Rehabilitation Methods and Revitalization Strategies in the Old Inner-City Areas of Rapid Growth Cities in Asia
Bibliographic record
Abstract
Rapid population growth is putting increasing pressure on Asian countries. Rehabilitating and revitalizing old inner-city areas in Asian countries have become essential to preserving cultural assets. With the development of old inner-city areas as urban heritage sites, determining which sustainability approach is optimal has also been a concern. Many countries in Asia have aggressively developed unique strategies for heritage conservation. In order to define the differences of rehabilitation methods and revitalization strategies in different cities and determine the implication to the area, this study is conducted for the following aims: i) To compare rehabilitation methods and revitalization policies and strategies in the old inner-city areas of rapidly growing cities in Asia by referring to four cases: Penang (George Town), Hanoi (Ancient Quarter), Shanghai (Tianzifang and Xintiandi), and Tokyo (Yanaka District); ii) To study the trends in the use of historical buildings in the cities. Target comparative in this study are “physical and manmade environment”, “sociocultural environment”, and “economic environment” in the four cities. This research uses primary data obtained in site visits and secondary data collected from archive departments, libraries, online database and local authorities. Site survey was conducted to observe the site according to the elements of the current condition and impact of heritage conservation and tourist. Observation was done by watching the site condition, and recorded in qualitative format (note-taking and photographing for case study). In addition, short interviews were engaged with local authorities and related organizations, residents and shop owner or staffs as well. In conclusion, two types of methods have generated different results. Firstly, by preserving the building structure with strict conservation rules and regulations, it has sustained a distinguishable identity and landscape feature for the places. Proper physical spatial planning and environment preservation framework are implemented. These cities specialize in tourism sector with new and creative commercial activities. It has encouraged the development of traditional craft industry through the production of innovative products. Consequently, job opportunities for local people have increased and thus boosted the local economy. However, conflict between tourism activities and the lifestyle of local community has occurred. Secondly, preserving the entire environment by using management or control of urban planning / land use method, and consensus building method have encouraged community activities and generated authentic ambience in the cities. Socio cultural elements that are compatible and harmonized with local business (traditional industry) remain as the main attraction for tourists. However, issues related to living condition and the inconsistency in implementing the preservation effort need to be tackled. Therefore, this study has concluded that both preservation methods have brought different kinds of tourism effect for the cities. It could be a reference for other cities when making decision to preserve its cultural heritage site.
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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 | 0.000 | 0.000 |
| 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".