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Record W7144923845

The Transformation of the Facades of Town Houses to Accommodate Changes in the Tourist Business : A Study on the Conservation of the 36 Streets of Hanoi's Old Quarter, Vietnam

2007· article· ja· W7144923845 on OpenAlexaboutno aff
佐和子 内海, Sawako UTSUMI

Bibliographic record

VenueInstitutional Repositories DataBase (IRDB) · 2007
Typearticle
Languageja
FieldEconomics, Econometrics and Finance
TopicFinancial Crisis of the 21st Century
Canadian institutionsnot available
Fundersnot available
KeywordsTourismDowntownQuarter (Canadian coin)Capital (architecture)Old townPluckingUrban planningHistoric site
DOInot available

Abstract

fetched live from OpenAlex

The conservation of Hanoi's "Old Quarter of the 36 Streets" has been an important town planning issue for over 10 years. The history of this area began when the capital was constructed in 1010. The town was formed gathering various kinds of craftsmen together from the surrounding villages. Since then the district has been flourishing as the downtown of Hanoi. The character is.unique and attractive since historic urban structures and historic houses. remain. In June 1999 the people's Committee of Hanoi provided regulations for preserving the historic houses. In 2004 the area was designated as a national conservation area. However, while the area is the center of economy and culture of Vietnam, it is also an international tourist spot. Therefore, many changes of employment to tourist businesses are performed causing the remodeling and reconstruction of the town houses. In this paper, the variety of the changes for the new tourism is examined. In addition, changes of the facades of town houses are analyzed and the contents of appearance of town houses when changed for tourist business are clarified. As a result, 1) The increase in the business of travel agencies is remarkable. 2) Most reconstructions are for hotels. 3) The effective regulation concerning signboards especially for travel agencies must be considered.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.606
Threshold uncertainty score0.770

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.032
GPT teacher head0.250
Teacher spread0.217 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2007
Admission routes1
Has abstractyes

Explore more

Same venueInstitutional Repositories DataBase (IRDB)Same topicFinancial Crisis of the 21st CenturyFrench-language works237,207