Social Capital and Community Adaptation to the COVID-19 Pandemic (Empirical Evidence: Sambirejo Village, Special Region of Yogyakarta, Indonesia)
Why this work is in the frame
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Bibliographic record
Abstract
With the ever-increasing uncertainty of the impact of humans on the environment, the study of adaptive societal behavior has gained interest in seeking to actively limit disaster-related losses. Despite numerous studies on the role of social capital in Indonesian tourism, the extent to which community social capital adapts to social order changes due to events like the COVID-19 pandemic or earthquake shocks has not been thoroughly studied. This study explored the social capital of people in tourist village areas, specifically in Sambirejo Village, Indonesia, and how it supported collective action during the COVID-19 pandemic to enhance community resilience and in turn succeed as a tourist village. Sambirejo Village has been severely impacted by the COVID-19 pandemic, resulting in a decline in tourism visits and income, highlighting the importance of social capital in fostering resilience. The research utilized a quantitative approach, collecting data through a questionnaire and analyzing descriptive statistical results. The model construct was then built and tested using a Structural Equation Modeling (SEM) analysis. The SEM analysis revealed the crucial role of government and community initiatives in fostering community resilience during the COVID-19 pandemic, emphasizing the need for well-placed policies to help communities increase their social capital and combat the pandemic effectively.
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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 | 0.003 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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