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Record W2028302561 · doi:10.1177/0020731414568512

“The Major Forces that Need to Back Medical Tourism Were … in Alignment”

2015· article· en· W2028302561 on OpenAlexaff
Rory Johnston, Valorie A. Crooks, Jeremy Snyder, Rebecca Whitmore

Bibliographic record

VenueInternational Journal of Health Services · 2015
Typearticle
Languageen
FieldHealth Professions
TopicGlobal Healthcare and Medical Tourism
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsTourismMedical tourismBusinessPolitical science

Abstract

fetched live from OpenAlex

Governments around the world have expressed interest in developing local medical tourism sectors, framing the industry as an opportunity for economic growth and health system improvement. This article addresses questions about how the desire to develop a medical tourism sector in a country emerges and which stakeholders are involved in both creating momentum and informing its progress. Presenting a thematic analysis of 19 key informant interviews conducted with domestic and international stakeholders in Barbados's medical tourism sector in 2011, we examine the roles that "actors" and "champions" at home and abroad have played in the sector's development. Physicians and the Barbadian government, along with international investors, the Medical Tourism Association, and development agencies, have promoted the industry, while actors such as medical tourists and international hospital accreditation companies are passively framing the terms of how medical tourism is unfolding in Barbados. Within this context, we seek to better understand the roles and relationships of various actors and champions implicated in the development of medical tourism in order to provide a more nuanced understanding of how the sector is emerging in Barbados and elsewhere and how its development might impact equitable health system development.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.603
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.066
GPT teacher head0.457
Teacher spread0.390 · 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 teacher head, 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

Citations16
Published2015
Admission routes1
Has abstractyes

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