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Record W2914058470 · doi:10.3390/su11030850

Sustainable Urban Renewal and Built Heritage Conservation in a Global Real Estate Revolution

2019· article· en· W2914058470 on OpenAlexaff
Lawrence W.C. Lai, Frank T. Lorne

Bibliographic record

VenueSustainability · 2019
Typearticle
Languageen
FieldArts and Humanities
TopicCultural Heritage Management and Preservation
Canadian institutionsNew York Institute of Technology
Fundersnot available
KeywordsCommodificationReal estateRedevelopmentReal estate developmentContext (archaeology)Urban planningEconomySustainable developmentArchitectural engineeringBusinessEnvironmental planningCivil engineeringEngineeringPolitical scienceGeographyEconomicsFinanceArchaeologyLaw

Abstract

fetched live from OpenAlex

A global real estate revolution has been transforming the urban landscape everywhere. Development and redevelopment projects have mixed with, if not become an integral part of, real estate construction. At the same time, there is a drive to commodification in this revolution, as shown by a growing trend to conserve built heritage in new development projects characterised by the rise of museums. This paper reviews some examples of attempts in various parts of the world to combine real estate development and conservation and applies the fourth Coase theorem to explore how built heritage conservation and urban renewal in Hong Kong, hitherto problematic in terms of their invasion of private property, can become a win-win outcome in the context of this global real estate revolution.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.015
Scholarly communication0.0060.004
Open science0.0000.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.024
GPT teacher head0.243
Teacher spread0.220 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations36
Published2019
Admission routes1
Has abstractyes

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