic group for purposes of research and data collection, significant heterogeneity exists within the Latinx population in the U.S. particularly in country of origin and population dispersion. The growth of Latinx children in contact with the U.S. child protective services system at the national level has been largely commensurate with growth in the general population. By 2060, Latinx children are expected to make up 32% of children under 18 years of age (Vespa, Armstrong, & Medina, 2018). However, recent research suggests a slowing in growth and dispersion since the 2007 recession, in addition to a sharp decline in Latinx fertility (Stepler & Lopez, 2016). The decline in migration from specific areas (e.g., Mexico) has partly been attributed to recent U.S. immigration policy changes and enforcement (Krogstad & Lopez, 2014).

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Table 5.2 Demographic characteristics of the Latinx Population in the US Overall latinx population (%) Latinx youth population (%) Child maltreatment victims (%) U.S. region (%) West South Northeast Midwest Country of origin (%) Mexican Puerto Rican Other South American Spanish and other Salvadoran Cuban Dominican Guatemalan Honduran Other central American a

2000 12.5

2010

2015 17.6

16

22.6

Citation U.S. Census Bureau (2000), Flores, Lopez, and Radford (2017) U.S. Census Bureau (2000, 2017)

14.2

24.9

USDHHS (2002, 2018)

18.9 7.8 7.2 2.8

29.7 17.2 14 7.6

Fry and Gonzales (2008), Flores et al. (2017)

Tienda and Sánchez (2013), U.S. Census Bureau (2017) 61.3 a

14.4 a

6.3 5.8 4.6 4.3 a

3.3

63.3 9.5 6.1 4.8 3.8 3.7 3.3 2.5 1.5 1.5