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That Which is Essential has been Made Invisible: The Need to Bring a Structural Risk Perspective to Reduce Racial Disproportionality in Child Welfare

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Abstract

The racial and ethnic disproportionality and disparity in the child protective system (CPS) has been a concern for decades. Structural factors strongly influence engagement with the child welfare system and families experiencing poverty or financial hardship are at a heightened risk. The economic factors influencing child welfare involvement are further complicated by structural racism which has resulted in a greater prevalence of poverty and financial hardship for families who are Black, Native American or Alaska Native (Indigenous), or and Latino/Hispanic (Latino) and their communities. The multiple decision points within CPS are an opportunity to reify or correct for bias in child welfare outcomes. One major effort to eliminate racial disparities and disproportionalities has been to enact standardized decision-making procedures that aim to control for implicit or explicit bias in CPS. The Structured Decision-Making Model’s (SDM) actuarial-based risk assessment (RA) is the gold-standard of these efforts. In this conceptual article, we ask (1) How are structural factors accounted for in assessment of risk within CPS? and (2) What are the consequences when structural factors are left out of risk assessments procedures? We posit that the exclusion of race, ethnicity, and economic factors from the RA has inflated the importance of variables that become proxies for these factors, resulting in inaccurate assessments of risk. The construction of this tool reflects how structural racism has been overlooked as an important cause of disproportionality in CPS, with interventions then focused on individual workers and cases, rather than the system at large. We suggest a new framework for thinking about risk, the structural risk perspective, and call for a revisioning of assessment of risk within child welfare that acknowledges the social determinants of CPS involvement.

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Notes

  1. We define systematic and structural racism as the intersecting effects of residential segregation, White political power, inequality in educational opportunities and economic opportunities, and policies and practices designed to restrict access based on race.

  2. Studies that include children and families who are Native American or Indigenous find similar disproportionate results as studies find for children and families who are Black. However, the geographic distribution and much smaller size of the population means that many studies do not include this population or have too small of a sample to analyze. Therefore, we may refer only to Black families to accurately represent the results of studies.

  3. This is not to say that differential care has not been an issue in racially disparate outcomes for Blacks, Indigenous, and Latinos with COVID-19. There are multiple anecdotal accounts of physicians not taking their patients’ symptoms seriously, suggestive of widespread individual explicit and implicit bias in medical care.

References

  • Annie E. Casey Foundation. (2020). Annie E. Casey Foundation, Kids Count Data Center. https://datacenter.kidscount.org/updates/show/264-us-foster-care-population-by-raceand-ethnicity.

  • Annie E. Casey Foundation (AECF). (2012). Kids Count Data Snapshot on high-poverty communities. http://www.aecf.org/m/resourcedoc/AECFChildrenLivingInHighPovertyCommunities-2012-Full.pdf.

  • Baird, C., & Wagner, D. (2000). The relative validity of actuarial and consensus based risk assessment systems. Children and Youth Services Review, 22, 839–871.

    Article  Google Scholar 

  • Berger, L. M. (2004). Income, family structure, and child maltreatment risk. Children and Youth Services Review, 26(8), 725–748.

    Article  Google Scholar 

  • Berger, L. M., Font, S. A., Slack, K. S., & Waldfogel, J. (2017). Income and child maltreatment in unmarried families: Evidence from the earned income tax credit. Review of Economics of the Household. https://doi.org/10.1007/s11150-016-9346-9.

    Article  Google Scholar 

  • Bonilla-Silva, E. (1997). Rethinking racism: Toward a structural interpretation. American Sociological Review, 50, 465–480.

    Article  Google Scholar 

  • Bosk, E. A. (2018). What counts? quantification, worker judgment, and divergence in child welfare decision making. Human Service Organizations: Management, Leadership & Governance, 42(2), 205–224.

    Google Scholar 

  • Bosk, E. A. (2020). Iron cage or paper cage? The interplay of worker characteristics and organizational policy in shaping unequal responses to a standardized decision-making tool. Social Problems, 67(4), 654–676.

    Article  Google Scholar 

  • Bosk, E., & Feely, M. (2020). The Goldilocks Problem: Tensions between Actuarially Based and Clinical Judgment in Child Welfare Decision Making. Social Service Review, 94(4), 659-692.https://doi.org/10.1086/712060

    Article  Google Scholar 

  • Bowlby, J. (1969/1982). Attachment and Loss: Attachment (Vol. 1). New York: Basic Books.

    Google Scholar 

  • Bowlby, J. (1979). The making and breaking of affectional bonds. New York: Basic Books.

    Google Scholar 

  • Bowlby, J. (1980). Attachment and Loss: Loss Sadness and Depression (Vol. 3). New York: Basic Books.

