Quality of Early Childhood Health Care in the Los Angeles Healthy Kids Program Prepared for: Prepared By
Bibliographic record
Abstract
The Los Angeles Healthy Kids program was created in 2003 to provide health insurance to uninsured children ages 0–5 years in families with household income below 300 percent of the federal poverty level (FPL) who are ineligible for SCHIP or Medicaid. A quality of care survey sampled parents of 538 children ages 12–72 months enrolled in the program for at least one year, with a response rate of 91 percent. Parents reported whether they discussed their young child’s development and received recommended content of preventive care. Results show that quality of preventive care for children in Healthy Kids has similar patterns as care for children in lowincome households, both in California and nationally, based on the 2003 National Survey of Children’s Health. Among children with a recent preventive care visit, parents of only 31 percent of children in the Healthy Kids survey were asked about their concerns, and only a quarter received information about their specific concerns. Content of preventive care is well below American Academy of Pediatrics (AAP) recommendations, although it is consistent with statewide and national levels of care. Given that parental concerns about health and development are predictive of later learning and developmental problems, more systematic elicitation and discussion of concerns is an important area for strengthening care quality.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".