A STUDY OF HISTORIC QUARTER STREETSCAPES BASED ON TYPOLOGY OF TOURIST-ORIENTED ACTIVITY—A CASE STUDY OF GEORGE TOWN AND HANOI—
Bibliographic record
Abstract
This paper studies the streetscapes of George Town (Malaysia) and Hanoi (Vietnam) through typology classification of tourist-oriented activity in these historic cities.The typology classification is based on a combination of the following criteria to define the type of tourist-oriented activity, which is considered a factor in the transformation of historic quarters' streetscapes: business activity elements, primary target market, secondary target market, and additional services provided.The study then examines the sustainable planning strategies and streetscape guidelines of rapidly changing historic quarters in Asian countries caused primarily by tourism activities.Thus, it is necessary to determine the current condition of historic quarters' streetscapes through the view of tourism-oriented activities.This study has two objectives: (1) propose a unique typology composed of various business elements and current activities, and (2) identify the current condition of two streetscapes in historic quarters (George Town and Hanoi) according to this typology.Results revealed that there were both similarities and differences between George Town and Hanoi, as evidenced by the use of the proposed typology based on streetscape elements.Differences were found to be due to the application of the conservation methods, as well as implementation of policies related to each quarter's tourism economy.Both areas have been similarly impacted by tourism activities, which are considered the main factors for streetscape formation, directly reflected by current activity and façade elements.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".