    Google Scholar 

  • Bullinger, L. R., Feely, M., Raissian, K. M., & Schneider, W. (2019). Heed neglect, disrupt child maltreatment: A call to action for researchers. International Journal on Child Maltreatment: Research, Policy and Practice, 1–12.

  • Carlson, P. M., Feely, M., Kurz, B., Lin, H. J., Ives, M., Pierce, J., ... & Nilson, K. (2020). Connecticut’s family assessment response system. Journal of Public Child Welfare, 1–24

  • Cancian, M., Yang, M. Y., & Slack, K. S. (2013). The effect of additional child support income on the risk of child maltreatment. Social Service Review, 87(3), 417-437

    Article  Google Scholar 

  • Conger, R. D., Conger, K. J., Elder, G. H., Lorenz, F. O., Simons, R. L., Whitbeck, L. B., ... Simons, R. L. (1992). A family process model of economic hardship and adjustment of early adolescent boys. Child Development, 63(3), 526–541

  • 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.

  • Conrad-Hiebner, A., & Byram, E. (2020). The temporal impact of economic insecurity on child maltreatment: A systematic review. Trauma, Violence, & Abuse, 21(1), 157–178.

    Article  Google Scholar 

  • Corcoran, M. (2001). Mobility, persistence, and the consequences of poverty for children: Child and adult outcomes. In S. H. Danziger & R. H. Haveman (Eds.), Understanding poverty (pp. 127–161). New York: Russell Sage Found.

    Chapter  Google Scholar 

  • CRC. (1999). The Improvement of Child Protective Servies with Structured Decision Making: The CRC Model. In NCCD (Ed.).

  • Dankert, E.W. & Johnson, K. (2014). Risk assessment validation: A prospective study. California Department of Social Services, Children and Family Services Division, Children’s Research Center, National Council on Crime and Delinquency.

  • Derezotes, D. M., Testa, M. F., & Poertner, J. (2004). Race matters: Examining the overrepresentation of African Americans in the child welfare system. Washington DC: Child Welfare League of America.

    Google Scholar 

  • 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.

    Article  Google Scholar 

  • Drake, B., Lee, S. M., & Jonson-Reid, M. (2009). Race and child maltreatment reporting: Are Blacks overrepresented? Children and Youth Services Review, 31(3), 309–316.

    Article  Google Scholar 

  • Duncan, G. J., Yeung, W. J., Brooks-Gunn, J., & Smith, J. R. (1998). How much does childhood poverty affect the life chances of children? American Sociological Review, 63, 406–412.

    Article  Google Scholar 

  • Feely, M., Seay, K. D., & Loomis, A. M. (2019). Harsh physical punishment as a mediator between income, re-reports and out-of-home placement in a child protective services-involved population. Children and Youth Services Review, 103, 70–78.

    Article  Google Scholar 

  • Feely, M., Raissian, K., Schneider, W., Bullinger, L. (2020). The social welfare policy landscape and child protective services: Opportunities for and barriers to creating system synergy. Annals of the American Academy of Political and Social Sciences. 692(11):140-161

    Article  Google Scholar 

  • Fluke, J., Harden, B. J., Jenkins, M., & Ruehrdanz, A. (2011). Research synthesis on child welfare: Disproportionality and disparities. Disparities and Disproportionality in Child Welfare,

  • Fluke, J. D., Yuan, Y. 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.

  • Fong, K. (2019). Concealment and constraint: Child protective services fears and poor mothers’ institutional engagement. Social Forces, 97(4), 1785–1810.

    Article  Google Scholar 

  • Fong, K. (2020). Getting eyes in the home: child protective services investigations and state surveillance of family life. American Sociological Review, 85(4), 610–638.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • Font, S. A., & Maguire-Jack, K. (2015). Decision-making in child protective services: Influences at multiple levels of the social ecology. Child Abuse & Neglect, 47, 70-82.

    Article  Google Scholar 

  • Golash-Boza, T. (2016). A critical and comprehensive sociological theory of race and racism. Sociology of Race and Ethnicity, 2(2), 129–141.

    Article  Google Scholar 

  • Gambrill, E., & Shlonsky, A. (2000). Risk Assessment in context. Children and Youth Services Review, 22(11–12), 813–837.

    Article  Google Scholar 

  • Gambrill, E., & Shlonsky, A. (2001). The need for comprehensive risk management systems in child welfare. Children and Youth Services Review, 23(1), 79–107.

    Article  Google Scholar 

  • Gillingham, P., & Bromfield, L. (2008). Child protection, risk assessment and blame ideology. Children Australia, 33(1), 18–24.

