MétaCan
Menu
Back to cohort
Record W2029191394 · doi:10.3354/cr01183

Differential climate preferences of international beach tourists

2013· article· en· W2029191394 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueClimate Research · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicDiverse Aspects of Tourism Research
Canadian institutionsUniversity of Waterloo
FundersSocial Sciences and Humanities Research Council of CanadaCanada Research Chairs
KeywordsTourismClimate changeGeographyTemperate climateEcology

Abstract

fetched live from OpenAlex

Weather and climate are a principal resource and constraint for tourism that directly and indirectly influence global demand patterns. Against the background of rapidly expanding literature on climate and tourism, this study sheds needed insight into the complexities of tourist climate preferences and the implications for rating current and future climate resources for tourism. A survey of 472 beach tourists is the basis for comparing the climatic preferences of diverse tourism market segments on the Caribbean islands of Barbados, Saint Lucia and Tobago. Key findings include warmer temperature preferences and tolerances for tourists originating from tropical regions, with lower heat preferences and tolerances for tourists from temperate regions. Statistically significant differences (p < 0.05) were also found between temperate and tropical residents for every climate variable examined (temperature, rain, sky conditions, wind). The results are discussed with regard to their implication for the construction of tourism climate indices, demand models and climate change assessments.

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.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.328
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0020.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0170.002

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 head0.103
GPT teacher head0.438
Teacher spread0.335 · 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