KAJIAN KESIAPAN PENERAPAN KONSEP KOTA KREATIF DESAIN DI SURAKARTA
Bibliographic record
Abstract
City plays important role making the city owns its high enchantment. This could effect on the emerging of city’s problems, where the city could not accommodate to all the complexity of people interest. Those problems need a new strategy to solve city’s problem which is more suitable to globalization era. The suitable solution is creative city which means city must be attractive by optimizing city’s local potentials. Surakarta, since 2013 has been established by the Ministry Of Tourism and Creative Economy of Indonesia to be a creative city of design by UCCN (UNESCO Creative City Network). There is much potency supporting Surakarta to be city of design. The existence of creative industries such as batik and furniture, various creative communities, creative spaces (Benteng Vastenburg, ISI, batik training organizations), and also various events based on cultural are good aspect to be considered. This research has purpose on knowing the readiness of Surakarta in implementing Creative City Of Design. The boundaries of this research are readiness of creative economy, readiness of creative community, readiness of creative space, readiness of leading, and readiness on holding events. This action then is followed by analyzing the readiness score of Surakarta as creative city of design. The research finding shows the readiness scales of Surakarta as creative city of design based on the five requirements that creative city must have. The research shows that Surakarta is not ready yet to be a creative city of design. There are some criterias that have not been accomplished. Creative economy, creative space, and experience in holding event are the lowest supporting aspect. Creative economy is the average in supporting creative city of design. Then the leading is the only one aspect who is ready in supporting implementation of Surakarta as city of design. Keywords: creative city, city of design
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.041 | 0.006 |
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".