Child Support in an Economic Downturn: Changes in Earnings, Child Support Orders, and Payments
Bibliographic record
Abstract
Changes in Earnings, Child Support Orders, and Payments The number of single parent families, especially mother-child families, has increased dramatically since the 1970s, and prior research has found that these families are particularly vulnerable to poverty (Mather, 2010). With approximately 40 percent of single mother families living in poverty and close to one quarter of single father families with poverty-level earnings (compared to 8.3 percent of married families living in poverty; U. S. Census Bureau, 2010), policymakers and the public have grown increasingly concerned about the well-being of children residing in single-parent homes. With growing numbers of children living in single-parent families and decreases in public aid for these families, child support has become an important source of income for single-parent families (Cancian, Meyer, and Park, 2003; Cancian and Meyer, 2006; Sorenson, 2010). This is especially the case for lower-income mothers as child support receipt is more crucial to their finances than it is for higherincome mothers (Sorensen and Zibman, 2000; Ha, Cancian, and Meyer, 2007). Nevertheless, researchers have found that child support receipts are often irregular and unstable in their timing and amounts (Ha et al., 2007). Multiple studies have revealed that many fathers, especially those living in poverty, either pay
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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 | 0.000 | 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 | 0.001 |
| 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 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".