Measuring social and community services for children, youth, and families in contact with the child welfare system: A scoping review
Bibliographic record
Abstract
Administrative data can be used to systematically analyze and evaluate social and community services for families in contact with the child welfare system. These services aim to address social and economic disadvantages and prevent the recurrence of child maltreatment. The objectives were to: map the types of social and community services captured in child welfare administrative and linked data sources; describe population-based indicators that measure services; and identify data sources used to create service indicators. Children, youth, and/or families in contact with the child welfare system. A scoping review was conducted using MEDLINE/PubMed, EMBASE, PsycINFO, Scopus, and a grey literature search (2000 to 2023). The outcome of interest was social and community service-related indicators captured within or linked to child welfare administrative data. Twenty-nine articles met inclusion criteria. Types of services varied widely (e.g., parenting, financial, education). For service indicators, we identified 11 process indicator themes and 11 outcome indicator themes. Information on services were not typically included directly in child welfare administrative data. Most studies combined child welfare administrative data with service data using linkage methodology, with a median of two data sources per study. This review systematically classified social and community service categories, identified process and outcome service indicators, and examined data sources used to create service indicators. Findings can be used by child welfare agencies, other service providers, and public health organizations to improve child welfare data infrastructure and inform policy and practice decision-making. • Social and community services data are integral to child welfare prevention efforts • Identified service categories / indicators measuring social and community services • Service indicators utilized both child welfare administrative data and linked data • Service indicators inform child welfare prevention policy and programs
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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 | 0.025 | 0.100 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.006 |
| Bibliometrics | 0.039 | 0.042 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".