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Record W7099629562

Quality of Early Childhood Health Care in the Los Angeles Healthy Kids Program Prepared for: Prepared By

2007· article· en· W7099629562 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicGeochemistry and Geologic Mapping
Canadian institutionsnot available
Fundersnot available
KeywordsPreventive careQuarter (Canadian coin)PovertyHealth careEarly childhoodMedicaidHealth insuranceChild care
DOInot available

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.209
Threshold uncertainty score0.416

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.023
GPT teacher head0.333
Teacher spread0.311 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2007
Admission routes1
Has abstractyes

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