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Record W4402530856 · doi:10.61132/jutrabidi.v1i4.239

Kontribusi Ekonomi Kreatif Dalam Mendukung Sektor Pariwisata Di Kabupaten Sikka

2024· article· en· W4402530856 on OpenAlexaff
Bertholomeus Baghi Tjeme

Bibliographic record

VenueJurnal Transformasi Bisnis Digital · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicCommunity-based Tourism Development and Sustainability
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsTourismCreative economyPromotion (chess)General partnershipGovernment (linguistics)EconomyBusinessEconomicsPolitical scienceCreativityFinance

Abstract

fetched live from OpenAlex

Sikka Regency is an area with superior tourism potential but the contribution of the tourism sector does not have a significant influence on economic growth, this is due to the low contribution of the creative economy in supporting the tourism sector which is influenced by less attractive and competitive creative economy products, lack of promotion and branding, lack of collaboration and partnership between tourism actors and creative economy actors and lack of support from the government and related institutions. To overcome these problems, the proposed solution is the existence of regulations as a strong legal foundation and framework for policies and programs that support the creative economy in Sikka Regency. The writing of this Policy Paper aims to enable the creative economy to contribute more to the development of the tourism sector in Sikka Regency and increase regional economic growth as well as policy recommendations to overcome the low contribution of the creative economy to support tourism in Sikka Regency. The method used in this paper is problem tree analysis involving literature study, field observation and in-depth interviews with tourism and creative economy actors. The recommended policy option is a Sikka Regent Regulation on Creative Economy that can provide a legal framework and programs that support the development of the creative economy sector in Sikka Regency.

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), Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.955
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0020.003
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.019
GPT teacher head0.297
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 designNot applicable
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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