Bibliographic record
Abstract
PURPOSE OF REVIEW: This article reviews the impact of the Medicaid program, including the proportion of children in America insured by Medicaid; the extent to which Medicaid-enrolled children have access to care; the use of services and the quality of care received by Medicaid enrollees, including evidence for disease reduction; and family satisfaction with the program. RECENT FINDINGS: More than a quarter of all children in the United States were insured through public programs, primarily Medicaid, in 2002. Public insurance programs are even more critical for low-income children: 69.5% of children in families with incomes below 100% of the federal poverty level are covered by public programs. The reach of Medicaid is extensive, although substantial numbers of eligible children remain uninsured. Although Medicaid-insured children still face access barriers, particularly for certain types of specialty care, parents of children with public insurance report high levels of satisfaction with their experience with well-child care. While the study findings are mixed, several recent studies show very favorable comparisons between the experience of privately insured children and that of publicly insured children. SUMMARY: Medicaid plays a critical role in providing health insurance coverage for children, particularly for very low-income families. Additional efforts are needed to fully enroll all eligible families and to assure full access to high-quality care.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".