"Urban-Rural Integration" in the Earthquake Zone: Sichuan's Post-Disaster Reconstruction and the Expansion of the Chengdu Metropole
Bibliographic record
Abstract
One of the more recent movements in China’s policy for periurban planning and development is the pursuit of “town and country integration” (cheng xiang yi ti hua). The officially reframed approach to planning suggests possibilities for the official reconsideration of developmental practice, but entrenched conditions of governance, land, environmental and developmental policy, and the planning profession itself constrain these possibilities. Perhaps no other context in China illustrates these constraints more dramatically than the reconstruction effort underway in Sichuan following the earthquake of May 12, 2008. Cultural, environmental and economic differences among settlements in the earthquake zone vary widely, and local and national leaders frequently mention the opportunity the recovery presents for innovative and sustainable development, but the “cataclysmic” nature of reconstruction investment, and the extremely rapid and construction-dominated approach to recovery has prevented planners from considering local conditions or alternative approaches. If the official earthquake response has served to propel urbanization along preexisting trajectories, local geographical, historical and cultural conditions nevertheless assert themselves, even if informally. The uniquely dense, dispersed and agriculturally productive Chengdu Plain has already shaped a national discourse on urban-rural relations. The expansion of Chengdu’s urban region into the narrow valleys and minority ethnic settlements across the Longmen Mountains presents new and unpredictable challenges for considering how city and country are related.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.008 | 0.005 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".