Young Children and Ongoing Child Welfare Services: A Multilevel Examination of Clinical and Worker Characteristics
Bibliographic record
Abstract
There is a growing body of research that underscores that young child welfare-involved children are a unique vulnerable subgroup of children. The decision to provide postinvestigation child welfare services is consequential to children's safety and well-being and has fiscal implications for organizations. Despite the potential ramifications of the decision, there is little known about the factors associated with the ongoing services provision for young children. This study uses secondary data analysis of the Canadian Incidence Study of Reported Child Abuse and Neglect 2008 to explore what case and worker factors predict the provision of ongoing child welfare services. Multilevel modeling was used to assess the relationship between independent variables and the decision to provide ongoing services; analyses included 2,296 children and 555 workers. Case and worker characteristics, including worker training and worker position, predicted ongoing child welfare services suggesting that further research examining the role of what worker characteristics impact child welfare decisions is warranted and essential.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".