Home, School, and Community Deprivations: A Multi-Context Approach to Childhood Poverty in China
Why this work is in the frame
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Bibliographic record
Abstract
Few studies of childhood poverty in China have considered social deprivations, and fewer still have considered deprivations in contexts beyond the household. In this article, the authors propose a multi-context poverty measure that includes economic and social deprivations in the family, school, and community domains. The authors compare this measure to standard money-metric measures of poverty using a 15-year longitudinal study of children from 100 villages in Northwest China. Nearly a quarter of multi-context poor children are not income poor, while almost three-fourths of the income poor are not multi-context poor. Social and community deprivations are only weakly associated with "money-metric" deprivations but are significantly linked with short and long-term welfare outcomes for children. The multi-context approach can be tailored to index household and community poverty alleviation targets.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it