Bibliographic record
Abstract
Low Indonesian culinary exports indicate that Indonesian cuisine is not well-known internationally. Culinary promotes national identity, multiethnic cultures, and tourism. On the other hand, tourism exposes local culinary practices and can become a country's international brand. Furthermore, culinary relevance to public diplomacy is recognized. Through these connections, Indonesia can utilize gastro diplomacy to capture the global culinary arts market. Indonesia can learn from Thailand and South Korea how to implement the program more effectively by using the policy transfer framework. Thailand programs addressed various elements that must be developed when opening an overseas culinary arts business. They involved governmental and non-governmental agencies because the programs are board. The South Korean program was more formalized than the Thai programs by enacting a specific law and establishing a distinct organization to oversee the program’s execution. In addition to the healthy image of South Korean cuisine and the global trend toward healthier lifestyles, South Korea's program rode the Korean pop culture wave, which set the stage for the success of the program. Based on the analysis, the recommended model for Indonesia’s program implementation consists of six components in terms of menu and target diners, regulation, responsible organizations and coordination, goals, financing sources, and personnel.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.194 | 0.077 |
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".