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Record W2901343483 · doi:10.21834/e-bpj.v3i9.1540

Why Ecotourism Failed as an Alternative Livelihood in Marine Park: The importance of community’s involvement in park management

2018· article· en· W2901343483 on OpenAlexafffund
Nor Azlina Abu Bakar, Geoffrey Wall

Bibliographic record

VenueEnvironment-Behaviour Proceedings Journal · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicDiverse Aspects of Tourism Research
Canadian institutionsUniversity of Waterloo
FundersUniversity of Waterloo
KeywordsLivelihoodEcotourismStakeholderTourismBusinessLocal communityEnvironmental planningLicenseEnvironmental resource managementGeographyPolitical scienceAgriculturePublic relationsEconomicsLaw

Abstract

fetched live from OpenAlex

This study investigates the impacts of park establishment on communities and how institutional structures, such as customary laws, can influence communities’ involvement in ecotourism. A sustainable livelihoods (SL) approach was adopted as a framework to analyze the relationships among institutional processes and organizational structures (i.e. NCR, institutional arrangement), livelihood strategies and livelihood outcomes. In-depth household surveys and stakeholder interviews were undertaken during three months of fieldwork conducted in Tun Sakaran Marine Park (TSMP), Sabah, Malaysia. Although TSMP contains beautiful islands, and has many attributes and potential to be suitable for ecotourism development, surprisingly, this study found out that the local communities are not involved in tourism. At the same time, dive operators are bringing divers and snorkelers to the park on a daily basis. In conclusion, ecotourism as an alternative livelihood in TSMP can be achieved through efficient institutions i.e. the implementation of policies that are informed by the local situation. Therefore, institutional support should be strengthened if ecotourism is to become a livelihood strategy for communities in TSMP.Keywords: Ecotourism; Sustainable Livelihoods; Institutional Arrangement; Marine ParkeISSN: 2398-4287 © 2018. The Authors. Published for AMER ABRA cE-Bs by e-International Publishing House, Ltd., UK. This is an open access article under the CC BYNC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer–review under responsibility of AMER (Association of Malaysian Environment-Behaviour Researchers), ABRA (Association of Behavioural Researchers on Asians) and cE-Bs (Centre for Environment-Behaviour Studies), Faculty of Architecture, Planning & Surveying, Universiti Teknologi MARA, Malaysia.https://doi.org/10.21834/e-bpj.v3i9.1540

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.165
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0020.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.031
GPT teacher head0.310
Teacher spread0.279 · 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

Citations8
Published2018
Admission routes2
Has abstractyes

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