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Record W4413377573 · doi:10.56294/digi2025200

Guidelines for the design of a digital marketing strategy of the Cuban Ministry of Tourism aimed at the Canadian market

2025· article· en· W4413377573 on OpenAlexaboutno aff
Daniela Gascón Ramírez

Bibliographic record

VenueDiginomics · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicMedia, Gender, and Advertising
Canadian institutionsnot available
Fundersnot available
KeywordsChristian ministryTourismMarketingBusinessDigital marketingAdvertisingPolitical science

Abstract

fetched live from OpenAlex

Cuban Ministry of Tourism is in charge of managing communication around the Cuba destination. Given the lack of a structure in charge of Digital Marketing in this Organization, this area is neglected, leaving the entities of the Tourism System deprived of a guide for their actions. That is why the author proposes the design of a Digital Marketing Strategy for MINTUR, aimed at the Canadian public and supported by the official CubaTravel tourism portal, as the main way to market the destination. With this purpose, a descriptive, applied and production study is drawn up, under a qualitative approach. The methods and techniques used include documentary bibliographic review, semi-structured interviews, qualitative and quantitative content analysis of both the Ministry and its counterparts, as well as a focus group. All of this allows you to know the aspects of your remote environment, as well as features of the institution itself, its clients and competitors. The main challenge lies in the identification of accurate guidelines to position the ministry as the main reference for the promotion and information of the Cuba destination in the Canadian market. She addresses the topic with a view to the digital transformation of tourism, which is more than a necessity for research, it constitutes it for the nation.

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)0.002
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: Empirical
Teacher disagreement score0.403
Threshold uncertainty score0.991

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
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 integrity0.0000.000
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 head0.093
GPT teacher head0.347
Teacher spread0.254 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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