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Record W1989358488 · doi:10.1377/hlthaff.2014.0273

Inequities In Health Care Needs For Children With Medical Complexity

2014· article· en· W1989358488 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueHealth Affairs · 2014
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealthcare Policy and Management
Canadian institutionsHospital for Sick Children
FundersNational Center for Advancing Translational Sciences
KeywordsHealth careMedicineFamily medicineNursingEconomic growthEconomics

Abstract

fetched live from OpenAlex

Children with special health care needs are believed to be susceptible to inequities in health and health care access. Within the group with special needs, there is a smaller group of children with medical complexity: children who require medical services beyond what is typically required by children with special health care needs. We describe health care inequities for the children with medical complexity compared to children with special health care needs but without medical complexity, based on a secondary analysis of data from the 2005-06 and 2009-10 National Survey of Children with Special Health Care Needs. The survey examines the prevalence, health care service use, and needs of children and youth with special care needs, as reported by their families. The inequities we examined were those based on race/ethnicity, primary language in the household, insurance type, and poverty status. We found that children with medical complexity were twice as likely to have at least one unmet need, compared to children without medical complexity. Among the children with medical complexity, unmet need was not associated with primary language, income level, or having Medicaid. We conclude that medical complexity itself can be a primary determinant of unmet needs.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.935
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.059
GPT teacher head0.302
Teacher spread0.243 · 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