When Housing and Communities Were Delivered: A Case Study of Post-Wenchuan Earthquake Rural Reconstruction and Recovery
Bibliographic record
Abstract
This study contributes to an in-depth examination of how Wenchuan earthquake disaster survivors utilize intensive built environment reconstruction outcomes (housing and infrastructural systems) to facilitate their long-term social and economic recovery and sustainable rural development. Post-disaster recovery administered via top-down disaster management systems usually consists of two phases: a short-term, government-led reconstruction (STGLR) of the built environment and a long-term, survivor-led recovery (LTSLR) of human and social settings. However, current studies have been inadequate in examining how rural disaster survivors have adapted to their new government-provided housing or how communities conducted their long-term recovery efforts. This qualitative case study invited sixty rural disaster survivors to examine their place-making activities utilizing government-delivered, urban-style residential communities to support their long-term recovery. This study discovered that rural residents’ recovery activities successfully perpetuated their original rural lives and rebuilt social connections and networks both individually and collectively. However, they were only able to manage their agriculture-based livelihood recovery temporarily. This research suggests that engaging rural inhabitants’ place-making expertise and providing opportunities to improve their housing and communities would advance the long-term grassroots recovery of lives and livelihoods, achieving sustainable development.
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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 | 0.001 | 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 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".