Untangling child welfare inequalities and the‘Inverse Intervention Law’ in England

Calum Webb, Paul Bywaters, Jonathan Scourfield, Claire McCartan, Lisa Bunting, Gavin Davidson, Kate Morris

Research output: Contribution to journalArticle

Abstract

This article addresses some potential limitations of key findings from recent research into inequalities in children’s social services by providing additional evidence from multilevel models that suggest the socio economic social gradient and ‘Inverse Intervention Law’ in children’s services interventions are statistically significant after controlling for possible confounding spatial and population effects. Multilevel negative binomial regression models are presented using English child welfare data to predict the following intervention rates at lower super output area-level: Child in Need (n = 2707, middle super output area [MSOA] n = 543, local authority [LA]n = 13); Child Protection Plan (n = 4115, MSOA n = 837, LA n = 18); and Children Looked After (n = 4115, MSOA n = 837, LA n = 18). We find strong evidence supporting the existence of a steep socioeconomic social gradient in child welfare interventions. Furthermore, we find certain local authority contexts exacerbate this social gradient. Contexts of low overall deprivation and high income inequality are associated with greater socioeconomic inequalities in neighbourhood intervention rates. The relationship between neighbourhood deprivation and children looked after rates is almost five times stronger in local authorities with these characteristics than it is in local authorities with high overall deprivation and low income inequality. We argue that social policy responses addressing structural determinants of child welfare inequalities are needed, and that strategies to reduce the numbers of children taken into care must address underlying poverty and income in equality at both a local and national level.
Original languageEnglish
Article number104849
Number of pages10
JournalChildren and Youth Services Review
Volume111
Early online date20 Feb 2020
DOIs
Publication statusPublished - 1 Apr 2020

    Fingerprint

Cite this