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Record W2043976154 · doi:10.1080/15433714.2010.494984

Parental Perceptions of the Children in Need of Treatment Dental Program

2010· article· en· W2043976154 on OpenAlexaffabout
Patricia A. Sealy, Piotr Wilk, Charlene Beynon, Sandra Bennett, Ashley Hoogenboom

Bibliographic record

VenueJournal of Evidence-Based Social Work · 2010
Typearticle
Languageen
FieldDentistry
TopicDental Health and Care Utilization
Canadian institutionsMinistry of HealthMiddlesex London Health UnitWestern University
Fundersnot available
KeywordsChristian ministryMedicineFamily medicineGeneral partnershipPromotion (chess)Health promotionPublic healthMedical educationNursingPolitical science

Abstract

fetched live from OpenAlex

This paper discusses the collaborative partnership involving the Middlesex-London Public Health Research, Education and Development site, the Ontario Ministry of Health Promotion and Sport, then Chronic Disease Prevention and Health Promotion Branch, and an academic institution in the first-ever research of parental perceptions of the Children In Need Of Treatment. This paper provides an overview of the Children In Need Of Treatment program, reviews the results of the research (a mailed, self-administered survey with a systematic random sample of parents from three health units whose children received dental treatment that was paid by Children In Need Of Treatment in 2006), and its subsequent recommendations. How these recommendations affected program planning and policy are examined. In conclusion, parents were very satisfied with the treating dentist and the Children In Need Of Treatment program, and found Children In Need Of Treatment to be vital in addressing the health of their children by attending to their urgent dental 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.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.302

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.042
GPT teacher head0.362
Teacher spread0.320 · 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 teacher head, 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

Citations2
Published2010
Admission routes2
Has abstractyes

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