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Record W2763939512 · doi:10.5296/jsss.v5i1.11975

Performance Evaluation of Tourism Sector Policy in Support of Bandung Creative City

2017· article· en· W2763939512 on OpenAlexaboutno aff
Thomas Bustomi, Raditya Pamungkas

Bibliographic record

VenueJournal of Social Science Studies · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicCommunity-based Tourism Development and Sustainability
Canadian institutionsnot available
Fundersnot available
KeywordsTourismDimension (graph theory)Quarter (Canadian coin)Resource (disambiguation)Economic sectorProcess (computing)Regional scienceEconomic geographyMarketingBusinessEconomyEconomicsSociologyPolitical scienceGeographyComputer science

Abstract

fetched live from OpenAlex

The existence of the tourism sector is no longer a complementary sector, but has become a major sector that can generate other sectors in an area. During the first quarter of 2014, growth in the tourism sector reached 6.86%, higher than the national economic growth that is equal to 5:21%. Bandung, as one of the icons of tourism in West Java, is proposed as UNESCO Creative City. This research paper uses data analysis techniques or methods Combination of Mixed Methods (quantitative and qualitative). The dimensions of performance evaluation policies, namely: Dimensional results, Dimension process, resource dimensions, dimensions of existence and development of the organization, and leadership dimensions. The dimensions of the above criteria will be juxtaposed with the Creative City. Paired results produces policy issues on which the consideration to conduct a review of tourism policy so as to produce a new policy supporting policy as Bandung Creative City.

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)0.021
metaresearch head score (Gemma)0.029
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.125

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0210.029
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0020.002
Scholarly communication0.0080.003
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.104
GPT teacher head0.450
Teacher spread0.346 · 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

Citations1
Published2017
Admission routes1
Has abstractyes

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