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Record W2103944229 · doi:10.5539/ass.v8n4p175

The Practice of Sustainable Tourism in Ecotourism Sites among Ecotourism Providers

2012· article· en· W2103944229 on OpenAlexvenueno aff
Norajlin Jaini, Ahmad Nazrin Aris Anuar, Mohd Salleh Daim

Bibliographic record

VenueAsian Social Science · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicDiverse Aspects of Tourism Research
Canadian institutionsnot available
FundersUniversiti Teknologi MARAMinistry of Higher Education, Malaysia
KeywordsEcotourismTourismBusinessRespondentSustainable tourismEnvironmental planningSustainable developmentMarketingSustainabilityAlternative tourismEnvironmental resource managementGeographyPolitical scienceEcologyEconomics

Abstract

fetched live from OpenAlex

Ecotourism and sustainable tourism have similar objectives to link conservation goals, economic and rural development. Ecotourism also offers educational and new experience to tourists, and it has to be developed and managed in an environmentally sensitive manner while protecting the environment. With the influx of eco-tourist into Malaysia, the numbers of tourism agencies interested to be ecotourism providers increased tremendously. Since there are no specific guidelines in practicing ecotourism, many tourism agencies normally proclaim themselves as eco-tour providers and served in the ecotourism industry without any restriction. This situation will definitely affect the environment due to lack of proper ecotourism practice. Therefore, the aim of this study is to investigate the standard of the current ecotourism practice among ecotourism providers in Malaysia. The main objective of this research is to determine whether ecotourism providers follow sustainable tourism practices. An ecotourism provider in Selangor and Kuala Lumpur has been selected as the respondent. This study attempts to help in identifying the best practices for ecotourism in Malaysia towards sustainable tourism.

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)0.012
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.855
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0120.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.003
Science and technology studies0.0040.006
Scholarly communication0.0010.005
Open science0.0020.000
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 head0.015
GPT teacher head0.333
Teacher spread0.319 · 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; both teacher heads agree on what is shown here.

Study designQualitative
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

Citations30
Published2012
Admission routes1
Has abstractyes

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