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Record W3134001475 · doi:10.1108/jtf-10-2020-0187

Cuba’s response to COVID-19: lessons for the future

2021· article· en· W3134001475 on OpenAlexaff
Lana Wylie

Bibliographic record

VenueJournal of Tourism Futures · 2021
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicGlobal Public Health Policies and Epidemiology
Canadian institutionsMcMaster University
Fundersnot available
KeywordsDiplomacyContext (archaeology)TourismGovernment (linguistics)Political sciencePandemicPublic relationsMedical tourismEconomic growthGlobal healthPoliticsHealth careCoronavirus disease 2019 (COVID-19)GeographyMedicineDiseaseInfectious disease (medical specialty)EconomicsLaw

Abstract

fetched live from OpenAlex

Purpose The purpose of this paper is to examine the relevance of Cuba’s medical system, its health tourism and related diplomacy in the context of the recent COVID-19 pandemic for the global response to disease outbreaks. In addition to Cuba being a destination for leisure tourists in the Caribbean, the renowned Cuban medical system attracts thousands of health tourists seeking low-cost but high-quality treatment. This paper demonstrates how Cuba’s unique response to the pandemic, which included sending thousands of medical staff abroad, can inform structural and global issues and contribute to a more sustainable future. Design/methodology/approach The research in this study is primarily drawn from published academic and media sources that address Cuba’s medical system, its health tourism and the government’s response to the recent pandemic. The author, a political scientist and an author of many publications on Cuba, and the PI of a study focused on Cuban tourism, will also draw on her expertise. Findings This paper addresses the Cuban Government’s ongoing response to the COVID-19 pandemic and places this response in the context of Cuba’s medical system, its health tourism and related diplomacy. It reveals key lessons from Cuba’s response for other tourist destination states and, more broadly, for the worldwide response to global outbreaks and the management of health systems. The findings will further research in diplomacy and tourism as well as inform policy and practice. Research limitations/implications This paper explores an ongoing topic and thus further research will be required following the pandemic. Practical implications This research note offers important implications for practice including providing accurate, research-based information that challenges misinformation about Cuba’s health system, its medical diplomacy program, health tourism and its response to COVID-19. It offers valuable lessons for public health authorities including the importance of preventative health measures, community medicine and the benefits of working globally to combat outbreaks through the sharing of medical staff and resources. Social implications This research note reveals the health, political and social implications of Cuba’s response in this time of crisis. It shows the benefits of a robust but low-cost community-based medicine program, medical diplomacy and how a state’s response during crisis can moderate the global inequities and injustices such as unequal access to care that often accompany disease outbreaks such as COVID-19. Originality/value This research note is an early analysis of a response by an important tourist destination country to the pandemic. The author anticipates that the information provided to the international community via this open access journal will offer practical implications for the ongoing global efforts to manage this crisis and contribute to the research on tourism, diplomacy, justice and health policy.

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)0.003
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.243
Threshold uncertainty score0.484

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0050.003
Scholarly communication0.0070.004
Open science0.0010.004
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0120.001

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 head0.044
GPT teacher head0.364
Teacher spread0.320 · 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 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

Citations13
Published2021
Admission routes1
Has abstractyes

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