    Article  Google Scholar 

  • Gillingham, P., & Humphreys, C. (2009). Child protection practitioners and decision-making tools: Observations and reflections from the front line. British Journal of Social Work, 40(8), 2598–2616.

    Article  Google Scholar 

  • Harcourt, B. (2015). Risk as a proxy for race: The dangers of risk assessment. Federal Sentencing Reporter, 27(4), 237–243.

    Article  Google Scholar 

  • Hirschman, D., & Bosk, E. A. (2019). Standardizing biases: Selection devices and the quantification of Race. Sociology of Race and Ethnicity. https://doi.org/10.1177/2332649219844797.

    Article  Google Scholar 

  • Johnson, K., Bogie, A. (2009). Risk assessment validation: A prospective study. Children’s Research Center, National Council on Crime and Delinquency. Madison, WI.

  • Kalev, A., Dobbin, F., & Kelly, E. (2006). Best practices or best guesses? Assessing the efficacy of corporate affirmative action and diversity policies. American Sociological Review, 71(4), 589–661.

    Article  Google Scholar 

  • Kim, H., & Drake, B. (2018). Child maltreatment risk as a function of poverty and race/ethnicity in the USA. International Journal of Epidemiology, 47(3), 780–787. https://doi.org/10.1093/ije/dyx280.

    Article  Google Scholar 

  • Kim, H., Wildeman, C., Jonson-Reid, M., & Drake, B. (2017). Lifetime prevalence of investigating child maltreatment among US children. American journal of public health, 107(2), 274–280.

    Article  Google Scholar 

  • Knoke, D., & Trocme, N. (2005). Reviewing the evidence on assessing risk for child abuse and neglect. Brief Treatment and Crisis Intervention, 5(3), 310–327. https://doi.org/10.1093/brief-treatment/mhi024.

    Article  Google Scholar 

  • Krase, K. S. (2013). Differences in racially disproportionate reporting of child maltreatment across report sources. Journal of Public Child Welfare, 7(4), 351–369.

    Article  Google Scholar 

  • Loman, L.A. & Siegel, G.L. (2004). An evaluation of the Minnesota SDM Family Risk Assessment, conducted for the Minnesota Department of Human Services. A report of the Institute of Applied Research. St. Louis, MO

  • Maguire-Jack, K., & Font, S. A. (2017). Community and individual risk factors for physical child abuse and child neglect: Variations by poverty status. Child Maltreatment, 22(3), 215–226. https://doi.org/10.1177/1077559517711806.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • Marcal, K. E. (2018). The impact of housing instability on child maltreatment: A causal investigation. Journal of Family Social Work, 21(4–5), 331–347. https://doi.org/10.1080/10522158.2018.1469563.

    Article  Google Scholar 

  • McEwen, C. A., & McEwen, B. S. (2017). Social structure, adversity, toxic stress, and intergenerational poverty: An early childhood model. Annual Review of Sociology, 43, 445–472.

    Article  Google Scholar 

  • Miller, M. G. (2008). Racial disproportionality in Washington State’s child welfare system. Olympia, WA: Washington State Institute for Public Policy.

    Google Scholar 

  • Miller, G. E., Chen, E., & Parker, K. J. (2011). Psychological stress in childhood and susceptibility to the chronic diseases of aging: Moving toward a model of behavioral and biological mechanisms. Psychological Bulletin, 137, 959–997.

    Article  Google Scholar 

  • Mukaka, M. M. (2012). A guide to appropriate use of correlation coefficient in medical research. Malawi Medical Journal, 24(3), 69–71.

    Google Scholar 

  • National Council on Crime and Delinquency (NCCD). (2015). Preliminary Risk Assessment Fit Analysis of the SDM® Family Risk Assessment Prepared for Texas Department of Family and Protective Services. NCCD, Children’s Research Center.

  • Patterson, J. M. (2002). Integrating family resilience and family stress theory. Journal of Marriage and Family, 64(2), 349–360.

    Article  Google Scholar 

  • Pelton, L. H. (2015). The continuing role of material factors in child maltreatment and placement. Child Abuse & Neglect, 41, 30–39.

    Article  Google Scholar 

  • Pew Research Center. (2015). Childlessness falls, family size grows among highly educated women. Washington, DC: May

  • Pirtle, W. N. L. (2020). Racial capitalism: a fundamental cause of novel coronavirus (COVID-19) pandemic inequities in the United States. Health Education & Behavior

  • Putnam, R. B. (2015). Our kids: The American Dream in Crisis. New York: Simon & Schuster.

    Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • Raissian, K. M. (2015). Does unemployment affect child abuse rates? Evidence from New York State. Child Abuse & Neglect, 48, 1–12.

