Strengths Moderate the Impact of Trauma on Risk Behaviors in Child Welfare
Bibliographic record
Abstract
Objectives: To determine whether traumatic experiences of children entering the child welfare system have an impact on their risk behaviors and whether these behaviors are moderated by children's strengths. Method: The Illinois Department of Children and Family Services administered the Child and Adolescent Needs and Strengths (CANS) measure to 8,131 children as they entered custody and analyzed Traumatic Experiences, Risk Behaviors and Strengths using polytomous logistic regression models. Results: Children entering child welfare have suffered multiple traumatic experiences. There is a strong linear relationship between the number of these experiences and the level of the children's high risk behaviors. However, there is an interactive effect between traumatic experiences and children's strengths on the risk behaviors, with strengths having a greater moderating effect as the number of traumatic experiences increases. Conclusions: Children entering the child welfare system present with complicated histories that include multiple traumatic experiences and multiple high risk behaviors. However, the more strengths these children have developed, the less likely they are to engage in high-risk behaviors. This resilience has major implications for both prevention and treatment.
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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 | 0.001 |
| 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".