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Record W4386950250 · doi:10.1079/tourism.2023.0032

Pedal Power to the People? Cycle Tourism and Local Economic Development in Cuba

2023· article· en· W4386950250 on OpenAlexaff
Erin K. Sharpe

Bibliographic record

VenueTourism Cases · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicDiverse Aspects of Tourism Research
Canadian institutionsBrock University
Fundersnot available
KeywordsTourismLegislatureState (computer science)Tourism geographyChinaPrivate sectorBusinessEconomic growthGeographyEconomics

Abstract

fetched live from OpenAlex

Summary Cycle tourism is a rapidly growing niche sector of the tourism industry and has been highlighted for its potential as a tool for socio-economic development, particularly in rural communities. Although tourism is well established in Cuba, it is primarily beach-based and massively controlled by state entities. However, Cuba has recently made a series of legislative changes intended to grow private sector small business opportunities. These changes open up the possibility for Cuban people to play a greater economic role in tourism than previously, if opportunities can be identified and challenges overcome. This case study considers the potential of cycle tourism as a form of people-powering tourism in Cuba. Using interview, field-based, and textual data, this case study maps the current state of cycle tourism, its actors and their interactions, and the opportunities, current challenges, and requirements to grow people-powering cycling tourism in Cuba. Information © The Author 2023

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 categoriesInsufficient payload (model declined to judge)
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 score0.218
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.002

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 head0.026
GPT teacher head0.322
Teacher spread0.297 · 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.

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
Published2023
Admission routes1
Has abstractyes

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