Inequalities in English child protection practice under austerity: A universal challenge?
Bibliographic record
Abstract
Abstract The role that area deprivation, family poverty, and austerity policies play in the demand for and supply of children's services has been a contested issue in England in recent years. These relationships have begun to be explored through the concept of inequalities in child welfare, in parallel to the established fields of inequalities in education and health. This article focuses on the relationship between economic inequality and out‐of‐home care and child protection interventions. The work scales up a pilot study in the West Midlands to an all‐England sample, representative of English regions and different levels of deprivation at a local authority (LA) level. The analysis evidences a strong relationship between deprivation and intervention rates and large inequalities between ethnic categories. There is further evidence of the inverse intervention law (Bywaters et al., 2015): For any given level of neighbourhood deprivation, higher rates of child welfare interventions are found in LAs that are less deprived overall. These patterns are taking place in the context of cuts in spending on English children's services between 2010–2011 and 2014–2015 that have been greatest in more deprived LAs. Implications for policy and practice to reduce such inequalities are suggested.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".