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Record W2982189145 · doi:10.5539/ass.v15n11p93

An Evaluation on Climate Change Awareness in Tourism Sector in the Mekong Delta Region of Vietnam

2019· article· en· W2982189145 on OpenAlexvenueno aff
Awais Piracha

Bibliographic record

VenueAsian Social Science · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicDiverse Aspects of Tourism Research
Canadian institutionsnot available
Fundersnot available
KeywordsTourismStakeholderClimate changeContext (archaeology)BusinessMekong deltaEnvironmental resource managementGeographyPolitical sciencePublic relationsEconomicsWater resource management

Abstract

fetched live from OpenAlex

This study analyses the awareness level of key stakeholders about climate change impacts on the tourism sector in the Mekong Delta. In the regional context, stakeholders include tourism authorities, tourism businesses and tourists. The study investigates the following aspects of climate change awareness in the tourism sector in the region: 1) the climate change knowledge of tourism authorities, tourism businesses and tourists; 2) sources of awareness as well as quality of these sources; 3) climate change awareness education and action. As well as descriptive statistics, means and significant analysis, cross tabulation analysis is also used in this study to compare the awareness between stakeholder groups. The study found that the awareness level of tourism stakeholders in the region is at stage two of environmental awareness model of Partanen-Hertell et al. (Partanen-Hertell, Harju-Autti, Kreft-Burma, & Pemberton, 1999).

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)0.004
metaresearch head score (Gemma)0.004
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 score0.023
Threshold uncertainty score0.046

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.094
GPT teacher head0.405
Teacher spread0.311 · 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

Explore more

Same venueAsian Social Science→Same topicDiverse Aspects of Tourism Research→French-language works237,207→