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Record W7110551142

El Turismo en Cuba: Desarrollo, Retos y Perspectivas = Tourism in Cuba: Development, Challenges, Perspectives

2019· other· es· W7110551142 on OpenAlexaboutno aff

Bibliographic record

VenueUniversitat de Girona Digital Repository (Universitat de Girona) · 2019
Typeother
Languagees
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsTourismLatin AmericansGovernment (linguistics)PoliticsPrivate sectorForeign policy
DOInot available

Abstract

fetched live from OpenAlex

The main aim of this article is to adopt an economic-geographical approach to analyze the evolution of tourism in Cuba and its possibilities for further development. Among other aspects, the socio-economic and political history of Cuba, particularly during the second half of the 20th century, was linked to the development of tourism, and very much dependent on relations with the United States, its close neighbor to the north. After the Revolution, open hostility between Cuba and the US from 1959 onwards meant that the island turned its attention to the Canadian, European and Latin American tourist market to develop this sector. From 2015 following the establishment of diplomatic relations between the two countries which had been broken decades before, an inmediate increment took place in the visits of Americans to Cuba (by air and sea), although many of the limitations established by the US government over the past 50 years remain in place. While this change has aroused hopes in many businesspeople, investors, and national and foreign tourism operators. The increment of the tourism sector only lasted until Donald Trump became the President of the United States in 2017. It was followed by a reinforced economic, financial and commercial policy of blockade against Cuba set in place in 1962 together with the increments in legal obstacles to grant the permits required to travel to Cuba. Moreover, it has caused changes to Cuban economic dynamics due to the current development of small and medium-sized private providers of accommodation, catering and transportation services, among others, and the effects of this are yet to be determined with regard to improving the quality of life of the Cuban population

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.258
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0040.005
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0070.002
Science and technology studies0.0010.002
Scholarly communication0.0010.005
Open science0.0050.003
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0010.009

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 head0.008
GPT teacher head0.206
Teacher spread0.198 · 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; both teacher heads agree on what is shown here.

Study designQualitative
Domainnot available
GenreOther

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

Citations0
Published2019
Admission routes1
Has abstractyes

Explore more

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