Kajian Literatur tentang Model Mitigasi Bencana Lanskap Pesisir di Kota Banda Aceh
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
Disaster mitigation is a disaster risk management strategy that can help reduce and minimize disaster impacts. Spatial planning policy is essential for disaster mitigation as it will affect the distribution of development and the vulnerability of communities to disasters. Communities living in coastal settlements are very vulnerable to disasters, so a spatial-based disaster mitigation strategy will provide an appropriate strategy for activities in coastal settlements, especially in the coastal areas of Banda Aceh City. The purpose of this research is to evaluate the role of spatial planning policies in supporting disaster mitigation, as well as to examine the implementation of mitigation strategies involving community participation and the use of GIS technology. This research used qualitative methods with a literature review approach to analyze, synthesize, and identify trends, gaps, and recommendations from various literatures related to spatial-based disaster mitigation, community participation, and GIS technology. The results of this study showed that spatial planning policies played an important role in reducing disaster risk, with a focus on proper zoning and protection of vital infrastructure. Adaptation strategies such as mangrove planting and effective evacuation routes were key to mitigation. Community participation and the use of GIS technology helped identify risks and develop hazard maps. However, challenges such as lack of policy socialization and limited spatial data remain obstacles to optimal implementation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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