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Record W2113957410 · doi:10.5539/ass.v8n13p239

Involvement in Agro-tourism Activities among Fishermen Community in Two Selected Desa Wawasan Nelayan Villages in Malaysia

2012· article· en· W2113957410 on OpenAlexvenueno aff
Mahazan Muhammad, Azimi Hamzah, Hayrol Azril Mohamed Shaffril, Jeffrey Lawrence D Silva, Sulaiman Md. Yassin, Bahaman Abu Samah, Neda Tiraieyari

Bibliographic record

VenueAsian Social Science · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicDiverse Aspects of Tourism Research
Canadian institutionsnot available
FundersUniversiti Putra Malaysia
KeywordsTourismGeographyAgricultural scienceSocioeconomicsBusinessSociologyBiology

Abstract

fetched live from OpenAlex

The agro-tourism activity in Desa Wawasan Nelayan is a new product of agro-tourism in Malaysia organized by Fisheries Development Authority of Malaysia. Local community involvement is important to the success of this agro-tourism programme. The main objective of this paper is to investigate the level of involvement of Desa Wawasan Nelayan community in agro-tourism activities. The data of this study is obtained from a survey of two Desa Wawasan Nelayan villages. A total of 220respondents were randomly selected to answer the questionnaire and the data was analyzed using the SPSS software.Based on this study, the overall mean score for level of involvement in agro-tourism activities in both states were moderate. However, both villages were found to have the highest mean score on involvement in environmental conservation activities and about their concern on the cleanliness of their village.The study recommends that more efforts should be taken by Desa Wawasan Nelayan community to be involved in agro-tourism activities that will significantly impact the local economy, social, and environment, and as a result will empower and support the cohesion of the community.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.029
Threshold uncertainty score0.058

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.030
GPT teacher head0.338
Teacher spread0.307 · 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

Citations4
Published2012
Admission routes1
Has abstractyes

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