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Record W4391145926 · doi:10.1079/tourism.2024.0012

Experiencing Cambodia’s Living Arts through Tourism

2024· article· en· W4391145926 on OpenAlexaff
Bobbie Chew Bigby, Madura Thivanka Pathirana, Sarin Chhuon

Bibliographic record

VenueTourism Cases · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicCambodian History and Society
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsTourismThe artsGeographyVisual artsArtArchaeology

Abstract

fetched live from OpenAlex

Summary Experience Cambodian Living Arts (CLA) was a nightly program showcasing traditional Cambodian arts to tourists while providing employment opportunities to artists. Produced by the Cambodia-based non-profit organization CLA for nearly a decade, this program used tourism as a platform for sharing traditional arts while also earning revenue to support other arts initiatives and providing employment to several of its arts students. This case study offers a glimpse into the arts-based programming of CLA, an organization based in Cambodia that has worked to revitalize traditional arts and inspire younger generations to engage with the arts over the past 25 years. ‘Experience CLA’ was one of the organization’s programs that offered nightly performances of traditional dance, music and performing arts between 2011 and 2020. These performances stood at the heart of CLA’s efforts in sharing traditional arts with international visitors through tourism, providing a platform for employment to young Cambodian artists, as well as helping the organization to earn revenue. However, due to the impact of COVID-19 on tourism as well as CLA adopting a new mission and vision that positioned it as more of an arts catalyst, rather than as an arts provider, the ‘Experience CLA’ program came to an end in 2020 as the organization began to shift its role in the Cambodian arts community. Information © The Authors 2024

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.406
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.048
GPT teacher head0.329
Teacher spread0.282 · 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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