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Record W3093605525 · doi:10.29173/topo29

Medical Tourism: A History and Overview of the Industry and the Case Study of Addiction Recovery in Spain

2017· article· en· W3093605525 on OpenAlexvenueno aff
Kazimir Haykowsky

Bibliographic record

VenueTopophilia · 2017
Typearticle
Languageen
FieldHealth Professions
TopicGlobal Healthcare and Medical Tourism
Canadian institutionsnot available
Fundersnot available
KeywordsMedical tourismTourismBusinessMarketingDiscretionPaternalismProfit (economics)Public relationsEconomic growthPolitical scienceEconomics

Abstract

fetched live from OpenAlex

This paper focuses on the emerging global market in medical tourism. The industry continues to expand and become increasingly profitable with greater popular support. This paper conveys the findings of a literature review on the origins, history and contemporary development of the industry. It explores the rationale and access of the medical tourist, and the purported benefits and costs to involved parties including patients, caregivers, citizens and governments. Ultimately it reveals that this phenomenon leads to lower costs, better care, discretion and leisure benefits to wealthy and mobile international clients while reducing available resources and quality of care for residents of host countries, which are mostly low and middle income countries and potentially costing source countries in aftercare. This paper examines the case study of international treatment for addiction in Spain and analyze two websites advertising the treatment for their use of promotional tactics, the importance of place and the relevance of Wilbert Gesler’s therapeutic landscape concept in marketing services. This reveals that international mobility allows businesses to profit from permissive legal environments and popular therapeutic landscapes abroad.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.509
Threshold uncertainty score0.961

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
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 science0.0000.000
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 head0.114
GPT teacher head0.428
Teacher spread0.314 · 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 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

Citations1
Published2017
Admission routes1
Has abstractyes

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