Evaluation of a Newborn Screen for Predicting Out-of-Home Placement
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
A newborn screen designed to predict family risk was examined to: (a) determine whether all families with newborns were screened; (b) evaluate its predictive validity for identifying risk of out-of-home placement, as a proxy for maltreatment; (c) determine which items were most predictive of out-of-home placement. All infants born in Manitoba, Canada from 2000 to 2002 were followed until March 31, 2004 (N = 40,886) by linking four population-based data sets: (a) newborn screening data on biological, psychological, and social risks; (b) population registry data on demographics; (c) hospital discharge data on newborn birth records; (d) data on children entering out-of-home care. Of the study population, 18.4% were not screened and 3.0% were placed in out-of-home care at least once during the study period. Infants not screened were twice as likely to enter care compared to those screened (4.9% vs. 2.5%). Infants screening at risk were 15 times more likely to enter care than those screening "not at risk." Sensitivity and specificity of the screen were 77.6% and 83.3%, respectively. Screening efforts to identify vulnerable families missed a substantial portion of families needing support. The screening tool demonstrated moderate predictive validity for identifying children at risk of entering care in the first years of life.
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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) | 0.001 | 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 it