Child neglect: predicting future protection concerns and a comparison of profiles
Bibliographic record
Abstract
Research suggests that factors that influence child maltreatment are not restricted to one \narea (e.g. parental characteristics, child characteristics, societal characteristics), but are spread \nacross numerous ecological systems. Child protection data from the Ontario Family and Child \nStrengths and Needs Assessment (FCSNA) was obtained. Records for children and caregivers of \n128 families who had verified child neglect allegations were used in predictive analyses, in order \nto determine which families would return with further child protection concerns. Results of \nlogistic regression analyses showed that variables related to caregiver capacity and social support \nwere predictive of verified maltreatment concern recurrence. Caregivers with alcohol, drug, and \nsubstance abuse concerns, resource management issues, and strengths in physical health were \nmore likely to be involved in recurrent investigations than those non-recurrent parents. Higher \nlevels of social support from peer and adult relationships (for children) indicated a greater \nlikelihood of child protection recurrence. Results suggest greater attention to substance abuse \nissues, as well as resource management and poverty in families with verified child neglect \nconcerns. Furthermore, the results offer insight into the nature of the relationship between child \nmaltreatment recurrence and social support. Recommendations of future research directions are \ndiscussed.
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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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".