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Record W3123699186 · doi:10.5539/ass.v8n8p28

Tourism Impacts and Support for Tourism Development in Ha Long Bay, Vietnam: An Examination of Residents’ Perceptions

2012· article· en· W3123699186 on OpenAlexvenueno aff
Long Pham

Bibliographic record

VenueAsian Social Science · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicDiverse Aspects of Tourism Research
Canadian institutionsnot available
FundersUniversiti Utara Malaysia
KeywordsTourismBayContext (archaeology)Ethnic groupPerceptionSustainable tourismSustainable developmentVietnameseEconomic growthSocioeconomicsEcotourismTourism geographyGeographyPsychologyPolitical scienceSociology

Abstract

fetched live from OpenAlex

The impacts of tourism have been given much attention by scholars attempting to examine the perceptions as well as attitudes of the local residents toward tourism. Such studies have been carried out thoroughly in the context of the developed countries. However, very little research has been carried out in developing countries. This study attempts to make a little contribution to the sustainable development of tourism by examining the residents’ profile, perceptions and attitudes towards tourism impacts and tourism development in Ha Long Bay, the Vietnam’s first World Heritage Site (recognized in 1994). Data were collected by means of a questionnaire study. Based on 417 respondents surveyed, the findings show that the majority of respondents were young, Kinh rather than other ethnic group, they were married and were living in Ha Long Bay for over 20 years. On the whole, respondents viewed tourism positively and would support tourism development. They were generally in favor of tourism that contributes economically and socio-culturally to Ha Long Bay. They were, however, slightly ambivalent to environmental impacts of tourism. Implications, policy recommendations and limitations of study are presented in the conclusion.

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)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.854
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.002
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 head0.038
GPT teacher head0.368
Teacher spread0.330 · 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 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

Citations54
Published2012
Admission routes1
Has abstractyes

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