Post-disaster social capital: trust, equity,<i>bayanihan</i>and Typhoon Yolanda
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
Purpose The purpose of this paper is to explore the impact of disaster rehabilitation interventions on bonding social capital in the aftermath of Typhoon Yolanda. Design/methodology/approach The data from the project are drawn from eight barangays in Tacloban City, the Philippines. Local residents and politicians were surveyed and interviewed to examine perceptions of resilience and community self-help. Findings The evidence shows that haphazard or inequitable distribution of relief goods and services generated discontent within communities. However, whilst perceptions of community cooperation and self-help are relatively low, perceptions of resilience are relatively high. Research limitations/implications This research was conducted in urban communities after a sudden large-scale disaster. The findings are not necessarily applicable in the rural context or in relation to slow onset disasters. Practical implications Relief agencies should think more carefully about the social impact of the distribution of relief goods and services. Inequality can undermine community level cooperation. Social implications A better consideration of social as well as material capital in the aftermath of disaster could help community self-help, resilience and positive adaptation. Originality/value This study draws on evidence from local communities to contradict the overarching rhetoric of resilience in the aftermath of Typhoon Yolanda.
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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 | 0.001 | 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 | 0.001 | 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) | 0.001 | 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