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Record W7030287412

Movement of Domestic Tourist in Malaysia in 2010 = Pergerakan Pelancong Domestik di Malaysia Tahun 2010

2024· article· en· W7030287412 on OpenAlexfundno aff

Bibliographic record

VenueUnimas Institutional Repository (Universiti Malaysia Sarawak) · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicDiverse Aspects of Tourism Research
Canadian institutionsnot available
FundersUniversiti Sains MalaysiaUniversity of WaterlooMinistry of Higher Education, Malaysia
KeywordsTourismVariety (cybernetics)Product (mathematics)Consumption (sociology)Domestic tourismMovement (music)Space (punctuation)Tourist attraction
DOInot available

Abstract

fetched live from OpenAlex

Malaysia is a one of the countries that was awarded with various natural attractions. The variety of race also built colorful culture that always offered variety prospects to tourists. Tourism industry in this country has gained attention as one of the main sectors in generating income. Therefore, many strategies have been planned and implemented to promote Malaysia as one of the main tourist hubs in the world. Tourism involving people movement through time and space, tourist experience in some locations is different and their consumption influenced by the pattern of movement. Pattern and trend of tourist movement influenced by various factors, and it was individualistic whether for domestic tourist or international tourist. Understand how tourist move through time and space is important to be implemented for infrastructure and transportation development, product development, destination and new attraction planning and it also important for management studies impact to social, environment and culture that caused by tourism sector. Using domestic tourist data from 2010 in Malaysia, the objective of this paper is to identify the pattern and trends of domestic tourist movement using GIS applications. In addition, this paper also aims to examine the significance of the destination choices made​​ by the tourists.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.632
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0010.002
Scholarly communication0.0000.002
Open science0.0010.000
Research integrity0.0000.001
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 head0.014
GPT teacher head0.275
Teacher spread0.261 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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