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Record W2183272137

Use of dental services by immigrant Canadians.

2006· article· en· W2183272137 on OpenAlexaffabout
K. Bruce Newbold, Amish Patel

Bibliographic record

VenuePubMed · 2006
Typearticle
Languageen
FieldHealth Professions
TopicGlobal Health Workforce Issues
Canadian institutionsMcMaster University
Fundersnot available
KeywordsImmigrationForeign bornDental insuranceDental careNative-BornPopulationMedicineDental healthDemographyHealth careFamily medicineGerontologyGeographyEnvironmental healthPolitical scienceSociologyLaw
DOInot available

Abstract

fetched live from OpenAlex

Although the health status and health behaviour of foreign-born residents of Canada have been well documented, little is known about their use of dental services. The authors, hypothesizing that foreign-born people would have lower utilization of dental care services than native-born Canadians, undertook this study to identify the factors associated with dental visits by Canadians aged 12 years and older and to compare the use of dental services by foreign-born and native-born populations. According to data derived from Statistics Canada"s 1996-97 National Population Health Survey, foreign-born people were somewhat more likely than native-born Canadians to have visited a dentist within the previous year. Higher levels of education, greater income adequacy, and the presence of dental insurance were associated with greater use of dental services, whereas increasing age was associated with lower use. Although immigrants reported greater use of dental services than native-born Canadians, a variety of barriers to care may be present in this population.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.046
Threshold uncertainty score0.093

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.030
GPT teacher head0.319
Teacher spread0.289 · 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

Citations53
Published2006
Admission routes2
Has abstractyes

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