    Article  Google Scholar 

  • Raissian, K. M., & Bullinger, L. R. (2017). Money matters: Does the minimum wage affect child maltreatment rates? Children and Youth Services Review, 72, 60–70.

    Article  Google Scholar 

  • Ray, V., & Purifoy, D. (2019). The Colorblind Organization', Race, Organizations, and the Organizing Process (Research in the Sociology of Organizations, Volume 60).

  • Regehr, C. (2018). Stress, trauma, and decision-making for social workers. Columbia University Press, New York.

    Book  Google Scholar 

  • 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(2), 2–7.

    Google Scholar 

  • Russell-Brown, D., & De Cao, E. (2018). The impact of unemployment on child maltreatment in the United States (No. 2018-04). ISER Working Paper Series.

  • Sedlak, A. J., Mettenburg, J., Basena, M., Peta, I., McPherson, K., & Greene, A. (2010). Fourth National Incidence Study of Child Abuse and Neglect (NIS-4). Washington, DC: US Department of Health and Human Services, 9, 2010.

  • Sharkey, P. (2008). The intergenerational transmission of context. American Journal of Sociology, 113, 931–969.

    Article  Google Scholar 

  • Sharkey, P., & Elwert, F. (2011). The legacy of disadvantage: Multigenerational neighborhood effects on cognitive ability. American Journal of Sociology, 116, 1934–1981.

    Article  Google Scholar 

  • Shonkoff, J. P., Garner, A. S., Siegel, B. S., Dobbins, M. I., Earls, M. F., McGuinn, L., ... & Committee on Early Childhood, Adoption, and Dependent Care. (2012). The lifelong effects of early childhood adversity and toxic stress. Pediatrics, 129(1), e232-e246

  • Schwalbe, C. S. (2008). Strengthening the integration of actuarial risk assessment with clinical judgment in an evidence based practice framework. Children and Youth Services Review, 30(12), 1458–1464

    Article  Google Scholar 

  • Schneider, W., Waldfogel, J., & Brooks-Gunn, J. (2017). The Great Recession and risk for child abuse and neglect. Children and Youth Services Review, 72, 71-81.

    Article  Google Scholar 

  • Slack, K. S., Holl, J. L., McDaniel, M., Yoo, J., & Bolger, K. (2004). Understanding the risks of child neglect: An exploration of poverty and parenting characteristics. Child maltreatment, 9(4), 395-408

    Article  Google Scholar 

  • Storer, A., Schneider, D., & Harknett, K. (2020). What explains racial/ethnic inequality in job quality in the service sector?. American Sociological Review, 85(4), 537-572.

    Google Scholar 

  • US Interagency Council on Homelessness. (2018). Homelessness in America: Focus on Families With Children.

  • Ungar, M. (2013). Resilience, trauma, context, and culture. Trauma, Violence, & Abuse, 14(3), 255–266.

    Article  Google Scholar 

  • U.S. Department of Health & Human Services, Administration for Children and Families, Administration on Children, Youth and Families, Children’s Bureau. (2019). Child Maltreatment 2017. Available from https://www.acf.hhs.gov/cb/research-data-technology/ statistics-research/child-maltreatment.

  • U.S. Department of Health & Human Services, Administration for Children and Families, Administration on Children, Youth and Families, Children’s Bureau. (2020). Child Maltreatment 2018. Available from https://www.acf.hhs.gov/cb/research-data-technology /statistics-research/child-maltreatment.

  • Wagmiller, R. L., Jr., & Adelman, R. M. (2009). Childhood and intergenerational poverty: The long-term consequences of growing up poor. New York: National Center for Children in Poverty.

    Google Scholar 

  • Warren, E. J., & Font, S. A. (2015). Housing insecurity, maternal stress, and child maltreatment: An application of the family stress model. Social Service Review, 89(1), 9–39.

    Article  Google Scholar 

  • Wildeman, C., Emanuel, N., Leventhal, J. M., Putnam-Hornstein, E., Waldfogel, J., & Lee, H. (2014). The prevalence of confirmed maltreatment among US children, 2004 to 2011. JAMA pediatrics, 168(8), 706–713.

    Article  Google Scholar 

  • Wooten, M., & Couloute, L. (2017). The production of racial inequality within and among organizations. Sociology Compass, 11(1), 1–10.

    Article  Google Scholar 

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Acknowledgements

The authors would like to thank the Doris Duke Fellowship for the Promotion for Child Well-Being for introducing them to each other and encouraging collaborative scholarship and research.

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Feely, M., Bosk, E.A. That Which is Essential has been Made Invisible: The Need to Bring a Structural Risk Perspective to Reduce Racial Disproportionality in Child Welfare. Race Soc Probl 13, 49–62 (2021). https://doi.org/10.1007/s12552-021-09313-8

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