The Effects of Economic Crises on Families Caring for Children: Understanding and Reducing Long‐term Consequences
Why this work is in the frame
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Bibliographic record
Abstract
This article examines case examples of some of the consequences for children and families of average and severe economic and social disruptions, including the economic losses and failure of social supports during the transition after perestroika in Russia, the experience of poor families during economic retrenchment in Mexico, the massive asset loss in the capital of Honduras after a natural disaster, the dramatic economic contraction in Vietnam after the war, and the impact of the AIDS pandemic on both economic and social institutions in Botswana. It then considers social supports which have made a difference in acting as a buffer against the effect of economic downturns, drawing on primary data from in‐depth interviews with 2,000 families around the world, survey data on 55,000 households, and analysis of policies in all 192 members of the United Nations.
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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 | 0.001 | 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 it