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Record W17680945 · doi:10.24043/isj.280

Medical Tourism in the Caribbean Islands: A Cure for Economies in Crisis?

2013· article· en· W17680945 on OpenAlexaffvenue
John Connell

Bibliographic record

VenueIsland Studies Journal · 2013
Typearticle
Languageen
FieldHealth Professions
TopicGlobal Healthcare and Medical Tourism
Canadian institutionsUniversity of Prince Edward Island
Fundersnot available
KeywordsMedical tourismTourismDiversification (marketing strategy)Order (exchange)BusinessEconomyTourism geographySmall islandEconomic growthInternational tradePolitical scienceEconomic geographyGeographyEconomicsMarketingFinance

Abstract

fetched live from OpenAlex

Small island states have increasingly sought new means of economic diversification. Several Caribbean states have begun to develop medical tourism, partly building on existing tourist-oriented economies. Medical tourism has boomed in this century in several states in Asia and in Central America. The Bahamas, Barbados and the Cayman Islands exemplify different strategies for medical tourism, in order to generate foreign exchange and new employment, and reduce costs from overseas referrals. Most medical tourism projects have been developed by overseas corporations and are oriented to a US market. Business principles rather than health care dominate development strategies, notably of emerging transnational medical corporations, and raise ethical issues. Success will be difficult to achieve in a crowded and competitive market.

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)0.005
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 score0.038
Threshold uncertainty score0.075

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.006
Scholarly communication0.0060.007
Open science0.0010.006
Research integrity0.0040.006
Insufficient payload (model declined to judge)0.0150.002

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 head0.080
GPT teacher head0.460
Teacher spread0.380 · 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

Citations40
Published2013
Admission routes2
Has abstractyes

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