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Atractividad - Competitividad de destino turístico. Evaluación de Holguín para el mercado estadounidense

2019· article· es· W2999674037 on OpenAlexvenueno aff
Justa Ramona Medina Labrada, Elizabeth del Carmen Pérez Ricardo, Milagros de las Mercedes Riquenes Gainza

Bibliographic record

VenueConcienciaDigital · 2019
Typearticle
Languagees
FieldSocial Sciences
TopicGeography and Environmental Studies in Latin America
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical scienceHumanitiesPhilosophy

Abstract

fetched live from OpenAlex

El restablecimiento de las relaciones diplomáticas entre Cuba y Estados Unidos en 2015 provocó un crecimiento importante del flujo de visitantes estadounidenses a Cuba. A pesar de las restricciones legales que en la actualidad desestimulan dichos flujos, se consideró conveniente evaluar la atractividad - competitividad del destino turístico Holguín para distintos segmentos de clientes estadounidenses. Para desarrollar el estudio se propuso un procedimiento, que considera las mejores experiencias precedentes y que combina el análisis de la atractividad y la competitividad. Como resultado de la aplicación del procedimiento se determinaron los aspectos favorables y desfavorables que presenta el destino Holguín con relación a la atractividad turística para cada segmento estudiado; así como la posición competitiva que ocupa Holguín para los segmentos de yatistas, cruceristas y los que acceden por vía aérea. Se realizaron recomendaciones para favorecer la gestión efectiva del destino Holguín para dicho mercado

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)0.002
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.073
Threshold uncertainty score0.146

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0080.001

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 head0.015
GPT teacher head0.322
Teacher spread0.308 · 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

Citations1
Published2019
Admission routes1
Has abstractyes

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