Implementation of Supply Chain and Logistics for Natural Disaster Management in Indonesia: A Smart Governance Perspective
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This research is at the ontological level and sociological level of the implementation of supply chain and logistics equipment for disaster management that are very significant in reducing risk of natural disaster in Indonesia. The problem is very interesting to be analyzed by conducting a descriptive qualitative research. The research used the theory of public policy, smart governance, and supply chain management and logistics. The data were collected using in-depth interview to several key informants, direct observation, and related documentation. The data were analyzed using interactive models, which were data reduction, data display, and data verification, supported by triangulation to obtain validity and reliability. The results were based on ontology, epistemology, and sociology using smart governance perspective by empowering supply chain and logistic to improve disaster management in Indonesia. Vision and mission of public policies related to natural disaster are needed to complete the facilities of prevention, equipment management and logistics supervision, providing information to stakeholders regarding regulations and sanctions in natural disaster that were carried out deliberately and balanced provision of disaster management. Therefore, it will produce a revised and detailed relevant regulation for state agencies as public officials in making regulations on natural disaster and disaster management in Indonesia. The researchers suggest that state institutions must conduct and cover smart governance in making regulations on disaster management.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it