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Record W3195311345 · doi:10.18280/ijsdp.160415

The Spiritual Path of Pilgrimage Tourism for Sustainable Development: Case-Desa Astana-Cirebon, Indonesia

2021· article· en· W3195311345 on OpenAlexvenueno aff
Hilwati Hindersah, Ina Helena Agustina, Ivan Chofyan

Bibliographic record

VenueInternational Journal of Sustainable Development and Planning · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicCommunity-based Tourism Development and Sustainability
Canadian institutionsnot available
FundersUniversitas Islam Bandung
KeywordsPilgrimageTourismDestinationsGeographyTourist destinationsJavaReligious tourismSocioeconomicsAncient historyArchaeologyHistorySociologyComputer science

Abstract

fetched live from OpenAlex

The Cirebon region which is located in the province of West Java, Indonesia has valuable artifacts and sites as a source of knowledge. Conservation in this area has not been actualized yet, even though it has potential for pilgrimage tourism destinations. The purpose of this research is to describe the spiritual path of Cirebon pilgrimage tourism. The method used is a case study, this method is more operational to find out why and how the spiritual path of the Cirebon pilgrimage was formed. The findings of this study are the existence of a spiritual path that connects the cemetery locations and sites such as: Talun Keramat Cemetery is located in Cirebon Girang Village, Talun District, Syekh Magelung Sakti Site is located in Karangkendal Village, Kepetakan District, Nyi Mas Gandasari Tomb is located in Pangurang Village. Arjawinangun District and one that is very well known to foreign countries is Astana Sunan Gunung Jati in Astana Village, Gunungjati District. The results of the study provide direction for developing a spiritual path to become a Cirebon tourist destination package as well as regional conservation.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.002
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.018
GPT teacher head0.293
Teacher spread0.275 · 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

Citations5
Published2021
Admission routes1
Has abstractyes

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