The relationship of child neglect and physical maltreatment to placement outcomes and behavioral adjustment in children in foster care: a Canadian perspective.
Bibliographic record
Abstract
Dramatic increases in child welfare rates in Canada over recent years have been largely driven by an increased reporting of neglect cases (Trocmé, Fallon, MacLaurin, & Neves, 2005). To a large extent, exploring the importance of neglect separate from physical maltreatment has been ignored in the child maltreatment literature. This study examined the differential effects of foster care in the child welfare system with children who presented as either experiencing physical maltreatment or neglect prior to their admission to care. Findings from this study are important to child welfare decision making about the differential needs of these two groups of children. The files of a sample of 110 children (79 neglected children and 31 physically maltreated children) were examined for differences in their adjustment while in foster care and on discharge. Some distinct differences in presentation were noted between the children experiencing the two types of maltreatment. Children experiencing neglect were younger, were more likely to have caregivers diagnosed with a substance abuse disorder, and had higher rates of exposure to spousal violence than maltreated children. Physically maltreated children displayed greater difficulty during their foster care adjustment. Once discharged from care, neglected children were more likely to be returned to the care of the agency. This study draws attention to the differential needs of children who experience neglect prior to their admission to a child welfare agency. Longer-term outcome studies are necessary to more completely understand how these two types of maltreatment influence the outcomes of children who are provided care within the child welfare system.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".