Poverty among Foster Children: Estimates Using the Supplemental Poverty Measure
Why this work is in the frame
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Bibliographic record
Abstract
We use data from the Current Population Survey and the new Supplemental Poverty Measure (SPM) to provide estimates for poverty among foster children over the period 1992 to 2013. These are the first large-scale national estimates for foster children who are not included in official poverty statistics. Holding child and family demographics constant, foster children have a lower risk of poverty than other children. Analyzing income in detail suggests that foster care payments likely play an important role in reducing the risk of poverty in this group. In contrast, we find that children living with grandparents have a higher risk of poverty than other children, even after taking demographics into account. Our estimates suggest that this excess risk is likely linked to their lower likelihood of receiving foster care or other income supports.
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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 | 0.004 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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