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Record W2099219598 · doi:10.1002/hec.1237

Different dental care setting: does income matter?

2007· article· en· W2099219598 on OpenAlexaff
Sukanya Tianviwat, Virasakdi Chongsuvivatwong, Stephen Birch

Bibliographic record

VenueHealth Economics · 2007
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealthcare Policy and Management
Canadian institutionsMcMaster University
FundersRoyal Golden Jubilee (RGJ) Ph.D. Programme
KeywordsDental careEconomicsMedicineFamily medicine

Abstract

fetched live from OpenAlex

In this paper we consider the use of mobile dental clinics as a means of improving access to dental care among primary school children in Southern Thailand by reducing the opportunity cost of service use to parents. Parents' willingness to pay (WTP) is measured for three different services provided in a community hospital dental clinic and a school-based mobile clinic. Although the service setting does not affect significantly the WTP for treatment directly, the estimated positive association between WTP and income is modified by setting. The results indicate that the potential for mobile clinics to increase utilization of services among primary school children is associated with parents' income, with the difference in valuation of dental services between the two settings being less among lower income parents than higher income parents. However, even among lower income parents our results indicate that the potential for increasing service utilization among children depends on the improvements in access associated with the mobile clinic not being achieved at the opportunity cost of lower levels of effectiveness.

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)0.010
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 score0.009
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0090.001

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 head0.028
GPT teacher head0.282
Teacher spread0.254 · 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

Citations17
Published2007
Admission routes1
Has abstractyes

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