Racial and ethnic disparities: A population-based examination of risk factors for involvement with child protective services

Putnam‐Hornstein, Emily; Needell, Barbara; King, Bryn; Johnson‐Motoyama, Michelle

doi:10.1016/j.chiabu.2012.08.005

Cited by 348 publications

(206 citation statements)

References 41 publications

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“…Longitudinally linked records provide opportunities to overcome the limitations of any one administrative data source (Jutte et al 2011). For example, using California birth records linked at the individual-level to child protection records, researchers documented aggregate black-white disparities in CPS contacts, but found that black children actually had a significantly lower risk of maltreatment reports, confirmed victimization, and removals to foster care than white children after controlling for poverty and adjusting for other risk factors at birth (Putnam-Hornstein et al 2013). …”

Section: Introductionmentioning

confidence: 97%

Black–White Differences in Child Maltreatment Reports and Foster Care Placements: A Statistical Decomposition Using Linked Administrative Data

Maloney

Jiang

Putnam‐Hornstein

et al. 2017

Matern Child Health J

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Introduction Official statistics have confirmed that relative to their presence in the population and relative to white children, black children have consistently higher rates of contact with child protective services (CPS). We used linked administrative data and statistical decomposition techniques to generate new insights into black and white differences in child maltreatment reports and foster care placements. Methods Birth records for all children born in Allegheny County, Pennsylvania, between 2008 and 2010 were linked to administrative service records originating in multiple county data systems. Differences in rates of involvement with child protective services between black and white children by age 4 were decomposed using nonlinear regression techniques. Results Black children had rates of CPS involvement that were 3 times higher than white children. Racial differences were explained solely by parental marital status (i.e., being unmarried) and age at birth (i.e., predominantly teenage mothers). Adding other covariates did not capture any further racial differences in maltreatment reporting or foster care placement rates, they simply shifted differences already explained by marital status and age to these other variables. Discussion Racial differences in rates of maltreatment reports and foster care placements can be explained by a basic model that adjusts only for parental marital status and age at the time of birth. Increasing access to early prevention services for vulnerable families may reduce disparities in child protective service involvement. Using birth records linked to other administrative data sources provides an important means to developing population-based research.

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Section: Introductionmentioning

confidence: 97%

Black–White Differences in Child Maltreatment Reports and Foster Care Placements: A Statistical Decomposition Using Linked Administrative Data

Maloney

Jiang

Putnam‐Hornstein

et al. 2017

Matern Child Health J

Self Cite

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“…While disproportionality in the child welfare system is currently understood to be a complex issue with multiple causes (Putnam-Hornstein et al 2013, Pelton, 2015, Font et al 2015, child welfare research in the 1990s framed the persistent overrepresentation of racial and ethnic minorities as partly a result of decisionmaker bias in which "race, rather than risk, was the relevant factor" (Putnam-Hornstein et al 2013: 34). Decreasing cognitive errors in decision-making that rested on the heuristic errors and implicit biases of the child welfare worker therefore, represented an important policy corrective to race-based differential treatment (Gambrill and Shlonsky 2000).…”

Section: Structuring Child Welfare Decisionsmentioning

confidence: 99%

Standardizing Biases: Selection Devices and the Quantification of Race

Hirschman¹,

Bosk²

2017

Preprint

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Abstract:Racial inequality persists despite major advances in formal, legal equality. Scholars and policymakers argue that individual biases (both explicit and implicit) combine with subjective organizational decision-making practices to perpetuate racial inequality. The standardization of decision-making offers a potential solution, promising to eliminate the subjectivity that biases consequential decisions. We ask, under what conditions may standardization reduce racial inequality? Drawing on research in science studies and law and society, we argue that standardization must be understood as a heterogeneous practice capable of producing very different outcomes depending on the details of the standard and the organizational infrastructure surrounding its use. We compare "selection devices" -simple quantified tools for making allocation decisions -in undergraduate admissions and child welfare to highlight the complex relationships between race and standardization. Child welfare agencies adopted a colorblind actuarial device that attempted to predict which children were most at risk, and then make decisions based on those predictions. In contrast, the University of Michigan's points system explicitly considered and valued race, with the goal of increasing minority student enrollments in the context of promoting student body diversity. Comparing these cases demonstrates how actuarial standardization practices, including those adopted with the intention of reducing racial inequality, tend to reinforce an unequal status quo by ideologically reconfiguring mutable social structures into immutable individual risk factors. In contrast, non-actuarial practices that explicitly promote racial equality are vulnerable to political challenges, as they violate norms of colorblindness and cannot be defended in terms of their predictive validity.Acknowledgements:

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“…According to this model, over-represented racial/ethnic groups engage in higher rates of child maltreatment because they are, on average, exposed to more personal and community-level risk factors, such as poverty and unemployment, and tend to have less access to services and supports …' However, recently, on both sides of the Atlantic, evidence shows that when controlled for deprivation, rates of Black children in out-of-home care may not be raised compared to majority children and that each step increase in deprivation across society has a greater impact on intervention rates for White children than for Black Putnam-Hornstein et al, 2013;Wulczyn et al, 2013). Moreover, in England, children from…”

Section: Introductionmentioning

confidence: 99%

“…(There is less attention in studies of rates to other dimensions of identity such as gender, disability, age or sexual orientation, although differences are also apparent ). Explanations for racial or ethnic differences in intervention rates (Blackstock et al, 2004;Lonne et al, 2013;Putnam-Hornstein et al, 2013), sometimes extended to include religious affiliation (Attar-Schwartz et al, 2011), again commonly reflect the need vs bias dichotomy (Drake et al, 2011). Klein and Merritt (2011, p.96) describe these arguments:…”

Section: Introductionmentioning

confidence: 99%

Exploring inequities in child welfare and child protection services: Explaining the ‘inverse intervention law’

Bywaters

Brady

Sparks

et al. 2015

Children and Youth Services Review

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Attempts to record, understand and respond to variations in child welfare and protection reporting, service patterns and outcomes are international, numerous and longstanding.Reframing such variations as an issue of inequity between children and between families opens the way to a new approach to explaining the profound difference in intervention rates between and within countries and administrative districts. Recent accounts of variation have frequently been based on the idea that there is a binary divide between bias and risk (or need).Here we propose seeing supply (bias) and demand (risk) factors as two aspects of a single system, both framed, in part, by social structures. A recent finding from a study of intervention rates in England, the 'inverse intervention law', is used to illustrate the complex ways in which a range of factors interact to produce intervention rates. In turn, this analysis raises profound moral, policy, practice and research questions about current child welfare and child protection services.

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Racial and ethnic disparities: A population-based examination of risk factors for involvement with child protective services

Cited by 348 publications

References 41 publications

Black–White Differences in Child Maltreatment Reports and Foster Care Placements: A Statistical Decomposition Using Linked Administrative Data

Black–White Differences in Child Maltreatment Reports and Foster Care Placements: A Statistical Decomposition Using Linked Administrative Data

Standardizing Biases: Selection Devices and the Quantification of Race

Exploring inequities in child welfare and child protection services: Explaining the ‘inverse intervention law’

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