Development and Evaluation of the Family Asset Builder: A New Child Protective Services Intervention to Address Chronic Neglect
Bibliographic record
Abstract
Over the past 20 years, neglect has been the most pervasive form of child maltreatment in the United States, affecting more than half a million children annually. Further, neglect is more likely than other forms of maltreatment to occur repeatedly within child welfare-involved families. Children experiencing neglect, especially early in childhood and with regularity, face long-term deleterious effects on their physical, cognitive, social, and emotional development. Despite the ubiquity of neglect throughout child welfare and the potentially devastating consequences, interventions designed to target families chronically reported to Child Protective Services (CPS) for neglect are scant. The Family Asset Builder intervention asserts that a strengths-based, supportive model of service delivery is essential to break the cycle of neglect early along the continuum of CPS involvement for families. Informed by current theory and practice, the solution-focused intervention offers intensive case management services (including more frequent contact and extended service delivery duration) to families with a history of neglect. Early in 2011, the Family Asset Builder intervention was piloted in two Minnesota counties; this study evaluates the development of the model, lessons learned from implementation, and early findings from the intervention, all of which set the stage for replication of the model and expansion of practice knowledge around chronic neglect.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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".