Transplanting Hong Kong high-rise housing during the time of transition
Bibliographic record
Abstract
Hong Kong has been influencing the urban development of Chongqing since China’s post-1978 reform, which is a significant aspect of the contemporary urban history of Chongqing that remains unstudied. This case study focuses on the planning, design and implementation of Wanglongmen residential quarter project (1982-1992) to preliminarily explore how Chongqing learned from Hong Kong in pursuit of modernity in the early reform. The study finds that its planning and design were inspired by orthodox Hong Kong high-rise housing mode, but when transplanted to Chongqing, such mode interacted with the legacies of China’s pre-1978 planned-economy era, including small economic volume, underdeveloped housing commodification owing partly to ideological controversy, and vague building code. The interactions produced walk-up high-rise residences, and influenced building massing and landscaping. Besides, the logic behind some design tactics changed from pursing commercial profit to pursing public interest during the transplantation. The paper argues that when China was transforming from planned economy to market economy in the early reform, the influences from Hong Kong were emerging but the remains of the planned-economy era still prevailed. Such interim hindered Chongqing from duplicating Hong Kong housing comprehensively, but enabled Chongqing to reproduce Hong Kong’s modernity in an innocent and creative way.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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 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".