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Understanding oral health beliefs and practices among Cantonese‐speaking older Australians

2010· article· en· W2118579449 on OpenAlexaff
Victor Minichiello, Michael I. MacEntee

Bibliographic record

VenueAustralasian Journal on Ageing · 2010
Typearticle
Languageen
FieldDentistry
TopicDental Health and Care Utilization
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsImmigrationEthnic groupOral healthChinaOral health careMedicineHealth careFamily medicineGovernment (linguistics)Dental careFocus groupNursingGerontologyPolitical scienceSociology

Abstract

fetched live from OpenAlex

AIM: The present study was conducted to explore how older immigrants from Hong Kong or Southern China manage their oral health in Melbourne. METHODS: We used six focus groups involving 50 Cantonese-speaking immigrants who were 55 years and over and living in Melbourne. RESULTS: Four major themes relevant to oral health care emerged from the discussion: (i) traditional Chinese health beliefs; (ii) traditional medicine and oral health; (iii) attitudes towards dentists; and (iv) access to oral health-care services. Language, communication and cost of dentistry were identified as major barriers to oral health care. CONCLUSION: Older Chinese immigrants in Melbourne have concerns about oral health care that are similar to other ethnic groups, they want more oral health-related support from government, and many of they return to China or Hong Kong for dental treatment.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.095
Threshold uncertainty score0.189

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.098
GPT teacher head0.386
Teacher spread0.288 · 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 designQualitative
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

Citations16
Published2010
Admission routes1
Has abstractyes

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