Advokasi Transportasi Berkelanjutan melalui Pembelajaran Moda di Jepang pada Festival Bunkasai Universitas Syiah Kuala, Banda Aceh
Bibliographic record
Abstract
This community service aims to promote public awareness of sustainable transportation through learning from Japan’s multimodal transport system. The activity was held at the Bunkasai Festival of Syiah Kuala University in Banda Aceh, where visitors were introduced to Japan’s transportation modes—ranging from rail, bus, bicycle-sharing, and walking systems—through maps, models, and interactive discussions. The program also presented a case study on the potential for Transit-Oriented Development (TOD) along Banda Aceh’s Trans Koetaradja corridor, connecting the concept of sustainability in transport with local practices. This initiative adopted an informative exhibition method supported by visual aids such as transport maps, infographics of Japanese mobility systems, and an audio visual content showing how transportation system works Japan. The main objectives were to enhance community knowledge about sustainable transport, encourage discussions about alternative modes to private motorized vehicles, and introduce the relevance of TOD principles for Banda Aceh’s urban mobility. The results show that most visitors demonstrated increased awareness and curiosity about sustainable modes after engaging with the exhibition. The activity highlights the potential for public education and advocacy through cultural festivals as a means of linking academic research, urban sustainability, and community participation.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.018 | 0.002 |
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".