Assessing Vulnerability and Social Capital for Disaster Mitigation and Recovery in Palu City, Indonesia
Bibliographic record
Abstract
Located in an area crossed by active faults, Palu City has a high vulnerability to natural disasters.In 2018, this city was hit by a tsunami that caused thousands of casualties and hundreds of damaged urban facilities and infrastructure.By this incident, it is crucial to carry out disaster mitigation to reduce risks in the future.This research aims to assess the level of vulnerability and social capital possessed by the people of Palu City and how it relates to creating a resilient city.The method used was quantitative, by collecting questionnaires on 268 samples distributed throughout the research area using cluster sampling techniques and analyzing data using the Social Vulnerability Index (SoVI) and the Social Capital Index.The results showed that the average level of vulnerability of Palu City to disasters is relatively high, with the most vulnerable variable being gender in the female population (0.075.Furthermore, the people of Palu City have good social capital values, especially for their solidarity values (82%), including their trust in neighbors/residents and willingness to help relatives.Thus, the level of vulnerability can be seen as a form of disaster risk reduction effort and social capital as a recovery effort.These indicators will support city resilience through mitigation strategies.Inclusiveness and participation must be prioritized in formulating policies and post-disaster management programs.
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How this classification was reachedexpand
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".