The Role of Place Identity, Local Genius, Orange Economy and Cultural Policies for Sustainability of Intangible Cultural Heritage in Bali
Bibliographic record
Abstract
This paper examines the relationship between orange economy activity which is an activity that allow for ideas to be transformed into cultural goods, local genius, place identity, cultural policies, and sustainability intangible cultural heritage (ICH) of Balinese handwoven textiles. A questionnaire survey was administered to 145 respondents. Partial Least Squares-Structural Equation Modelling (PLS-SEM) was applied to the resultant data using SmartPLS 3.0 software. The result revealed local genius, orange economy activity, and place identity have positive and significant influence on sustainability ICH of Balinese handwoven textiles. A positive and significant direct effect between local genius and place identity to the orange economy activity was also found. The result also proved that the orange economy mediates the relationship between local genius and place identity on sustainability. Moreover, cultural policies moderates the relationship between orange economy and sustainability. Our findings might also be relevant to sustainability Bali’s ICH to strengthening the involvement of cultural industry through orange economy activity, in enhancing their place identity and local genius, in supporting and promoting the sustainability ICH of Balinese handwoven textiles. Furthermore, the role of government through cultural policies might also relevant as moderating effect the relationship between orange economy activity and sustainability of ICH.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".