Disparity in child welfare referrals from public schools: An example of Simpson's Paradox?
BACKGROUND
Black children continue to be found in child welfare outcome measures at rates nearly double those of White children in the United States. Researchers have turned from bias theory to risk theory, arguing that disparity disappears when considering only the subgroup of children in poverty. In this study, we consider whether this phenomenon is an example of Simpson's Paradox, where aggregate findings are confounded by a third factor.


PARTICIPANTS
We created a dataset by matching child welfare data to schools in a metropolitan California county.


METHODS
We consider measures of poverty and racial-ethnic student composition as possible confounders, utilizing compositional data analysis for the latter. Traditional linear and ridge regression models were used to calculate the unadjusted and adjusted effects of each independent variable.


RESULTS
We find only partial evidence of Simpson's Paradox, in that Black to White disparity only disappears in the highest quartile of poverty. Holding poverty constant, only increasing student population non-White composition was significantly associated with reducing Black to White disparity ratios.


CONCLUSION
In a small, exploratory study, we find that while poverty may serve as an equalizer, diversity racial/ethnic student body composition may serve as a neutralizer. We find that underlying causes of disparity are complex and caution against endorsement of single theories to explain the disproportionate representation of Black children in child welfare. We find utility in analyzing child welfare data with concepts and techniques common in other disciplines and highlight several weaknesses of current child welfare informatics which impact both program evaluation and research.
['Thurston|Holly|H|', 'Miyamoto|Sheridan|S|']
D002648:Child D002669:Child Welfare D005260:Female D006801:Humans D008297:Male D012017:Referral and Consultation D012574:Schools D014481:United States
Disparity Child welfare referrals Disproportionality Risk bias Simpson’s Paradox Surveillance bias