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Record W2956501542 · doi:10.3390/su11143901

Trialogue on Built Heritage and Sustainable Development

2019· article· en· W2956501542 on OpenAlexaff
Lawrence W.C. Lai, Stephen Davies, Frank T. Lorne

Bibliographic record

VenueSustainability · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicUrban Planning and Valuation
Canadian institutionsNew York Institute of Technology
Fundersnot available
KeywordsSustainable developmentCultural heritageIndustrial heritageEnvironmental planningValuesCultural heritage managementLegitimacyPoliticsBuilt environmentEnvironmental resource managementBusinessEnvironmental ethicsPolitical scienceArchitectural engineeringGeographyCivil engineeringEngineeringEconomicsArchaeology

Abstract

fetched live from OpenAlex

This study represents a trialogue by a town planner, an economist, and a political scientist on the concepts of built heritage and sustainable development in terms of some features in the relationship between sustainable development and economics, sustainable development, built heritage conservation and economics, built heritage conservation and politics, built heritage conservation and sustainable development, and the tension between built heritage conservation vs. conservation/sustainable development. From planning, economic, and political angles, the feasibility and limitations of heritage building conservation in relation to conservation and sustainable development are presented. Compared to ecological conservation, built heritage conservation can easily accommodate sustainable development, as it is certainly a physical dimension for managing cultural heritage conservation. Built heritage as “heritage buildings” can articulate with real estate development via proper conservation planning. Its historical aspect signifies the legitimacy of conservation, while its proprietary aspect renders it fit for betterment.

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)0.006
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.025
Threshold uncertainty score0.083

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.015
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0070.014
Scholarly communication0.0140.011
Open science0.0010.007
Research integrity0.0060.013
Insufficient payload (model declined to judge)0.0250.003

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 head0.013
GPT teacher head0.250
Teacher spread0.237 · 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 designTheoretical or conceptual
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

Citations13
Published2019
Admission routes1
Has abstractyes

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