Bibliographic record
Abstract
Childhood disabilities entail a range of immediate and long-term economic costs that have important implications for the well-being of the child, the family, and society but that are difficult to measure. In an extensive research review, Mark Stabile and Sara Allin examine evidence about three kinds of costs-direct, out-of-pocket costs incurred as a result of the child's disability; indirect costs incurred by the family as it decides how best to cope with the disability; and long-term costs associated with the child's future economic performance. Not surprisingly, the evidence points to high direct costs for families with children with disabilities, though estimates vary considerably within these families. Out-of-pocket expenditures, particularly those for medical costs, for example, are higher among families with children with a special health care need. An important indirect cost for these families involves decisions about employment. Stabile and Allin examine several studies that, taken together, show that having a child with disabilities increases the likelihood that the mother (and less often the father) will either curtail hours of work or stop working altogether. Researchers also find that having a child with disabilities can affect a mother's own health and put substantial strains on the parents' relationship. In the longer term, disabilities also compromise a child's schooling and capacity to get and keep gainful employment as an adult, according to the studies Stabile and Allin review. Negative effects on future well-being appear to be much greater, on average, for children with mental health problems than for those with physical disabilities. Stabile and Allin calculate that the direct costs to families, indirect costs through reduced family labor supply, direct costs to disabled children as they age into the labor force, and the costs of safety net programs for children with disabilities average $30,500 a year per family with a disabled child. They note that the cost estimates on which they base their calculation vary widely depending on the methodology, jurisdiction, and data used. Because their calculations do not include all costs, notably medical costs covered through health insurance, they represent a lower bound. On that basis, Stabile and Allin argue that many expensive interventions to prevent and reduce childhood disability might well be justified by a cost-benefit calculation.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".