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Record W2541162818 · doi:10.1186/s13584-016-0115-2

Dental reform in Israel’s National Health Insurance Law has helped children and their families, but what’s next?

2016· letter· en· W2541162818 on OpenAlexaff
Carlos Quiñonez

Bibliographic record

VenueIsrael Journal of Health Policy Research · 2016
Typeletter
Languageen
FieldHealth Professions
TopicFood Security and Health in Diverse Populations
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsSocial policyPublic healthHealth promotionHealth policyEnvironmental healthOral healthSocial securityMedicineDental decayDental insuranceHealth care reformEconomic growthFamily medicinePolitical scienceLawNursingEconomics

Abstract

fetched live from OpenAlex

Through a nationally-representative survey of 6 year-old children, Natapov, Sasson and Zusman demonstrate that the 2010 dental reform to the National Health Insurance Law (NHIL) has helped to improve the oral health of children in Israel. While the prevalence of dental caries (tooth decay) in Israel's children has remained relatively stable over time, compared to previous surveys, children now have more treated than untreated disease, suggesting that the NHIL reform has increased utilization and access to dental care, and arguably improved the quality of life of children and their families. Even though inequalities in oral health remain, universal coverage for children in Isreal is a positive development; yet for further improvements in oral health to materialize, attention will arguably need to be paid to broader preventive measures (e.g. drinking water fluoridation, oral disease prevention and oral health promotion in primary care), and more importantly, to the social determinants of health (e.g. income security, fair income distribution, food security).

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 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)0.016
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity
Consensus categoriesResearch integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.192
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0160.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0040.001
Science and technology studies0.0050.001
Scholarly communication0.0000.002
Open science0.0010.001
Research integrity0.0020.015
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 head0.422
GPT teacher head0.555
Teacher spread0.132 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreCommentary

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

Citations3
Published2016
Admission routes1
Has abstractyes

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