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Record W2122595837

"Dental tourism": issues surrounding cross-border travel for dental care.

2009· article· en· W2122595837 on OpenAlexaboutno aff
Leigh Turner

Bibliographic record

VenuePubMed · 2009
Typearticle
Languageen
FieldHealth Professions
TopicGlobal Healthcare and Medical Tourism
Canadian institutionsnot available
Fundersnot available
KeywordsResidenceTRIPS architectureTourismDental carePopulationBusinessRevenueMedicineAdvertisingFamily medicineGeographyEnvironmental healthSociologyFinanceDemography
DOInot available

Abstract

fetched live from OpenAlex

When I visit my dentist I travel 4 kilometres from my residence to her office. My experience is commonplace; many Canadians commute from their homes or workplaces to see a nearby dentist. Although our coffee might come from Colombia and our clothes from China, for most of us dental care is as local as the neighbourhood grocery store, library or community centre. However, for some people, obtaining affordable dental care involves travel to another country. Journalists call these travellers “dental tourists.” Americans visit dentists in such Mexican border towns as Ciudad Juarez, Los Algodones, Nogales and Tijuana.1–3 Australians fly to Thailand for inexpensive dental care. People from England, Ireland and Wales journey to clinics in Bulgaria, Croatia, Hungary and Poland. In general, patients travel from higher-cost settings to regions where care is comparatively less expensive, and the price differential must be significant. Most “dental tourists” travel for treatment when the total cost of dental care, meals, accommodations, transportation and other expenses is less than the price of local care. The Internet facilitates cross-border dental care. Dental tourism companies advertise “allinclusive” travel packages that include dental procedures, hotel room reservations, side trips to tourist attractions and airline tickets. Dental clinics also use the web to attract international clients. People who consider travelling for dental care use the Internet to email sales representatives, submit digital images and negotiate prices. Given the size of the U.S. population and the proximity of the country to low-cost dental clinics in Mexico, far more Americans than Canadians presumably travel in search of affordable dental care. Nonetheless, Canadian snowbirds are among the customers seeking inexpensive care in Mexican clinics located adjacent to the borders of Arizona, California, New Mexico and Texas.4 An Ottawa-based company, The InciDental Tourist, sells dental tourism packages to China.5 The company states that care costing $8,400 in Canada is available in Nanjing for $1,840.6 Several Canadian medical tourism companies also market dental tourism “deals.”7–9 It is not surprising that dental tourism companies use patient testimonials to tout cost savings, customer satisfaction and quality of care. In turn, some dentists argue that inexpensive cross-border dental care is sometimes substandard. 10,11 They report encountering patients who have experienced serious complications as a result of obtaining low-priced dental care. Dental tourism companies respond to these criticisms by asserting that local dentists are merely protecting their own economic interests when they impugn “Dental Tourism”: Issues Surrounding Cross-Border Travel for Dental Care

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)0.005
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.025
Threshold uncertainty score0.078

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0090.004
Scholarly communication0.0070.007
Open science0.0020.007
Research integrity0.0100.009
Insufficient payload (model declined to judge)0.0230.003

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 head0.064
GPT teacher head0.494
Teacher spread0.430 · 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 designNot applicable
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

Citations18
Published2009
Admission routes1
Has abstractyes

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