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Record W1977885621 · doi:10.5539/ass.v9n14p70

Revitalizing Ecotourism for a Sustainable Tasik Chini Biosphere Reserve

2013· article· en· W1977885621 on OpenAlexvenueno aff
A. Habibah, Ah Choy Er, I. Mushrifah, J. Hamzah, Amriah Buang, Mohd Ekhwan Toriman, Sharifah Mastura

Bibliographic record

VenueAsian Social Science · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicDiverse Aspects of Tourism Research
Canadian institutionsnot available
Fundersnot available
KeywordsEcotourismSustainabilityBiosphereBusinessSustainable developmentTourismEnvironmental planningGeneral partnershipEnvironmental resource managementPolitical scienceGeographyEcologyEnvironmental science

Abstract

fetched live from OpenAlex

Ecotourism is often perceived as an excellent tool for promoting sustainable development in most of the protected and special areas, including the Biosphere Reserve (BR). In fact, ecotourism can help to revive a declining tourist destination as it preserves nature and support rehabilitation and most importantly, it fits well with the Biosphere Reserve functions of conservation, development and logistics. This article aims to analyse the life cycle of Tasik Chini as an ecotourism destination, by focusing on the following aspects, namely travel engagement, ecotourism approaches and revitalization initiatives. This study utilized a mixed method approach by combining the primary and secondary data in tracing the evolution, development and the existing stage of ecotourism. The study reveals that the four major components which drive ecotourism program/initiatives toward achieving sustainable development are the state of ecotourism in the BR, the targeted segments of the community, the extent of community involvement as well as the supportive infrastructure for ecotourism. As ecotourism in the BR significantly promotes learning and research, smart partnership or collaboration between the stakeholders will help generate true eco-tourists. It is therefore imperative that ecotourism initiatives in the context of the BR is revitalised as it will enable a reflective analysis of the destination’s life cycle. The intervention of credible initiatives can fulfil the real and future roles of ecotourism in sustainable development.

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)0.003
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.946
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0050.002
Scholarly communication0.0010.003
Open science0.0020.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.024
GPT teacher head0.347
Teacher spread0.323 · 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 designTheoretical or conceptual
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

Citations12
Published2013
Admission routes1
Has abstractyes

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